nazlabs

Gareth Lowrie

Deputy Head of Engineering at Hive HR. Newcastle upon Tyne.

Hands-on engineering leader with eight years on a multi-tenant SaaS platform, most recently as Deputy Head of Engineering at Hive HR, an employee engagement platform used largely by public-sector and non-profit organisations. I co-lead the engineering department while spending most of my week in the code, and I take on the work that spans the whole platform: data and search migrations, authentication and permissions, public APIs, and getting generative AI safely in front of customers.

Email hello@nazlabs.dev Download CV (PDF)

Impact at a glance

Measured outcomes from the last few years. Each one is explained in the selected work below.

Experience

Side business, ongoing

Founder

Paper Porch (paperporch.co.uk)

Founded Paper Porch, a website that uses AI to turn a photo of someone's home into a custom art print, delivered to their door with no human intervention.

  • Customers upload a photo of their home, even the front photo from a Rightmove or Zoopla listing, and the AI art studio paints it in their chosen style within a minute or two, with a free preview.
  • Fully automated from order to doorstep: Stripe takes payment, and the order goes straight to our third-party print partner Prodigi, which prints on archival art paper and ships with free tracked UK delivery.
  • Built and run the whole product end to end: the customer experience, AI generation, payments and the fulfilment integration.
Paper Porch logo beside a framed watercolour print of a family home on a mantelpiecepaperporch.co.ukPaper Porch: your home, as artCustom art prints made from a photo of your home. Free preview in a choice of styles, museum-quality archival paper and free tracked UK delivery. Works brilliantly with Rightmove and Zoopla photos.

Freelance project

Developer, practitioner app

Acquisition Aesthetics

Built a progressive web app for Acquisition Aesthetics, an award-winning UK academy that trains medical professionals in non-surgical aesthetic treatments, with academies in London, Manchester, Newcastle and Dublin.

  • Practitioners use it to support their ongoing learning, follow treatment protocol guidance, report complications and connect with a community of peers.
  • Installs like a native app on phone or desktop, with passwordless sign-in through Google or a one-time code sent by email.
Sign-in screen of the Acquisition Aesthetics Practitioner Portal, with Continue with Google and email sign-in options.
The Practitioner Portal sign-in screen.

Jul 2022 – present

Deputy Head of Engineering

Hive HR, Newcastle upon Tyne (remote)

Co-lead the engineering department with the Head of Engineering and sit on the company's senior leadership team. I own technical direction for data and search, survey analytics, AI features, HR system integrations and the public API, and I remain hands-on for around 80–90% of my time.

  • Retired Elasticsearch from the entire platform as the sole engineer on the migration: over 100 APIs rebuilt on MongoDB Atlas Search one endpoint at a time, each verified in Sentry to match Elasticsearch's results and speed, with zero disruption to customers and a saving of about £2,000 a month.
  • Delivered Hive's first generative AI features on AWS Bedrock: tone-of-voice classification of employee comments, an analytics assistant for survey results, and automatically generated survey insights.
  • Took the public REST API from specification to production in five phases, reusing the platform's own business logic so the API can never contradict the product's confidentiality rules.
  • Replaced browser-stored login tokens with secure, revocable sessions and magic links, which removed password sign-in entirely.
  • Designed fine-grained permissions modelled on AWS IAM, so customers can express rules like "managers see their own team" without custom roles.
  • Cut internal build times from over 30 minutes to under 10 by moving ten services to Node 24 and strict TypeScript, with the Head of Engineering.
  • Brought monitoring spend back down from over $1,000 a month, and avoided a large permanent database capacity increase by sizing autoscaling to real traffic.
  • Line-manage and develop engineers: one-to-ones, performance reviews, 9-box assessments for pay and performance decisions, and a career ladder and promotion framework co-written with the Head of Engineering.
  • Embedded AI-assisted engineering across the team, taking releases from about 80 to 170–180 a month with one fewer engineer, and merge to production in about 10 minutes.
  • Introduced a Project Requirements Document so requirements and stakeholders are agreed before work starts, and automated the department's monthly delivery metrics.

Aug 2020 – Jul 2022

Lead Software Engineer

Hive HR, Newcastle upon Tyne

Led a squad of software engineers through the full delivery cycle, from planning to launch, and ran code review, training and recruitment for the team.

  • Built the platform's first external API, with documentation generated from the code and published automatically on every deploy.
  • Delivered customer-defined webhooks, so customers' own systems can react to platform events.
  • Created per-customer live database views so the business intelligence tools read current data without breaking customer data isolation.
  • Owned the hiring loop for the team: job descriptions, interviews and feedback to every candidate.

Nov 2018 – Aug 2020

Software Engineer

Hive HR, Newcastle upon Tyne

Joined when the platform was ten separate repositories on React 16, with no public API and no data science in the product.

  • Co-created the team's first accessible component library, which the whole team now builds with.
  • Built large parts of the replacement survey builder end to end, from editing and design through scheduling, translation and sending.
  • Built two-factor authentication from scratch using Twilio.
  • Helped onboard new joiners, joined the equality, diversity and inclusion group, and organised team social events.

Mar 2018 – Nov 2018

Front-end Developer

Communicator, Newcastle upon Tyne

React, Redux and Formik in the product team building a next-generation email marketing platform.

Jan 2017 – Feb 2018

Product Operations Analyst

Communicator, Newcastle upon Tyne

Technical support for internal and external customers. Moved into part-time front-end work, which became a full-time developer role.

Selected work

Thirteen pieces of work, each explained for someone outside Hive: what it is, the problem, what I did, and the result.

Nov 2024 – Sep 2026

Retiring a second data store from the whole platform

The platform kept customer data in MongoDB but answered all search and every reporting statistic from a separate Elasticsearch cluster, kept in step by a data pipeline.

  • MongoDB Atlas Search
  • Node.js
  • TypeScript
  • feature flags
  • Sentry
Technical detail in the project index
The problem
The pipeline had to be run and paid for permanently, and it caused a recurring class of bug where search and the database disagreed on a number a customer was looking at. Removing it kept losing out to roadmap work.
What I did
Ran the migration alongside roadmap work as the sole engineer, rebuilding the platform one endpoint at a time on MongoDB Atlas Search, behind feature flags, across every survey statistic and the search in five services. For each endpoint I used Sentry to verify that every metric matched the Elasticsearch API and that query times were on par or faster before moving on. Before deleting anything, I wrote checks comparing record counts for every customer.
The result
Over 100 APIs moved and Elasticsearch decommissioned in September 2026, with zero disruption to customers and no data loss. The business is about £2,000 a month better off, the platform has one data store instead of two, and the sync pipeline is gone. The comparison work also exposed defects that had been live for years, such as blank comments counted as comments, which are now fixed.

2026

AI classification of employee comments (Voice Typology)

Voice Typology sorts the free-text comments employees leave in surveys into tone-of-voice categories, so HR teams can see how people are talking about an issue, filter by it and export it.

  • AWS Bedrock (Amazon Nova, Anthropic Claude)
  • Node.js
  • TypeScript
  • MongoDB
  • SNS and SQS
  • feature flags
Technical detail in the project index
The problem
Large surveys produce thousands of comments, and the HR teams reading them rarely have the time. The feature also had to be safe and cheap to run across millions of historical answers.
What I did
Built on AWS Bedrock with Amazon Nova and Anthropic Claude models, chosen per customer with feature flags so a model can be changed without a release. I designed for failure: a pre-filter and an "unclassifiable" outcome stop junk text being forced into a category, and classification runs separately from survey submission so an AI outage can never block a response. Only the comment text is sent to the model, never the question or anyone's identity. I also diagnosed a quality problem where forcing strict output formatting stopped the model reasoning, and fixed it by giving the model room to reason and a way to decline.
The result
Hive's first generative AI feature in front of customers, backfilled across every customer's historical comments. Choosing the model per task keeps cost per comment low at that volume.

2026

AI analytics assistant for survey results (AI Insights)

A chat assistant inside the platform where HR teams ask questions about their survey results in plain English, and get answers with the same charts used everywhere else in the product.

  • AWS Bedrock
  • tool calling
  • GraphQL
  • React
  • automated evaluations
Technical detail in the project index
The problem
Most people looking at survey results aren't data analysts. An AI with access to that data also creates a new way for confidential results to leak if it can see more than the person asking.
What I did
Built tools covering every advanced analysis capability. Every tool goes through the same API layer as the user interface, so permission and confidentiality checks are identical and the model can never see more than the user. Each tool ships with an automated evaluation judged on its real results, ambiguous survey names are confirmed rather than guessed, and nothing falls back silently to a plausible answer.
The result
An assistant that is confidential by design rather than by prompt, with a quality check on every capability before it ships.

2026

Automatically generated survey insights (Auto Insights)

An Insight tab on each survey dashboard that answers "what do I need to know, and what should I do about it?" without anyone having to analyse the data.

  • AWS Lambda durable workflows
  • R in Docker
  • MongoDB
  • AWS Bedrock
  • TypeScript
The problem
Hive's customers are mostly public-sector and non-profit organisations: time-poor, under-resourced and under governance pressure. Their managers often left dashboards not knowing what to do next, and this kind of insight was being produced by hand for the largest customers. The feature had been in progress for about five months without reaching customers.
What I did
Brought together the groundwork from Product and Data Science, then built the core within a week, plus a further week of polish. A durable AWS Lambda workflow runs statistical analysis in R and MongoDB queries over the survey data, then turns the findings into plain-language insights. I tested it against reports the professional services and data science teams had produced by hand for a large customer.
The result
It found the same insights as the hand-made reports, plus relevant ones the analysts had missed, and does it for every customer automatically. Five months of stalled work became a working feature in about two weeks. It's in internal testing ahead of launch.

2025 – 2026

Public REST API for customers' reporting tools

A documented REST API so customers can pull their survey and feedback data into their own business intelligence tools.

  • OpenAPI 3.1
  • AWS Lambda
  • oRPC
  • Zod
  • Better Auth
  • DynamoDB
  • Scalar
Technical detail in the project index
The problem
The quick approach of writing new endpoints straight against the database would create a second copy of every confidentiality rule. On an anonymous feedback product, a drifted rule means exposing an individual.
What I did
Delivered in five phases: a specification-first OpenAPI 3.1 contract including the confidentiality rules, serverless endpoints on AWS Lambda, service accounts and API keys with an admin screen, and documentation republished on every deploy. Every endpoint reuses the logic the product's own screens use rather than reimplementing it. When writes were throttled one morning, I sized database autoscaling from the real traffic pattern instead of accepting a recommendation to permanently provision 13,000 write units.
The result
A live public API whose behaviour cannot drift from the product, an in-app request log so customers can debug their own integrations, and an expensive permanent capacity increase avoided.

2025

Secure sign-in overhaul

How every user of the platform signs in and stays signed in.

  • Node.js
  • MongoDB
  • HTTP-only cookies
  • AWS Lambda@Edge
  • GraphQL
Technical detail in the project index
The problem
Sign-in used long-lived tokens stored in the browser. Any script on the page could read them, and they couldn't be revoked before they expired.
What I did
Moved to server-side sessions in MongoDB with secure HTTP-only cookies, token refresh and magic-link sign-in. This meant teaching the edge function in front of the app to read sessions, and migrating the separate survey builder app. Users whose old tokens had expired were sent a magic link instead of being dropped at a login screen.
The result
Sessions can now be revoked, tokens are no longer exposed to page scripts, and password sign-in has been removed altogether.

2025

Fine-grained permissions modelled on AWS IAM

The rules that decide what each person can see, such as a manager seeing aggregated results for their own team only.

  • TypeScript
  • CASL
  • MongoDB
  • GraphQL
  • React
Technical detail in the project index
The problem
Fixed roles couldn't express what customers needed. "Manager" meant one thing in the code and about nine different things in customer conversations.
What I did
Designed a groups, policies and statements model borrowed from AWS IAM and evaluated with the CASL library, so the same rules apply on the server and in the interface. A rule can refer to the user's own attributes, so one policy covers "their own team" for every manager. I stored each person's line manager alongside their data, so team reports use an index instead of walking the organisation chart. The old model ran alongside until the new one was proven.
The result
Customers configure access themselves instead of needing custom roles, and one policy replaces one per manager.

2024 – 2026

Statistical analysis built into the product

Key driver analysis is a statistical method that shows which survey questions most influence overall engagement, so an organisation knows where to focus. The suite also includes significance testing and finding under-performing teams.

  • R
  • Node.js
  • Docker
  • AWS Lambda
  • API Gateway
  • MongoDB analytics nodes
  • React
Technical detail in the project index
The problem
The data team ran these as R scripts by hand for individual customers. That didn't scale, and customers couldn't run it themselves.
What I did
Ran the data team's R code in containers on AWS Lambda behind an API, against a read-only analytics copy of the database to protect production. I added caching and a guided interface, then extended it to significance testing and under-performing teams, and built scores-over-time natively in MongoDB. I documented the whole pattern and coached an engineer through it, and they now own it.
The result
Customers self-serve analysis that used to need the data team, and the next R script can reach production without me.

2023 – 2026

Integrations with customers' HR systems

Keeps a customer's employee list in Hive in step with their HR system automatically.

  • TypeScript
  • AWS Lambda
  • API Gateway
  • SNS and SQS
  • JSONata
  • React
  • GraphQL
Technical detail in the project index
The problem
Building and maintaining connectors for dozens of HR systems would be a permanent burden on a small team.
What I did
Bought breadth through a connector platform, Kombo, which provides one API across many HR systems, and wrapped it in our own typed SDK so their changes don't ripple through our services. Updates arrive by webhook and fan out through queues so large organisations sync reliably, with each change processed safely if it's repeated. Customers configure mappings in the product and can transform fields themselves. When our own field list went stale, I moved us onto the vendor's live field discovery.
The result
Customers connect and map their HR system themselves, without waiting on the engineering roadmap.

2026

Confidential analytics for anonymous feedback

Anonymous feedback lets employees raise ideas and concerns without being identified. The analytics dashboard summarises it for administrators.

  • Node.js
  • MongoDB Atlas Search
  • GraphQL
  • React
Technical detail in the project index
The problem
A simple dashboard breaks the product's core promise: combine two permitted filters, such as department and location, and you can narrow the results down to one person.
What I did
Built the dashboard around a confidentiality model. Thresholds count distinct people, not rows, at both the overall and per-view level, and complementary suppression stops a hidden group being worked out by subtraction. An organisation setting controls whether filters can be combined at all. The rules are written up alongside the code so the next change doesn't break them.
The result
Administrators get useful analytics without any way to identify an individual.

2025 – 2026

Platform modernisation and faster builds

Keeping a large, decade-old TypeScript codebase current and fast to work in.

  • Node.js 24
  • TypeScript
  • MongoDB
  • Mongoose
  • React
Technical detail in the project index
The problem
Internal builds took over 30 minutes, because every internal library had to be compiled before anything that depended on it. Every engineer paid that cost several times a day.
What I did
With the Head of Engineering, moved the platform to Node 24, switched on strict TypeScript across ten services and adopted Node's native TypeScript support, which removed the build step between libraries. Across the same codebase I've also delivered three major MongoDB upgrades, moved 618 files onto a shared database library, and upgraded React from 16 to 18 with a clear path to 19.
The result
Internal builds went from over 30 minutes to under 10.

2025 – 2026

Monitoring that finds bugs and costs less

The logging, error tracking and tracing used to understand what the platform is doing in production.

  • Sentry
  • Fluent Bit
  • AWS Lambda
  • SNS and SQS
  • Node.js
Technical detail in the project index
The problem
Logs lived in a home-built Kibana setup separate from errors. Later, trace volume grew until monitoring cost over $1,000 a month, and the previous fix had been to raise the quota tenfold.
What I did
Moved errors and logs onto Sentry, as an early adopter of its log drain, and carried traces across the platform's message queues and serverless functions, which don't pass trace context on their own. I then cut trace spend by removing low-value data and sampling sensibly, while keeping the traces that matter.
The result
Monitoring spend went back to baseline. Being able to see retries also exposed events being processed twice, which I fixed by making the handlers safe to repeat.

2026

Accessibility programme

Making the platform usable for everyone, including people using screen readers and keyboards, to the WCAG standard.

  • React
  • WCAG 2.1 and 2.2
  • jsx-a11y
  • GitHub Projects
Technical detail in the project index
The problem
Hive's largely public-sector customers need accessible software, and one-off audits only ever give a snapshot.
What I did
Ran a full WCAG 2.2 audit, tracked as an issue per page per conformance level. I fixed the main web app to WCAG 2.1 AA in one pass, added automated accessibility linting to every build, and wrote the standard into the team's AI coding tools so new screens come out compliant.
The result
Main web app brought to WCAG 2.1 AA, with regressions caught automatically instead of in the next audit.

People leadership

I co-lead the department with the Head of Engineering, so alongside the technical work I manage, develop and hire engineers.

Line management and performance

  • Line-manage engineers through regular one-to-ones focused on growth, wellbeing and delivery.
  • Run performance reviews, and use 9-box assessments of performance and potential to inform salary and performance decisions.
  • Handle underperformance by diagnosing first: unclear expectations, the wrong fit, or something outside work. Then I set clear, written, time-boxed expectations rather than letting things drift.
  • Completed a mental health qualification in 2022 to support people better in difficult conversations.

Developing engineers

  • Mentored and coached engineers across the team through pairing, code review and stretch work.
  • Co-wrote the department's career ladder and progression and promotion framework, so progression is based on clear criteria rather than opinion.
  • Use a self-directed development model: the engineer picks the growth area and I create the opportunity around it.
  • Delegate real ownership, for example documenting the statistical analysis pipeline and coaching an engineer to own it end to end.

Hiring and onboarding

  • Run the full hiring loop: job descriptions, interviews, decisions and feedback, including honest feedback to unsuccessful candidates.
  • Onboard new engineers, with realistic test data and documentation that lives with the code, so they're productive quickly.

Delivery, from idea to production

  • Manage projects from ideation through to production, working closely with the Product Manager on feasibility, scope and sequencing.
  • Introduced a Project Requirements Document so requirements and stakeholders are agreed before work starts.
  • Run delivery on Kanban, with engineers owning their projects, and release large programmes in stages, often behind opt-in early access, so customers give feedback before full launch.
  • Share out-of-hours incident cover with the Head of Engineering: urgent issues fixed that night, everything else prioritised for the morning.

Department leadership

  • Member of the senior leadership team of heads of department, reviewing KPIs, performance, survey scores, goals and strategy.
  • Wrote the engineering department's vision, resource plan and hiring plan with the Head of Engineering.
  • Report delivery health with automated monthly DORA metrics, at team rather than individual level so the numbers aren't gamed.
  • Experienced in security and compliance audits, including ISO and Cyber Essentials.
  • Present engineering trade-offs in business terms, such as monthly cost or customer risk, so other departments can make informed decisions.

Culture and ways of working

  • Pioneered the company's remote working scheme by working from the Asia-Pacific region, and use that experience to run an async-first, well-documented team.
  • Built the team's AI-assisted engineering setup, so standards are applied as code is written rather than caught in review.
  • Member of the equality, diversity and inclusion group. I organise team social events, and share what I learn at conferences with the team.

How I add value

From problem to customers

Building is no longer the hard part. What I'm best at is taking an idea or a problem, drawing the real requirements out of people, and getting it from A to B, all the way to customers. It's problem solving and project management together, and it's the part I enjoy most.

Bringing the right people together

I bring together the people who feel the problem, work out with them how to solve it, and then have the technical depth to build the solution myself. Auto Insights went from five months in progress to working in about two weeks. Retiring Elasticsearch, a job that had always lost out to roadmap work, happened with zero disruption.

Experience over output

Anyone can generate code now. My value is years of lessons about what won't work, where systems hit their limits, and which decisions age badly, because I've had to live with my own for eight years.

Where I see engineering going

  • I see engineers moving towards building and maintaining a software factory: defining in code how a team builds, and designing an automated software development life cycle that they look after.
  • Humans will still review code by hand where the risk is high, so changes touching data security get a human once-over before they reach production.
  • Once the factory is running, other teams can use it directly. Support could raise a bug and have it built, tested and deployed automatically. Product could triage fully defined requirements against the existing codebase, and even have them built.
  • I've already seen the early version of this: after embedding AI-assisted engineering, the team more than doubled its monthly releases with one fewer engineer.

Responsible AI and governance

As AI moves into core products, it needs governance as well as engineering. I'm actively building my knowledge of AI governance and the new ISO/IEC 42001 standard for AI management systems. It's optional today, but I expect many customers to start asking for it. I want to help businesses shape an AI strategy that is responsible, ethical and ready for audit, building on my experience with ISO and Cyber Essentials audits.

Engineering principles

The habits behind the work above.

Make standards automatic

If a rule matters, I encode it in linting, tests or tooling so it applies by default instead of relying on memory or review.

Prove each step before the next

I migrate in small pieces and measure each one against the old behaviour, for both correctness and speed, before moving on. Migrations are expand, migrate, contract, and the clean-up step is never skipped.

Keep AI off the critical path

AI features run alongside core flows, never in front of them, so an outage costs a stale field rather than a failed action.

Fix the cause where it starts

When data is wrong, I fix whatever wrote it rather than teaching every reader to tolerate it.

Delete what no longer earns its keep

If nothing can be shown to use something, it goes. Less to run is less to break.

Price the trade-off

I give the business real options with their costs, then commit to the decision and stop relitigating it.

Technical skills

Languages and runtimes
TypeScript, JavaScript, Node.js, R, Python
Back end and APIs
GraphQL, REST and OpenAPI, Express, oRPC, event-driven services with SNS and SQS, microservices
Data and search
MongoDB Atlas, Atlas Search, Atlas Data Federation, Elasticsearch, Redis, DynamoDB, Redshift views
Cloud and infrastructure
AWS Lambda, ECS, Batch, API Gateway, EventBridge, CloudFront and Lambda@Edge, Terraform, Docker, LocalStack
AI and machine learning
AWS Bedrock (Amazon Nova, Anthropic Claude), tool-calling assistants, structured outputs, evaluation harnesses, AWS Comprehend, AI-assisted engineering with Claude Code and MCP
Front end
React, Apollo Client, Redux, Formik, Storybook, design systems, WCAG accessibility
Security, compliance and identity
Session-based authentication, magic links, two-factor authentication, CASL and policy-based authorisation, Better Auth, data anonymisation, ISO and Cyber Essentials audits, AI governance and ISO/IEC 42001 (learning)
Delivery and quality
GitHub Actions, Buildkite, Playwright, Sentry, feature flags with Optimizely, DORA metrics

Project index

All 95 projects from 2018 to 2026, each traced to the pull requests behind it. Every entry says what it is in plain English. Open one for the technical detail.

Showing all 95 projects

2026AI analytics assistant for survey results (AI Insights)A chat assistant that lets HR teams ask questions of their survey data in plain English. It only sees what the user is allowed to see, and every tool has an automated quality check.AI and data science

What I built

Extended the AI chat into an analytics assistant: tools covering every Advanced Analysis capability, per-question widgets that persist across refresh, shared visualisation components so chat output looks like the rest of the product, an admin-only tool inspector, and a hardened evaluation harness.

  • Tools call the GraphQL layer rather than internal RPC so permission checks are identical to the UI path
  • Role-aware hierarchy defaults so managers and admins get appropriately scoped answers
  • Fixed same-named-survey ambiguity that was silently switching the user to a different survey mid-conversation
  • Sentry conversation tracing; per-tool eval fixture required before a tool ships

AI and Machine Learning

Technology used

AWS Bedrock
Ran the conversational agent on Bedrock, choosing a stronger model here than for classification because the job is multi-step tool use and synthesis rather than a single label.
Anthropic Claude
Migrated model versions as they were superseded, which the per-capability model selection made a config change rather than a code change.
GraphQL
Made every tool call go through the GraphQL layer rather than internal RPC, specifically so permission and confidentiality checks are byte-identical to the UI path and there is no privileged AI reader.
Node.js
Built the tool layer in the AI service covering each Advanced Analysis capability, with role-aware hierarchy defaults, and fixed a case where two same-named surveys caused a silent switch mid-conversation — it now disambiguates rather than guessing.
promptfoo
Hardened the eval harness so the judge receives the real per-call tool results instead of the model's narration of them — we had been grading the story, not the answer. Added targeted single-case runs so the loop is fast enough to actually get used.
React
Rendered tool output through the shared visualisation components so chat answers look like the rest of the product, with per-question widgets that survive a refresh and an admin-only tool inspector.
Sentry
Traced whole conversations, including across direct Lambda invokes where trace context does not propagate over HTTP.
TypeScript
Typed each tool's parameters and return so the model's tool call is validated before it reaches a resolver — an unparseable tool call fails closed instead of being guessed at.
2026AI-assisted engineering setup for the teamTurned the team's standards into AI coding skills and review agents, so new code meets the bar as it's written rather than being corrected in review.Developer experience

What I built

Built out the team's AI-assisted engineering setup: a library of Claude skills (feature-flag creation, accessibility, PR-comment handling, dataset restore, KPI generation, analysis-script onboarding, PR babysitting), persona subagents, hooks and settings, MCP server integrations (Atlassian, Playwright, Buildkite, AWS, MongoDB, Sentry), and a standards job that mines real team activity to propose documentation updates.

  • A self-paced PR loop that drives CI to green and routes Copilot review comments to a fix skill
  • Wrote the repository README explaining how skills, agents and hooks work so other teams could adopt the setup
  • Generated engineering KPIs (DORA deployment frequency and lead time, automation scenario counts) from scripts rather than by hand

Developer Experience and AI Engineering

Technology used

Claude Code
Authored the team's skills as executable standards — feature-flag creation (library + build + Optimizely audience in one step), accessibility, PR-comment handling, dataset restore, KPI generation, and a skill that walks a new engineer through embedding an R script end to end.
GitHub Actions
Built a team-standards workflow, then debugged it through real enterprise constraints: only enterprise-owned actions allowed (pinned SHAs), --allowedTools swallowing the piped prompt (moved to stdin), and dropping claude-code-action to invoke the CLI directly on Haiku. Retired the workflow once it proved better as an on-demand skill.
MCP
Wired MCP servers for Atlassian, Playwright, Buildkite, AWS, MongoDB and Sentry, and used them for real diagnosis — profiling a slow Lambda build through the Buildkite server rather than reading YAML.
Node.js
Wrote the babysit-pr loop that drives a new PR's CI to green and routes Copilot review comments into a fix skill — with an explicit prohibition on merging, because that stays a human decision.
TypeScript
Wrote the skills' supporting scripts and the babysit-pr loop in typed Node, so the tooling is maintained like the rest of the codebase rather than as shell glue.
2026API request log for customers and supportAn in-app page showing every request made to the public API, so customers can debug their own integrations without raising a support ticket.APIs and integrations

What I built

Built an in-app API Logs page (133 files) so customers and support can see public API requests, with a shared JSON tree viewer for inspecting payloads.

Public API and Developer Platform

Technology used

React
Built the API Logs page (133 files) so customers and support can see public-API requests, and lifted its JSON tree viewer into shared components so other pages can use it.
GraphQL
Exposed the log query with filtering and pagination, scoped to the caller's organisation so a customer sees only their own API traffic.
MongoDB
Stored the request records through the audit function with a TTL so logs age out rather than growing without bound.
Node.js
Added the audit capture on the public-API request path and its deploy pipeline, recording the request without its secrets — the API key header is deliberately not stored.
TypeScript
Typed the log record so request and response payloads render structurally rather than as opaque strings.
2026Guided statistical analysis suiteGrew one statistical feature into a suite that finds under-performing teams, tracks scores over time and links straight through to what is driving them.AI and data science

What I built

Grew a single regression feature into a guided analysis suite: added Low Performing Segments as a third R Lambda (renaming the key driver Lambda to a general analysis Lambda), built Score Progressions and Response Rate Progressions natively in MongoDB, and wired click-through from a low-performing segment or T-Test result straight into Key Driver Analysis for that cohort.

  • Score Progressions built without an R Lambda — a cross-survey question-average time series over Atlas Search
  • Response Rate Progressions built over a new invitee search index
  • Separate 'key drivers for everyone NOT in this group' comparison path
  • Guided, zero-jargon step-by-step UI with results interpretation, on a shared guided-experience component set
  • Codified the whole pattern as a Claude skill so a new engineer can add the next R script end to end

Advanced Analysis and Data Science

Technology used

R
Added a low-performing segments R script as the third analysis, and built its test harness — validation, branch checks and fixture generation — so the statistical output has fixtures rather than being eyeballed.
AWS Lambda
Renamed the key driver Lambda package to a general analysis package and restructured it to host three functions, then removed the old package's infrastructure once traffic moved.
Docker
Rebuilt the image for the renamed package including a docker-compose.yml for local runs, carrying over the split R-runtime stage so adding a third script didn't triple the build time.
MongoDB Atlas Search
Built Score Progressions and Response Rate Progressions natively with no R at all — cross-survey question-average and participation time series over the answers collection and a new invitee search index.
React
Built the guided step-by-step experience with results interpretation for a non-statistical audience, plus the drill-through from a low-performing segment (or its complement) into Key Driver Analysis for that cohort.
Buildkite
Added the deploy pipeline for the renamed package and its new function.
Node.js
Extracted the resolver logic so the same analysis is reachable from GraphQL, the Open API and the AI tools rather than being welded to one caller.
TypeScript
Shared the analysis input and result types across the Lambda, the survey service route, GraphQL and the AI tools, so one analysis has one contract regardless of caller.
2026Simplified the analyst data export pipelineReplaced a multi-stage AWS orchestration pipeline with a single function call once the original performance problem had gone away, removing a whole layer to run and debug.AI and data science

What I built

Replaced a Step Functions and batch-job export pipeline with a single in-process RPC call on the survey service, after moving the export reads onto MongoDB — removing an entire orchestration layer.

  • Also added multi-answer option-question support to analyst exports and reports behind a feature flag
  • Fixed answers being split across multiple CSV columns and unescaped embedded quotes

Advanced Analysis and Data Science

Technology used

AWS Step Functions
Deleted a Step Functions state machine that orchestrated the export batch jobs. It existed because the exports were once slow enough to need checkpointing; by then every job finished in under a minute, so the orchestration was pure cost — a layer of deploy, failure modes and debugging solving a problem we no longer had.
RPC
Replaced the whole pipeline with a single in-process RPC method on the survey service, so an export is a call rather than a workflow.
MongoDB
Moved the export reads onto MongoDB first, which is what made in-process generation viable at all.
AWS Batch
Removed the two export batch jobs and their CI pipelines once nothing invoked them.
Node.js
Added multi-answer option-question support to the exports and fixed answers splitting across CSV columns and unescaped embedded quotes.
TypeScript
Kept the export's output contract identical through the rewrite, so downstream consumers saw no change.
2026Sentiment and keyword data stored with each answerMoved derived data such as sentiment and keywords onto the answer itself, a step needed to retire the separate search engine.Data and search

What I built

Moved derived answer data out of Elasticsearch and onto the answer document: sentiment (AWS Comprehend) via out-of-band enrichment, stopword-based word-cloud keywords with an Elasticsearch backfill, a has-comment flag, and campaign and question-category stamped onto answers.

  • Versioned the response index writes so a stale write could not strip stored sentiment
  • Skipped keyword generation for answers with no extractable text after finding range answers being processed
  • Repaired invitee documents that had lost stored sentiment

Data Platform and Migrations

Technology used

MongoDB
Moved derived answer data out of Elasticsearch onto the answer document: sentiment, stopword-based keywords, a has-comment flag, and campaign plus question-category stamped onto answers so a stat doesn't need a live lookup. Versioned the response index writes so a stale write can't strip stored sentiment.
AWS Comprehend
Kept Comprehend as the sentiment source but persisted its output rather than only indexing it, and stopped scoring sentiment-less answers as neutral — which had been quietly skewing every average.
Elasticsearch
Backfilled keywords from the existing ES index, and separated what ES stemming did from what Comprehend did, since word cloud and sentiment had been conflated.
Node.js
Ran enrichment out of band on its own event, skipped keyword generation for answers with no extractable text (range answers were being processed), and repaired invitee documents that had lost stored sentiment.
TypeScript
Made the enrichment fields optional-until-written so readers handle the un-enriched state rather than assuming.
2026Separated former customers' data onto its own clusterMoved former customers' databases onto a dedicated cluster, keeping the main cluster for active customers while cross-customer queries still work.Data and search

What I built

Wrote the per-organisation tooling that identifies churned customers and moves their tenanted databases onto a dedicated 'Churned' cluster, extending the Data Lake configuration so federated queries still resolve.

  • Reduces cost and blast radius by separating live tenants from retained-but-inactive data

Data Platform and Migrations

Technology used

MongoDB Atlas
Wrote the tooling that identifies churned customers and moves their tenanted databases onto a dedicated 'Churned' cluster — reducing cost and blast radius by separating live tenants from retained-but-inactive data.
Atlas Data Federation
Added the new cluster as a store in the Data Lake config so federated queries still resolve after the move.
Node.js
Built it on the shared per-tenant iteration helper so it iterates every tenant safely rather than taking a hand-maintained list.
TypeScript
Made the move idempotent and resumable, since it iterates every tenant database and a mid-run failure must not leave a customer's data split across two clusters.
2026Migrated date fields to a proper date typeConverted dates stored as text into real dates so date filters can use indexes, using an expand-migrate-contract approach with no downtime.Data and search

What I built

Migrated date-valued user attributes stored as ISO strings on the invitee and answer collections into real BSON Dates, updated the event handlers that write them, then removed the ISO-string branches from the date-bucket filters.

  • Expand-migrate-contract executed properly: write both, migrate, then delete the string branches
  • Elasticsearch intentionally left on strings since it was being decommissioned anyway

Data Platform and Migrations

Technology used

MongoDB
Migrated date-valued user attributes on the invitee and answer collections from ISO strings to real BSON Dates, so date filters can use an index instead of string comparison.
Mongoose
Updated the event handlers that write invitee and answer attributes to produce Dates, then registered models so indexes are created consistently.
Node.js
Ran it as expand-migrate-contract: write both and tolerate both, migrate the history, then — as a separate scheduled ticket — strip the ISO-string branches out of the date-bucket filters. That last step is the one people skip, and skipping it doubles the complexity instead of reducing it.
TypeScript
Removed the string-handling branches from the filter types so a future caller can't reintroduce the string path.
2026Engineering documentation moved into the codebaseAudited and migrated three Confluence spaces into a documentation site that lives next to the code, so documentation is reviewed and kept current like code.Developer experience

What I built

Migrated the Engineering, Infrastructure and Support Confluence spaces into the documentation site in the monorepo, auditing each page first for whether it was still true or had been replaced by a skill.

  • Added dedicated pages for externally-facing surfaces that had none: the Kombo HRIS webhook, the Slack apps, and Voice Typology
  • Generated a package scripts index behind a convention so it stays current

Developer Experience and AI Engineering

Technology used

Markdown
Migrated the Engineering, Infrastructure and Support Confluence spaces in, auditing each page first for whether it was still true or had been replaced by a skill — and added pages for external-facing surfaces that had none: the Kombo webhook, the Slack apps, and Voice Typology.
TypeScript
Generated a package scripts index behind a convention so it stays current rather than rotting, and documented the User Data Uploader revert behaviour in detail including what it does not cover.
2026Reduced the web app's download sizeAdded an automatic bundle-size check to every pull request, then acted on its findings, including one change that removed about 1.24 MB.Front end and accessibility

What I built

Attacked a 17.4MB (5.95MB gzip) frontend bundle: built a GitHub Action that analyses bundle size on master and on the branch and posts a comparison table to the PR, then acted on it — including removing Mongoose from the frontend bundle entirely (~1.24MB raw).

  • Action restricted to PR-open plus package.json changes so it does not run on every push
  • Also used tsdown to bring an edge function under the Lambda@Edge 50MB limit

Frontend Platform and Design System

Technology used

GitHub Actions
Wrote .github/workflows/bundle-size.yml: builds the app on master and on the branch, diffs the output and posts a comparison table as a PR comment. Then restricted the triggers to PR-open plus package.json changes after it proved noisy on every push.
Vite
Generated and read the Vite/rollup treemap output to find what was actually large, rather than guessing from dependency names.
React
Acted on the findings in the main web app — the biggest single win was removing Mongoose from the frontend bundle entirely (~1.24 MB raw), which was being pulled in through a shared type import.
tsdown
Separately used tsdown to bundle an edge function down under the hard 50 MB Lambda@Edge limit, which was blocking production deploys.
TypeScript
Wrote the bundle-report script that parses the build output and formats the comparison table posted to the PR.
2026Hackathon prototype and R&D tax claim reportingBuilt a working prototype in a three-hour hackathon, and produced per-engineer reports from the git history to support the company's R&D tax relief claim.Developer experience

What I built

Built a hackathon prototype for a new user experience inside a three-hour window, and produced per-engineer R&D tax-claim reports by analysing branches, commits and pull requests across the git history.

Developer Experience and AI Engineering

Technology used

Claude Code
Used the agent tooling to build a working prototype inside a three-hour hackathon window, and separately to produce per-engineer R&D tax-claim reports by analysing branches, commits and PRs across the git history.
React
Built the prototype's new user experience as a working demo rather than a mockup.
TypeScript
Kept it inside the real codebase's patterns so the prototype was assessable as a possible product change, not a throwaway.
Node.js
Wrote the git-history analysis tooling that produced the per-engineer R&D reports, attributing branches, commits and PRs per contributor across the full history.
2026Internal Slack app for audited admin tasksReplaced shared admin accounts with time-limited, logged access requests in Slack, and put customer data anonymisation behind two-person approval.Developer experience

What I built

Built an internal Slack app to replace shared accounts and manual back-office work: audited temporary access escalation, organisation creation, and two-person-authorised organisation anonymisation.

  • Access requests use searchable dropdowns of reasons, create the user over RPC and issue a magic link
  • Two-person rule on anonymisation — a destructive action gated on a second approver
  • Sentry trace continued across direct processor Lambda invokes, which do not propagate context over HTTP

Developer Experience and AI Engineering

Technology used

Slack API
Built the internal app on Bolt — slash commands, interactive components and OAuth install — and debugged ExpressReceiver is not a constructor under our bundling. Access requests use searchable dropdowns of reasons rather than free text.
AWS Lambda
Split the app across command, interactive and processor Lambdas so Slack's 3-second acknowledgement deadline is met while real work happens asynchronously; consolidated the surface into two functions.
RPC
Had the Slack app create users over RPC and issue magic links, so temporary access grants go through the same code path as the platform rather than direct database writes.
Terraform
Provisioned the Lambdas with provisioned concurrency, the function URLs and the secrets, and debugged a production-only apply failure that didn't reproduce in development.
Sentry
Continued the trace across direct processor invocations, which don't carry context automatically, so a failed access request is traceable end to end.
Node.js
Implemented the audited escalation flow and a two-person rule on anonymisation — a destructive command needs a second approver, and every grant writes an audit record.
TypeScript
Typed the Slack command and interaction payloads so a new command declares its inputs, rather than reaching into an untyped Bolt body.
2026Self-service tools for the support teamGave support staff safe, audited screens for common back-office jobs that previously needed an engineer with database access.Security and access

What I built

Built the internal operations surfaces support needs without shell access: Manage Invitees with bulk removal, Sync Survey with audit history, an Account Settings Danger Zone for organisation anonymisation with audit logging, and opt-ins to include roles and authorised attribute segments in user exports.

  • Every destructive action writes an audit log entry
  • Export opt-ins later opened up from support-only to customer admins on the users page

Security and Privacy

Technology used

React
Built the internal operations surfaces so support doesn't need shell access: Manage Invitees with bulk removal, Sync Survey with audit history, and an Account Settings Danger Zone — each marked with an internal pill and staff gated.
GraphQL
Added the mutations, including organisation anonymisation, all permission-gated and audited.
Node.js
Extended the organisation-service anonymise endpoint and wrote an audit log entry for every destructive action, then opened the user-export roles/AAS opt-ins from support-only to customer admins once proven.
MongoDB
Implemented bulk invitee removal and the survey sync history record, so a staff action leaves a durable trace rather than only a log line.
TypeScript
Modelled these as explicitly internal operations so they can't leak into a customer-facing route by accident.
2026EU-hosted machine translationMoved survey translation to an EU-region service for data residency, which meant reworking its authentication, and fixed timeouts under heavy load.APIs and integrations

What I built

Migrated the translation Lambda to the Cloud Translation v3 EU endpoint for data-residency reasons, which required moving from API keys to service-account authentication, and raised the client timeout after diagnosing a wave of translation timeouts under batch load.

  • v3 does not support API keys — reworked auth and per-environment project IDs as part of the move

HRIS and Integrations

Technology used

Google Cloud Translation
Migrated the translation Lambda to the Cloud Translation v3 EU endpoint for data residency, which forced a change of auth model: v3 doesn't accept API keys, so it needed service-account credentials and per-environment project ids.
AWS Lambda
Reworked the translation function for the new client and credentials, keeping the existing invocation contract.
Node.js
Raised the client timeout to 15s after several hundred 'Translation API timed out' errors under batch load, having confirmed it was client-side timeout rather than upstream failure.
TypeScript
Typed the v3 response shape, which differs from v2, so the migration surfaced at compile time.
2026Confidential analytics for anonymous employee feedbackA dashboard for anonymous feedback with a confidentiality model that stops anyone combining filters to identify an individual.Product features

What I built

Built the anonymous feedback dashboard and, with it, a confidentiality model for free-form employee feedback: distinct-user gating rather than row counts, a universal overall gate, and complementary suppression to defeat differencing — documented in a dedicated CONFIDENTIALITY.md.

  • Only segment and date attributes are gated; categories are treated as content, not identity
  • Gated behind two flags so staffs could preview safely
  • Filters and CSV export share the same attribute normalisation as the dashboard queries

Anonymous feedback

Technology used

Node.js
Built the confidentiality model: gating on *distinct respondents* rather than row count (one person leaving five pieces of feedback is not five people), a universal overall gate, and complementary suppression so you can't derive a suppressed segment by subtracting the others. Documented it in a CONFIDENTIALITY.md beside the code.
MongoDB Atlas Search
Built the statistics API over suggestions with Atlas Search, and fixed the dashboard reporting Confidentiality Protection everywhere when the numbers weren't actually below the limit.
React
Built the anonymous feedback dashboard reusing the shared visualisation components and the feed's filters, gated behind two flags so admins could preview without exposing it.
GraphQL
Exposed the statistics with the gating applied server-side, so the browser never receives suppressed values.
AWS Bedrock
Surfaced the AI-derived voice typology alongside the statistics, with the same distinct-user gating applied to it — an AI-derived category is still a segment that can identify someone.
TypeScript
Decided and encoded which attributes are identity-bearing — segments and dates are gated, categories are content — because over-suppressing makes the tool useless and the promise pointless.
2026Anonymous feedback: public feed, voting and automatic taggingLet employees share feedback publicly and vote on it, and automatically tagged each piece with sentiment, keywords and tone.Product features

What I built

Extended anonymous feedback for employees and admins: a privacy toggle with a public employee feed, upvoting from public cards, admin updates on feedback, and an out-of-band enrichment pipeline adding sentiment, keywords and voice typology to suggestions.

  • Two-event enrichment pattern — first event persists, second enriches — so writes are never blocked on AI
  • Shared sentiment and keyword logic extracted into a new shared analysis library
  • Removed the confidentiality-limit requirement from the public feed once admins opted in explicitly

Anonymous feedback

Technology used

SNS/SQS
Built enrichment as a two-event pattern: the first event persists the suggestion, a second enrichment event does the AI and analysis work — so a submission is never blocked on an AI call.
Node.js
Extracted the shared sentiment and keyword logic into a new shared analysis library so surveys and anonymous feedback use one implementation, and built the backfill for existing suggestions.
AWS Comprehend
Used Comprehend for sentiment on suggestion text, matching the survey-answer path.
AWS Bedrock
Ran voice typology classification over suggestions, gated on both a feature flag and an organisation setting.
React
Built the privacy toggle and public employee feed, upvoting from public cards, and admin updates on feedback.
MongoDB
Stored the enrichment on the suggestion document, and removed the confidentiality-limit requirement from the public feed once an admin has explicitly opted in.
TypeScript
Modelled the enrichment as optional-until-processed so consumers handle the pre-enrichment state explicitly.
2026Fixed timeouts in score-over-time reportingTraced a report that timed out for the largest customers to the shape of the data and the index choice, then made it reliable.Platform and reliability

What I built

Chased Score Progressions from a production timeout to a reliable query: slimmed a bloated Atlas Search stored source, bounded the surveys considered, moved off Atlas Search to a btree match where that was faster, anchored date buckets to the survey open date, and stopped hinting a segments-led index on unsegmented runs.

  • Root cause of the original 20s+ timeout was bloat from invitee demographic segments in the stored source
  • Learned and documented that an unbounded multikey leading field in a hint is a production timeout waiting to happen

Observability and Reliability

Technology used

MongoDB Atlas Search
Slimmed the Atlas Search stored source after finding bloat from invitee demographic segments was the real cost — I was pulling far more bytes per document than the query needed — and later moved the query off Atlas Search to a btree match where that was genuinely faster.
MongoDB
Stopped hinting the segments-led index on unsegmented runs, because an unbounded multikey leading field is a production timeout waiting to happen; bounded the surveys considered; and anchored date buckets to the survey open date rather than the epoch.
Node.js
Diagnosed it from production explain output and learned the general lesson that a plan cannot show you the cost of draining documents — the plan looked healthy while all the time went into rows flowing through it.
TypeScript
Grouped progression questions by text or source id so cross-survey matching works when a question was rebuilt, without reintroducing the timeout.
2026Public REST API for customers' BI toolsTook the platform's public API from specification to production, reusing the platform's own business logic so the API can never contradict the product.APIs and integrations

What I built

Led a confidentiality-preserving public REST API for BI tools — from spec to production across five phases: OpenAPI 3.1 spec and privacy rules behind a flag, Lambda REST endpoints, service accounts and API keys via Better Auth with an admin UI, a Scalar documentation site served from the Lambda and republished on deploy, and full observability.

  • Endpoints for surveys, components with stats, key drivers, survey metrics, anonymous feedback submissions, peer recognitions, and category listings
  • Extracted logic from existing Express resolvers rather than duplicating it, so platform and API stay in step
  • Anonymity and confidentiality rules enforced in the API layer; UTC-only dates documented explicitly
  • An admin-only organisation setting as the master switch
  • DynamoDB autoscaling added after a write-throughput throttle incident

Public API and Developer Platform

Technology used

OpenAPI
Authored the OpenAPI 3.1 specification as the contract first, with the confidentiality and anonymity rules written into it, and documented UTC-only dates explicitly rather than accepting a timezone and guessing.
Better Auth
Implemented service accounts and API keys on Better Auth, including its API-key verification middleware — and fixed the types properly rather than casting the verify result through any.
AWS Lambda
Built the REST surface as Lambdas — one route per file — covering surveys, components with stats, key drivers, survey metrics, anonymous feedback submissions, peer recognitions and category listings.
oRPC
Used oRPC procedures as the typed boundary between the route registry and the handlers, so a new endpoint is a schema plus a procedure rather than hand-rolled parsing.
Scalar
Served the Scalar API reference from the Lambda itself and republished it on every deploy, so the docs cannot drift from the deployed spec.
Node.js
Extracted logic out of the existing Express resolvers into reusable functions so the public API and the platform UI share one implementation of every confidentiality rule — the alternative was two copies that drift.
Terraform
Provisioned the Lambdas, ALB listener rules and array-form headers, SSM parameters (hitting and fixing a namespacing collision), and DynamoDB autoscaling for the function-URL table.
Sentry
Added tracing, metrics and logs.
React
Built the admin UI for creating and revoking service accounts and API keys, and relabelled the permission names shown in both the dialogs and the Scalar docs after they read as internal jargon.
MongoDB Atlas Search
Backed the list endpoints with Atlas Search so filtering and pagination are index-served rather than scanning per request.
TypeScript
Typed the per-endpoint surface so adding a route means declaring its Zod schema, permissions, docs and lambda config in one place the compiler checks — the alternative was six files that drift silently.
2026Category management for the question libraryLet customers organise their survey question library into categories, with built-in categories protected from deletion.Product features

What I built

Added a Categories tab to the Question Bank with full category management, built on a typed router with Zod validation, protected by a dedicated permission and system-category protection so built-in categories cannot be destroyed.

Survey Builder and Planner

Technology used

Typed router
Built the category endpoints on a typed router — the current convention for new survey service routes — with collocated Zod validators and scope guards, rather than adding to the legacy Express routers.
Zod
Defined the category schemas inline with the routes, which is also what generates the OpenAPI entry.
React
Built the Categories tab on the Question Bank page, gated behind a dedicated permission.
Node.js
Added system-category protection so built-in categories can't be renamed or deleted, and a dedicated permission for reading categories.
GraphQL
Added the category queries and mutations to the schema so the frontend goes through the GraphQL layer rather than calling the survey service route directly, keeping permission checks on one path.
TypeScript
Modelled system versus custom categories as distinct so the protection is type-level, not a runtime string check.
2026Redesigned question-by-question survey reportingRebuilt per-question results as a searchable, side-by-side view inside the survey dashboard, so managers can move between questions without losing context.Product features

What I built

Rebuilt the question-level reporting experience as a master-detail dashboard embedded in the survey dashboard: a searchable, sortable question navigator with config pills, per-question-type layouts, a response-rate ring, merged score and answer cards, redesigned option-question distribution and segment breakdown, and a responses tab with comment pagination.

  • Ran four rounds of delivery-team and stakeholder feedback through the design
  • Designed for an executive who logs in a handful of times a year — clarity over density
  • Per-user Early Access opt-in via an in-app banner rather than a big-bang cutover
  • Accessibility, flag-aware routing and end-to-end coverage shipped with it

Survey Analytics and Reporting

Technology used

React
Rebuilt question-level reporting as a master-detail dashboard: a searchable, sortable question navigator with config pills, per-question-type layouts, a response-rate ring, merged score/answer cards, and a responses tab with comment pagination — fixed to use an offset rather than a growing limit.
Recharts
Redesigned the option-question answer distribution, option spread and segment breakdown, widened radar labels so full option text is readable, and fitted progression y-axes to the scores actually in view so small movements are visible.
GraphQL
Wired the per-question queries and applied dashboard filters to the embedded progressions, and fixed self-select-demographic filters not carrying through to the question detail page.
MongoDB
Fed it from the migrated Atlas Search stats, including per-question sentiment and voice typology.
Node.js
Added flag-aware routing and the per-user Early Access opt-in so customers self-select rather than being cut over.
Playwright
Wrote the .feature specs and page objects for scale, eNPS, option and text question types, plus confidentiality and demographic variants, and realigned them through four rounds of redesign.
TypeScript
Modelled per-question-type configuration so each type's dashboard is data-driven rather than a switch statement per widget.
2026Upgrade path to React 19Replaced the libraries blocking React 19 in a decade-old codebase, delivering the work piece by piece alongside product changes rather than as one large project.Platform and reliability

What I built

Cleared the path to React 19 across a decade-old application: react-router v3 → v7, recompose removed in favour of hooks, redux-form → Formik on shared form infrastructure, react-redux 5/7/9 running side by side via aliases while SurveyBuilder moved to react-redux 9 / redux 5 / RTK 2, plus react-select v5, recharts v2, Storybook 8.6, testing-library 16 and removal of deprecated APIs.

  • Identified redux-form's use of legacy context — removed in React 19 — as the true blocker and planned around it
  • Ran the rename-unsafe-lifecycles codemod rather than hand-editing

Platform Modernisation and Upgrades

Technology used

React
Cleared the path to 19 on a decade-old app: identified redux-form's use of legacy context — removed in 19 — as the real blocker, removed deprecated APIs, and ran the rename-unsafe-lifecycles codemod rather than hand-editing.
Redux
Ran react-redux 5, 7 and 9 side by side via package aliases so the migration could be incremental, and took SurveyBuilder to react-redux 9 / redux 5 / RTK 2.
Formik
Built shared Formik infrastructure and migrated forms off redux-form in phases, attaching each form's migration to work Product wanted anyway.
Storybook
Upgraded Storybook 7 to 8.6 for React 19 support, including .storybook/main.ts and preview changes.
Recharts
Upgraded Recharts 1.3.5 to 2.15 and react-select 3 to 5, both of which were React-19 blockers.
Vite
Kept the build working through the router migration — react-router v3 to v7 across 305 files — and removed recompose, migrating its HOCs to hooks with a shared compose utility.
TypeScript
Upgraded @testing-library/react 13 to 16 and fixed the type fallout, so tests weren't the thing blocking the upgrade.
2026Analytics dashboard for peer recognitionRebuilt the dashboard showing who recognises whom over time, and designed how one recognition can go to many people.Product features

What I built

Rebuilt recognitions under the modern app directory with an Atlas Search-backed dashboard: a Top Recognisers table, date-histogram bucketing with offset alignment, normalised attribute filters, and a multi-recipient architecture design for sending one peer recognition to many people or a whole segment.

  • Date-histogram offset alignment fixed buckets that did not line up with the customer's reporting periods

Peer recognition

Technology used

MongoDB Atlas Search
Backed the recognitions dashboard with Atlas Search after removing Elasticsearch from the service, including the insight endpoints.
React
Modernised the recognitions pages, built the dashboard and the Top Recognisers table, and fixed a default date being written into the URL but never passed to the initial query — so the page showed unfiltered data while claiming a filter.
Node.js
Implemented date-histogram bucketing with offset alignment so buckets line up with the customer's reporting periods rather than the epoch, and normalised then denormalised attribute filters so dashboard and insight queries agree.
GraphQL
Exposed the dashboard aggregates and the by-user-by-category insight later reused by the public API.
TypeScript
Designed the multi-recipient model for sending one peer recognition to several people or a whole segment.
2026Shared chart components for survey resultsExtracted the survey charts into shared components so the AI assistant, dashboards and analysis tools all present results the same way.Front end and accessibility

What I built

Lifted the survey dashboard's visualisations into a shared component tier so the AI chat, the question dashboard and the analysis tools all render the same charts, and lifted the API logs JSON viewer into shared components alongside it.

  • Fixed downloaded chart images losing fonts and colours
  • Fitted progression y-axes to the scores actually in view so small movements are visible

Frontend Platform and Design System

Technology used

React
Lifted the survey dashboard's visualisations into a shared tier so the AI chat, question dashboard and analysis tools render the same charts instead of three divergent copies.
Recharts
Standardised the chart components and their theming behind the shared tier, so a chart's colours and axes come from one place instead of each dashboard re-specifying them.
html-to-image
Replaced html2canvas after customers reported grey blocks in exported heatmap PNGs, and fixed downloaded charts losing their fonts and colours — the export path renders outside the app's style context.
TypeScript
Defined one visualisation prop contract so a new consumer gets the charts without re-deriving the data shape.
2026Bulk user import with safe undoMade the spreadsheet user import usable and robust, and added an undo that reverses only the changes that are still safe to reverse.Security and access

What I built

Put a real UI on the existing bulk user importer and then hardened it: error surfacing, segment matching across case and whitespace variants with deduplication, blank-row tolerance, unique-username failure handling, a six-month retention window, and the ability to revert a confirmed upload.

  • Revert implemented as inverse operations with a newest-only conflict policy, and documented in detail including what it does not cover
  • Removed a misleading 'Users To Be Deleted' banner and fixed counts that did not reconcile with the status totals
  • Added a Sentry feedback button to the uploads list so users can report problems in context

Users, Roles and Authorisation

Technology used

React
Put a real UI on the existing bulk importer, surfaced per-row errors, removed a misleading 'Users To Be Deleted' banner, fixed counts that didn't reconcile with the status totals, stopped showing upload counts before processing finished, and added a Sentry feedback button to the uploads list.
Node.js
Implemented revert as *inverse operations* with a newest-only conflict policy — a snapshot restore would silently destroy edits made since — and documented exactly what it does and does not cover, because a misunderstood safety feature is worse than none.
MongoDB
Resolved case-variant and whitespace-variant segment names to a single deduplicated segment id, stopped creating segments found only in the Manage Access column, and extended the upload retention TTL to six months.
AWS Batch
The create/update/delete work runs as batch jobs; added a revert batch job with its own deploy pipeline, and made the importer skip blank CSV rows instead of failing the whole run.
SNS/SQS
Carried the per-row operations through the queue so a large upload is incremental and resumable.
GraphQL
Exposed upload history and the revert mutation, with authorisation checks on the uploader routes.
TypeScript
Modelled each operation with its inverse so revert is derived from the operation type rather than special-cased per column.
2026AI tone-of-voice classification for survey comments (Voice Typology)Uses large language models on AWS Bedrock to sort free-text employee comments by tone, so HR teams can spot themes without reading thousands of comments. Hive's first generative AI feature.AI and data science

What I built

Built Hive's first generative-AI product feature: classification of free-text survey comments into tone-of-voice categories using Amazon Nova and Anthropic models on AWS Bedrock, stored on the answer document, surfaced as tone cards and filters, exportable to CSV, and backfilled for every organisation by migration.

  • Diagnosed a divergence between platform output and the Bedrock console: constrained structured generation was suppressing the model's reasoning — fixed by adding an explicit reasoning field plus a no-opinion escape hatch
  • Added an 'unclassifiable' sentinel and a word pre-filter so junk text is not forced into a category
  • Model selectable per organisation via feature flags
  • Enabled by default at the organisation service once proven; documented on the docs site

AI and Machine Learning

Technology used

AWS Bedrock
Ran classification on Bedrock and hit a real divergence: identical prompts gave different answers in our pipeline versus the console. Constrained structured generation was suppressing the model's reasoning — fixed by adding an explicit reasoning field plus a no-opinion escape hatch.
Amazon Nova
Chose Nova for per-comment classification on cost grounds at backfill volume, and verified its behaviour against the Bedrock console playground when output disagreed.
Anthropic Claude
Made the model per-organisation selectable so a customer can be moved onto an Anthropic model when Nova underperforms on their content, without a deploy.
Optimizely
Used feature flags as the model-selection mechanism, not just an on/off gate — the flag value picks the model.
MongoDB
Stored the classification on the answer document and wrote the backfill migration for every organisation. Versioned the enrichment re-index off a dedicated flag so a stale write can't strip a stored classification.
Node.js
Built the classifier in the shared AI library, with a word pre-filter and an unclassifiable sentinel so junk text is never forced into a category, and split the stored enum from the display enum so the sentinel persists without polluting customer-facing aggregations.
React
Built the tone cards, chips and filters — including separate filter options for uncategorised versus explicitly unclassifiable comments — and the CSV export, fixing answers being split across columns and unescaped embedded quotes.
GraphQL
Exposed the classification and its aggregate counts, including a "left to classify" count that later exposed a 250-answer gap no test had covered.
TypeScript
Derived the classification types from Zod schemas so the stored enum, the GraphQL enum and the display labels cannot diverge — which is what made splitting stored from displayed values safe.
2026Accessibility programme (WCAG 2.1 AA)Audited the platform against the accessibility standard, fixed the main web app in one pass, and added automated checks so problems don't come back.Front end and accessibility

What I built

Ran a platform-wide accessibility programme: a full WCAG 2.2 audit matrix, a GitHub project with milestones and an issue per page per conformance level, WCAG 2.1 AA compliance across the main web app, jsx-a11y linting to stop regressions, and WCAG 2.2 work on the employee app dashboard and authentication templates.

  • Wrote an accessibility Claude skill so the standard is applied by default in new work rather than audited afterwards
  • Fixed specific violations including ARIA on the RichTextEditor contenteditable node and status-message announcement for Loading and Banner
  • Distinguished version (2.1/2.2) from conformance level (AA) explicitly in the plan

Accessibility

Technology used

React
Ran the remediation across the main web app to WCAG 2.1 AA, plus WCAG 2.2 work on the employee app dashboard and the authentication templates. Specific fixes included wiring ARIA onto the RichTextEditor's contenteditable node and announcing Loading and Banner as status messages.
jsx-a11y
Added jsx-a11y linting as the durable half — an audit is a snapshot, a lint rule is a policy — so the violations can't quietly return.
Claude Code
Wrote an accessibility skill encoding the standard so new components come out compliant rather than being remediated later, and used it to generate the remaining-work report against the earlier audit.
Playwright
Kept the e2e suite passing through the markup changes, since ARIA and role changes move the selectors the specs rely on.
TypeScript
Built the audit matrix and tracked it as a project with an issue per page per conformance level, distinguishing version (2.1/2.2) from conformance level (AA) explicitly.
2025–2026Cross-customer benchmarking without copying dataUsed MongoDB's federated queries so benchmarks can compare results across customers without moving data between their separate databases.Data and search

What I built

Introduced MongoDB Atlas Data Lake/Federation so benchmarking could aggregate across tenant databases without copying data out, and reworked the benchmarking Lambda to write results directly and run aggregations in parallel within a time bracket.

  • Dropped the view layer benchmarking previously depended on
  • Extended the federation config to a new 'Churned' cluster when churned customers were separated out

Data Platform and Migrations

Technology used

Atlas Data Federation
Introduced Data Federation so benchmarking aggregates across per-tenant databases in place, without copying customer data into a shared store — and extended the federation config with a new store when churned customers moved cluster.
MongoDB Atlas
Configured the federated data sources and connection strings per environment, and fixed those connection strings when they were wrong in infrastructure.
AWS Lambda
Reworked the benchmarking Lambda to write results directly rather than through database views, and parallelised aggregations within a time bracket.
Node.js
Scripted the federation configuration so adding a store is repeatable rather than console clicking.
TypeScript
Typed the federated query results so a cohort returning no data is an explicit empty case rather than an undefined that silently becomes a zero in a published benchmark.
2025–2026Removed the search engine from four more servicesMoved recognition, feedback, messaging and user search from Elasticsearch to MongoDB Atlas Search, then deleted the old pipelines.Data and search

What I built

Removed Elasticsearch service by service: user service queries and indices, recognition-service to Atlas Search, suggestion-service via versioned /v2 routes, and messenger-service including its search SQS pipeline — deleting the event handlers, packages and indices behind each.

  • Used /v2 routes plus flags so each service could be cut over independently
  • Wrote integrity-check scripts comparing MongoDB and Elasticsearch document counts per collection before deleting anything
  • Eliminated a whole ETL surface and the data-consistency class of bug that came with it

Data Platform and Migrations

Technology used

MongoDB Atlas Search
Replaced Elasticsearch in recognition-service and suggestion-service with Atlas Search, and moved user service recipient counts onto it, adding a users search index including the token index.
MongoDB
Denormalised and normalised attribute filters so dashboard queries and CSV exports filter identically, and fixed status filtering that broke because status lived in a separate collection.
Elasticsearch
Removed it service by service, deleting event handlers, packages and indices — and in user service removed the final two routes then the indices in a dedicated migration.
SNS/SQS
Removed the messenger search SQS pipeline entirely along with its handlers — the queue existed only to feed the index.
Node.js
Introduced versioned v2 routes so each service could be cut over behind a flag, then removed the flag checks and the v1 routes once the GraphQL layer pointed only at v2.
TypeScript
Kept the route contracts identical across v1 and v2 so the GraphQL layer's switch was configuration, not a rewrite.
2025–2026Redesigned how manager access is administeredRebuilt the admin screens that control what each manager can see, with personal attributes private by default.Security and access

What I built

Rebuilt how manager access is administered: a new View User page, a revamped user update experience, attributes private by default, a redesigned attributes management page, segment renaming from Manage Attributes, and fixes to role naming in user filters.

  • Closed a defect where employees could read some full user information
  • Gated the users settings page behind a private-data permission

Users, Roles and Authorisation

Technology used

React
Built the View User page, the revamped user update experience, the redesigned attributes management page and segment renaming from Manage Attributes, and fixed role names in user filters.
GraphQL
Reworked the queries so manager-access changes appear without a page refresh — they had needed one — and gated the users settings page behind a private-data permission.
MongoDB
Made attributes private by default, which inverted the exposure default, and fixed segment creation from the Manage Access path.
Node.js
Closed a defect where employees could read some full user information, and skipped user attributes referencing deleted segments when loading a user rather than erroring.
TypeScript
Split public from private user properties as distinct types, so a resolver returning the wrong one fails to compile.
2025–2026In-app messaging rebuildFixed long-standing duplicate and permission bugs in the platform's messaging feature, then moved it off the search engine.Product features

What I built

Fixed long-standing Messenger defects and then modernised it: unique indexes on relations and conversations to stop duplicate creation, mark-read authorisation, memoised author resolution, Mongo-backed v2 read routes behind a flag, and complete removal of Elasticsearch and the search SQS pipeline.

  • Wrote a messenger integrity-check script auditing message, conversation, participant and relation counts per customer before the cutover

Messenger

Technology used

MongoDB
Added unique indexes on messenger relations and conversations to stop duplicate conversation creation at the database level, rather than guarding in application code.
Node.js
Built Mongo-backed v2 read routes behind a feature flag, memoised author lookups, fixed mark-read returning 401, and handled user-not-found properly instead of throwing.
Elasticsearch
Removed ES and the search SQS pipeline from the service, having first written an integrity script comparing message, conversation, participant and relation counts per customer.
TypeScript
Fixed relates-to text overlapping in the UI and kept the v2 route types matching v1 so the switch was flag-only.
2025–2026Logging, tracing and monitoring cost controlMoved errors and logs onto Sentry with tracing across services, then brought monitoring spend back down from over $1,000 a month.Platform and reliability

What I built

Moved Hive off a home-rolled Kibana setup onto Sentry for both errors and logs, working with Sentry to be an early adopter of their Fluent Bit log drain. Then extended coverage to every deployed Lambda and batch job, added distributed tracing across SQS/SNS handlers, and cut trace spend back down.

  • Removed all legacy OpenTracing/span code in two passes
  • Diagnosed a span explosion that had pushed Sentry spend past $1,000/month and cut it back by dropping Express layer spans and sampling traces at 1%
  • Added request and user context to every log line; promoted system-critical logs to FATAL
  • Forced session replay around SSO sign-in behind a flag to debug an intermittent customer issue
  • Made event handlers idempotent so retries stopped double-processing

Observability and Reliability

Technology used

Sentry
Ran the migration off a home-rolled Kibana setup to Sentry for errors and logs, and worked with Sentry to be an early adopter of their Fluent Bit log drain. Then diagnosed a span explosion that had pushed spend past $1,000/month — dropped Express layer spans and cut trace sampling to 1%, while verifying we still capture spans inside the route controllers where the queries live.
Fluent Bit
Configured the log drain end to end — the part that took real trial and error, since we were among the first using it against Sentry.
SNS/SQS
Implemented trace propagation through the shared messaging library so a trace survives a queue hop. HTTP propagates context for free; SQS/SNS does not, so async handlers were starting orphan traces exactly when causality mattered.
Node.js
Made event handlers idempotent once retries became visible — we had been double-processing conversation and recognition created events. Added request and user context to every log line, promoted system-critical logs to FATAL, and fixed VError instances stringifying as {}.
AWS Lambda
Put the shared instrumentation library on every deployed Lambda and routed their logs into Sentry — previously only a couple of functions were covered.
AWS Batch
Extended the same logging and tracing to the batch jobs, which had been entirely dark.
Terraform
Declared the Sentry projects, alerts and related resources as code, including targeting just the new Sentry resource on apply rather than a full plan.
React
Instrumented the frontend — replays, masking the rich-text editor out of replays, raising the maximum value length to stop truncating useful payloads, and a forced session replay around SSO sign-in behind a flag to catch an intermittent customer issue.
TypeScript
Built the instrumentation library as a typed wrapper so a service or Lambda opts into logging and tracing with one import rather than per-package Sentry configuration.
2025–2026Automated organisation-wide survey reportsFirst phase of automatically generated organisation reports, including the screens to request and manage them.AI and data science

What I built

Delivered phase 1 of automated organisation-level reporting: frontend design and implementation, GraphQL create/read/list/delete, survey service routes, a separate AI feature flag, and a refactored exports modal — then hardened the Python/R report generator behind it.

  • Typed Python errors surfaced with context instead of opaque failures
  • Manager-report narratives requested concurrently, behind a configurable limit
  • Manager-report timeouts reported rather than hanging on 'Processing'
  • Staff given visibility of every organisation and manager report

Advanced Analysis and Data Science

Technology used

React
Designed and built the Organisation Reports UI, refactored the exports modal it lives behind, added clearer messaging for why a report is disabled, and a legacy-reports migration banner that users can dismiss, remembered in local storage.
GraphQL
Added create, read, list and delete for reports, plus a separate AI feature flag so the AI narrative can be enabled independently of reports themselves.
Node.js
Added the survey service routes behind them, and let staffs see every organisation and manager report rather than only their own.
Python
Hardened the generator: typed errors with context instead of opaque failures, Q-number stripping from thematic titles, and correct handling of self-select demographic questions in eNPS attributes.
AWS Lambda
Ran generation in the report-generation Lambda, made timeouts report themselves instead of hanging on 'Processing', and requested narratives concurrently behind a configurable limit.
AWS Bedrock
Generated the narrative commentary, gated behind its own flag so a model problem doesn't take reports down.
R
Scoped: the report image carries a regression script whose dependency install I own; the statistical authoring here is the data team's.
TypeScript
Typed the Python output boundary, with tests, so a malformed report result is caught at the seam.
2025–2026Report generator for managers and organisationsMaintained and hardened the Python and R service that produces downloadable survey reports, including faster builds and clearer errors.AI and data science

What I built

Maintained and hardened the manager and organisation report generator: self-select-demographic questions in eNPS attributes, non-PNG logos, response-rate CSV correctness, month formatting, Q-number stripping from thematic titles, typed error surfacing, concurrent narrative generation, and build-time dependency caching.

  • Ran first-time setup documentation so a new engineer can run the R and Python stack locally

Advanced Analysis and Data Science

Technology used

Python
Own the manager-pack and organisation-report generators. Added Pydantic settings models with a loader and a merging model, replaced bare exceptions with typed errors carrying run context, stripped Q-numbers out of thematic titles, and built the multi-answer multiple-choice graph path.
Docker
Restructured the Lambda image so the Python and R dependency installs became cached layers instead of running on every deploy — the Rscript -e install.packages(c('dplyr','jsonlite')) step and the pip install were the whole build cost. Also moved the image to Node 24.
R
Scoped: the image ships an engagement regression in R, and I own its dependency install and caching, not the statistical code itself — the R I authored is in the analysis Lambdas.
Node.js
Wrote the TypeScript Lambda handlers that invoke the Python and parse its output, with unit tests — including making a non-zero exit surface as a typed error rather than a hang.
Sentry
Forwarded the report script's stdout/stderr into Sentry and logged each manager-report stage with durations and run context, so a failing report says which stage died instead of sitting on "Processing".
AWS Lambda
Added a concurrency setting so narrative generation fans out concurrently inside one invocation, and made manager-report timeouts report themselves rather than silently exhausting the Lambda budget.
TypeScript
Typed the Python output boundary and its parser with unit tests, so a malformed report result is caught at the seam rather than surfacing as a broken PDF.
2024–2026Action planning from survey resultsA new service that turns survey insights into tracked actions with owners and due dates, including AI-suggested actions.Product features

What I built

Built the Action library and Action service from scratch: action creation from survey insights, a dashboard with owner/contributor/follower filters and aggregation, an updates timeline, due-date bucketing, categories, and AI-suggested actions with guaranteed structured outputs.

  • Structured outputs made the AI suggestions safe to render without defensive parsing
  • Assignee combobox surfaces the highlighted attribute as a pill, matching patterns elsewhere in the app

Survey Analytics and Reporting

Technology used

Node.js
Built the actions service from scratch — models, events and routes — and fixed due-date bucketing that wasn't bucketing correctly, and an update event that was emitted without the record's ID.
MongoDB
Modelled actions with owner, contributor and follower relations and added the aggregation behind the dashboard filters and counts.
AWS Bedrock
Added AI-suggested actions with guaranteed structured outputs, so the suggestion can be rendered directly rather than defensively parsed — and stored the model ID on the record after finding it wasn't being persisted, which made it impossible to attribute a bad suggestion to a model.
React
Built the dashboard, the creation modal from a survey insight, the updates timeline, assignee filters with the highlighted attribute shown as a pill, and the action matrix image download — fixing its fonts and hexagon colours in the exported PNG.
GraphQL
Exposed actions and their aggregates, and skipped the unread-count query entirely for users without permission to read actions rather than letting it 403.
TypeScript
Typed the action relations so an assignee filter can't be applied to a relation that doesn't exist.
2024–2026Removed hidden inefficient queries from the API layerFound data loaders that looked batched but fetched records one at a time, replaced them with real batch endpoints, and fixed an ordering bug on the way.Platform and reliability

What I built

Audited the GraphQL service for N+1 patterns — including DataLoaders that were fanning out to a getById endpoint per id rather than a real batch endpoint — and converted them: roles, recognition categories, suggestion categories, demographic question options, storage assets and category averages.

  • Fixed a DataLoader that returned rows out of order relative to the requested keys, a silent correctness bug
  • Storage batch-asset N+1 found via Sentry rather than review

Observability and Reliability

Technology used

GraphQL
Audited every resolver for N+1s and found a class I hadn't expected: DataLoaders that received a batch of ids and then mapped over them calling a getById endpoint per id — the pattern present, the benefit absent.
Node.js
Built genuine batch endpoints behind them for roles, recognition categories, suggestion categories, demographic question options and storage assets, and found a loader returning results out of order relative to its keys — not slow, silently wrong, since every consumer got another record's data.
RPC
Added the batch RPC methods the loaders needed — and learned that a new RPC method must be registered on the service's server factory, not just its method index, or it fails authentication at runtime.
MongoDB
Made the batch endpoints single-query rather than a loop, and batched the category averages behind the survey dashboard.
TypeScript
Typed the loader key and value so returning a mismatched-length array is a compile error, which is what prevents the ordering bug recurring.
2024–2026Moved all survey statistics to MongoDB Atlas SearchRebuilt every survey statistic on the main database's search engine, proving each one matched the old system before switching customers over.Data and search

What I built

Led the migration of every survey statistic off Elasticsearch onto MongoDB Atlas Search behind a feature flag: invites, responses, comments, average and segmented average, eNPS, distributions, favourable score, campaign score, response rate, question-category average, engagement index, keyword frequency, sentiment and the answer list.

  • Built a shadow-comparison harness that ran both engines side by side and turned it into the rollout gate
  • Introduced a data-source interface so consumers were untouched by the swap
  • Keyword frequency solved with an Atlas $searchMeta stringFacet rather than draining documents
  • Legacy answer collections, views and dead endpoints removed once parity was proven

Data Platform and Migrations

Technology used

MongoDB Atlas Search
Reimplemented every survey statistic as Atlas Search queries: invites, responses, comments, average and segmented average, eNPS, distributions, favourable score, campaign score, response rate, question-category average and the answer list. Keyword frequency uses a $searchMeta stringFacet and average score an integer facet, so aggregates compute inside the index.
MongoDB
Designed the index strategy behind it — a lean stored source after finding the invitee demographic segments were bloating it, demographic index hints, factored manager-access clauses, and answer-scope fields (campaign and question category) stamped onto answers so a stat doesn't need a live lookup.
Elasticsearch
Kept the ES path running as the reference implementation, then found genuine pre-existing defects in it while comparing: blank comments being counted, and answers with no sentiment being scored as neutral.
Node.js
Introduced a data-source interface so consumers were untouched by the swap, and built the shadow-comparison harness that runs both engines on live traffic, tags divergences, and became the rollout gate rather than a dashboard.
Zod
Validated the stat request shape once at the seam so both implementations receive identical, parsed input — otherwise a divergence could just be different coercion.
Sentry
Reported shadow divergences as structured events with tags for the stat and whether it was category-scoped, and learned that detached shadow spans land under transaction rather than the span description.
TypeScript
Defined one data-source interface both engines implement, so the swap is a configuration change and a consumer cannot tell which engine answered.
2024–2026Statistical analysis in the product: key driver analysisTurned the data team's manually run R script into a self-service feature that shows which factors most influence employee engagement.AI and data science

What I built

Took the data team's manually-run regression script and made it a platform feature: a Dockerised Node Lambda that executes R via execa behind API Gateway, defined input/output contracts, Mongoose models for drivers, a regression API in the survey service, and a React scatter-plot experience with analyst controls.

  • Ran the analysis against a MongoDB Atlas analytics node to keep load off the primary
  • Regression threshold tied to the organisation's confidentiality limit rather than a magic number
  • Output written to S3 for the analyst team
  • Extended to non-KDA surveys, eNPS drivers, continuous and onboarding/exit surveys, and multi-index question filtering
  • R script vectorised in 2026 for a substantial runtime reduction

Advanced Analysis and Data Science

Technology used

R
Took the data team's key driver analysis R script into production and then kept changing it: allowed the metric score to sit in any column and always return a valid response, raised the driver limit, excluded non-flagged questions, rounded to 1dp to match the analysts' export, and later vectorised it to cut runtime and silence its console noise.
Docker
Built the Lambda's image so R and the script ship together and execa can shell out to Rscript at runtime. Iterated on layer ordering specifically for caching, then split the R runtime install into its own build stage so it stops being rebuilt on every code change.
AWS Lambda
Created the key driver analysis Lambda from scratch — handler, input/output contracts, error handling — and fixed the case where a failure returned a 200 with no body.
API Gateway
Fronted the Lambda with API Gateway and wired the SSM-held API key; later removed the Lambda's own JWT verification so it consumes the caller's authorisation instead of holding its own trust root.
MongoDB
Wrote the aggregation that assembles the regression input, tuned it, added a supporting index on the answers collection, and pointed the whole job at an Atlas **analytics node** so a heavy analytical scan never competes with production traffic.
Mongoose
Modelled the computed drivers for persistence and caching, with a memoisation layer so repeat views don't re-invoke the Lambda.
Terraform
Provisioned the Lambda, its ECR image, API Gateway route, IAM and SSM parameters, raised memory when generation timed out, and later removed the legacy resources after the rename.
React
Built the Key Drivers tab — scatter plot with click-to-scroll, score-influence labelling, analyst controls, question categories in analyst mode, multi-metric and multi-index filtering, and the confidentiality-gated drill-down dialog.
GraphQL
Exposed the regression through the schema and a React hook, so the frontend never talks to the Lambda directly.
S3
Wrote the generated output to S3 for the analyst team to download, including the URL-construction helper.
TypeScript
Defined the Lambda's input and output contracts as types shared by the survey service route and the frontend, so a change to the R script's output shape breaks the build rather than a chart.
2024–2026Statistical significance testing in the productAdded significance testing so customers can tell whether a difference between two groups is real, later rebuilt as a guided step-by-step tool.AI and data science

What I built

Added a T-Test function to the analysis Lambda with an analyst-facing frontend, then in 2026 rebuilt it as a guided wizard on a shared component set and dropped its bespoke JWT verification in favour of passing the user's own authorisation through.

  • Handled surveys where question order differs between comparison groups

Advanced Analysis and Data Science

Technology used

R
Added a t-test R script alongside the key driver analysis script, then fixed it to tolerate comparison groups whose questions arrive in different orders — previously it silently paired the wrong columns.
AWS Lambda
Added a second function to the same package, reusing the R execution harness, and dropped its bespoke JWT verification so the survey service passes the user's authorisation through.
React
Built the analyst-mode results table and attribute-segment selector, then rebuilt the whole thing in 2026 as a guided wizard on a shared guided-experience component set.
Node.js
Added the survey service route with its own memoisation, mirroring the KDA caching so a repeated comparison is free.
Zod
Defined the t-test input contract in the shared survey library so the frontend, the route and the Lambda validate against one schema.
TypeScript
Shared the t-test input and result types between the shared survey library, the route and the wizard, so the guided UI can't request a comparison the Lambda won't accept.
2023–2026Faster, more reliable build and deploy pipelineOngoing work to speed up builds and deployments, including caching, a staging environment and right-sized build machines.Developer experience

What I built

Ongoing work on build and deploy throughput: larger Buildkite agents where they paid for themselves, a staging environment, PR title conventions, dependency install caching for Python and R, splitting the R runtime into its own Docker stage, and fixing provisioned-Lambda alias publishing.

  • Python and R dependency caching cut the report-generation build substantially
  • Used the Buildkite MCP server to profile slow builds rather than guessing

Developer Experience and AI Engineering

Technology used

Buildkite
Maintained the per-package deploy pipelines, moved to larger agents where they paid for themselves (2xl then 4xl for the survey service), added more available instance types after capacity failures, and fixed publish not repointing a provisioned Lambda alias at the new version.
Docker
Cut build time by restructuring images — caching the Python and R dependency installs in the report generator, splitting the R runtime into its own stage, and improving KDA layer ordering.
GitHub Actions
Owned the PR-conventions workflow (including widening the title regex for apostrophes and em dashes), the bundle-size workflow, and the pnpm workflow.
pnpm
Kept the workspace healthy through upgrades — to 10.20 — and fixed peer-dependency and lockfile breakage, including preventing multiple GraphQL versions being installed.
Node.js
Added a staging environment to CI, and used the Buildkite MCP server to profile slow builds rather than guessing from YAML.
TypeScript
Kept the pipeline generation and package-script conventions typed and validated, so a new package gets a correct pipeline rather than a copy-paste with a stale package name.
2023–2026End-to-end test suite reliabilityKept the automated browser tests fast and trustworthy, running them in 10 parallel shards and fixing the causes of flaky failures.Developer experience

What I built

Owned the health of the end-to-end suite: sharded to 10 parallel shards, diagnosed ECS CPU spikes and MongoDB timeouts under load, made sign-in survive rate limits, fixed viewport configuration, and repaired or realigned dozens of specs as the product changed.

  • Built a local login helper that receives credentials as 1Password-injected environment variables so no secret ever reaches an agent's context
  • Traced a case where Currents reported 100% pass while Buildkite failed the pipeline
  • Stopped signing in on every scenario, which was both slow and rate-limit-prone

Quality Engineering and Automation

Technology used

Playwright
Own the end-to-end suite across 51 PRs: page objects and Gherkin feature specs. Sharded to 10 parallel shards, fixed a viewport that wasn't being applied, stopped signing in on every scenario (slow and rate-limit-prone), and realigned the heatmaps and v2 Questions specs after each redesign.
1Password
Built a local sign-in script plus a .env of op:// references so credentials reach the browser as op run-injected environment variables in a child process — the secret never enters an agent's context or a tool argument.
Buildkite
Diagnosed a run where Currents reported 100% pass while Buildkite failed the pipeline, and traced shard scheduling gaps where shards sat idle for minutes.
ECS
Root-caused CPU spikes and MongoDB connection timeouts that only appeared when shard count rose against single-task services, and sized the development environment to match the concurrency.
TypeScript
Kept the page-object layer typed and fixed real breakages — an ESM export that didn't exist, and a Tiptap toolbar dropdown that opened off-screen and so was unclickable.
2023–2026Standard realistic test data for every engineerA clean, realistic dataset any engineer can restore locally in one step, so features are tested against real-shaped data.Developer experience

What I built

Introduced a standardised 'gold' dataset restorable to local and development environments using mongorestore, Elasticsearch snapshots and Atlas Search index export/recreate — giving every engineer a clean, realistic dataset to test against.

  • Extended to export datasets as well as import them, and to wait for search indexes to be created
  • Fixed LocalStack S3 path-style issues and /tmp exhaustion from un-cleaned dataset clones
  • Removed dataset restore from the production pipeline where it had no business running

Developer Experience and AI Engineering

Technology used

MongoDB
Built the restore path on mongorestore, and added export as well as import so a dataset can be captured from an environment rather than only pushed to one.
MongoDB Atlas Search
Added search-index support to the dataset tooling — exporting index definitions and recreating them on restore, then waiting for them to build, because a restored dataset without its indexes silently returns nothing.
Elasticsearch
Used ES snapshot/restore for the search side while it still existed, and raised local ES memory in docker-compose so the import stopped being OOM-killed.
LocalStack
Restored S3 assets into LocalStack and snapshotted it so uploads survive a restart; fixed path-style addressing (forcePathStyle) that made the S3 client fail locally only.
Docker
Owned the local service composition in docker-compose.yml across MongoDB, Elasticsearch and Redis version bumps.
Node.js
Wrote the dataset tooling, and fixed dataset clones exhausting Lambda /tmp by reusing and cleaning them up. Removed the dataset restore from the production pipeline, where it had no business running.
TypeScript
Typed the dataset manifest so an import knows which collections, indexes and S3 assets it should have restored, and can fail loudly when one is missing.
2023–2026HR system integrationsBuilt the integration that keeps customers' employee records in sync with their HR system, using a third-party connector platform for breadth.APIs and integrations

What I built

Designed and built Hive's HRIS integration end to end: a typed TypeScript SDK over Kombo's REST API, Kombo Connect embedded onboarding, webhook-triggered Lambdas behind API Gateway, SNS/SQS fan-out for high user volumes, per-user operation processing with idempotency, and a React + GraphQL surface for configuration, field mapping and sync monitoring.

  • Custom JSONata support so customers could transform incoming HRIS fields themselves
  • Handled future termination dates, contract users, group sync, and terminated/deleted users absent from Hive
  • Sync history capped at 240 runs (30 days) to bound storage
  • Admin-only integration lock added in 2026

HRIS and Integrations

Technology used

JSONata
Added custom JSONata expression support so a customer can transform an incoming HRIS field themselves — a date format, a concatenation — instead of queueing behind our roadmap for every variation.
AWS Lambda
Built the webhook receiver, then split it into two functions once manual sync needed its own validation path, and later migrated the trigger from Kombo's sync-finished event to its data-changed event — where the URL has to be registered in Kombo *before* flipping the flag or syncs stop silently.
API Gateway
Fronted the webhook with API Gateway and verified Kombo's signature header, having first checked the wrong header.
SNS/SQS
Fanned per-user operations out through SNS/SQS so a sync of thousands of employees doesn't run in one request, and marked individual operations processed so a partial failure resumes rather than restarting.
MongoDB
Modelled integrations, field mappings and sync history — capping stored syncs at 240 (30 days) to bound growth — and handled future-dated terminations, contract users with fixed end dates, and users terminated in the HRIS who never existed in Hive.
React
Built the configuration, field-mapping and sync-monitoring UI, rebuilt the screens once, added an admin-only lock control, and made the sync UI performant when a sync has thousands of rows.
GraphQL
Exposed integration state and mappings, and fixed queries not refetching after mutations so the UI showed stale mapping state.
Node.js
Wrote the typed SDK over Kombo's REST API in a shared integration library so their API shape changes are absorbed in one place; extended it as we needed more methods, and added location, manager, legal entity and home address support.
TypeScript
Defined the full Kombo type surface up front, which is what made the mapping UI able to offer real field choices.
2023–2026Heatmap reporting across teams and surveysBuilt and extended the heatmap view that compares scores across groups and surveys side by side, with confidentiality controls throughout.Product features

What I built

Built the heatmaps tab and then extended it: a combined/side-by-side mode for comparing surveys, a 'Show Confidential Columns' filter, in-region scrolling, bulk segment CSV download, and manager access throughout.

  • Fixed grey blocks in PNG export by swapping html2canvas for html-to-image
  • Columns with zero invites hidden and excluded from the column budget; same treatment then built for sub-confidentiality columns

Survey Analytics and Reporting

Technology used

React
Built the heatmaps tab, then the combined side-by-side mode for comparing surveys, in-region scrolling so the grid scrolls inside its own pane, a "Show Confidential Columns" filter, and bulk segment CSV download.
Node.js
Hid columns with zero invites and excluded them from the column budget, then built the equivalent for columns below the confidentiality limit — the same rule applied to a different predicate.
GraphQL
Added the combined-heatmap queries and fixed only the selected filter tab's facet list being rendered, which had been fetching all of them.
MongoDB
Backed the heatmap aggregation and diagnosed a v1/v2 data discrepancy with a dedicated comparison script.
TypeScript
Replaced html2canvas with html-to-image after customers reported grey blocks in exported PNGs — a rendering difference I couldn't reproduce until I read what each library does with CSS backgrounds.
2023–2026Database upgrades and index governanceOwned three major MongoDB version upgrades and made database indexes part of the code, rather than settings changed by hand.Data and search

What I built

Owned MongoDB across three major versions (5 → 7 → 8) with the matching Node driver and Mongoose upgrades, worked with MongoDB solution architects on performance recommendations, introduced analytics nodes, and established that indexes are declared on the model schema and synced by migration rather than hand-created.

  • Attended MongoDB summits and fed vendor recommendations back into the schema design
  • Repeated index work on the invitee and answer collections, including compound and multikey indexes
  • Found and fixed a production timeout caused by hinting an unbounded multikey leading field

Data Platform and Migrations

Technology used

MongoDB
Owned three major upgrades (5, 7, 8) with the matching driver versions, each gated on a Node upgrade first — MongoDB 5 required Node 14.20.1, which is why that PR exists.
MongoDB Atlas
Worked with MongoDB solution architects on performance recommendations, introduced analytics nodes so analytical workloads don't compete with production, and verified index state against Atlas directly — production carried indexes no migration had created.
Mongoose
Established that indexes are declared on the model schema and synced by migration (syncIndexes), never hand-created — and declared the invitee indexes on the model with a single sync migration to prove the pattern.
Node.js
Fixed intermittent connection failures and pool exhaustion on service start-up, and registered models at boot so index creation is deterministic.
TypeScript
Made the model schema generic over its document type so a driver or Mongoose major version change surfaces at compile time across every model at once.
2023–2026Customer data anonymisationBuilt and extended the tools that anonymise people's data when required, with audit logging and two-person approval.Security and access

What I built

Built and repeatedly extended anonymisation: fixed deleted users not being anonymised, wrote the organisation anonymisation script and endpoint, exposed it as a staff-only danger zone with audit logging, and put it behind a two-person Slack command.

  • Destructive by nature, so every route to it is audited and the Slack path requires a second approver

Security and Privacy

Technology used

Node.js
Fixed deleted users not being anonymised — the delete path skipped them, so the data stayed — then wrote the organisation-level anonymisation and its endpoint.
MongoDB
Implemented the anonymisation across the tenant's collections, run per organisation.
Slack API
Put it behind a Slack command with a two-person rule, because a destructive irreversible action should need a second approver rather than one person's confidence.
AWS Lambda
Ran it as a Slack-triggered Lambda with the processor invoked asynchronously so Slack's acknowledgement deadline is met.
TypeScript
Exposed it as a staff-only danger zone with an audit log entry per run, so there's a record of who anonymised what and when.
2022–2026Cross-customer benchmarkingLets customers compare their engagement scores with similar organisations, including performance fixes so large comparisons complete.Product features

What I built

Built and maintained cross-customer benchmarking: engagement-index and eNPS benchmark data population, the benchmarking modal with role and flag gating, aggregation fixes, timeout and cursor-timeout remediation, parallelised aggregations, and direct result writes replacing the view layer.

  • Reviewed the cross-tenant anonymisation RFC for the benchmarking rollup
  • Gated the modal per benchmark type once multiple benchmark kinds existed

Survey Analytics and Reporting

Technology used

AWS Lambda
Own the benchmarking function: fixed generation timeouts and cursor timeouts, raised memory when the aggregation legitimately needed it, and parallelised the aggregations that fall in the same time bracket.
MongoDB
Populated engagement-index and eNPS benchmark data, filtered the eNPS aggregation by answer type after it was including the wrong questions, and switched to writing results directly instead of depending on database views.
Atlas Data Federation
Used Data Federation so benchmarks aggregate across tenant databases in place, without copying customer data into a shared store — which is what makes cross-customer benchmarking defensible at all.
React
Built the benchmarking modal with role and feature-flag gating, and later gated it per benchmark type once several kinds existed; fixed it erroring for users without the role instead of hiding.
Node.js
Reviewed the cross-tenant anonymisation RFC for the benchmarking rollup, since the aggregate is only publishable if no cohort is small enough to identify.
TypeScript
Typed benchmark cohorts and metrics so a benchmark can't be computed against a mismatched metric.
2022–2026More control over live surveysAdded pausing, copying and editing of surveys after they've been sent, which customers had been asking for.Product features

What I built

Progressively opened up survey lifecycle control: pause a live survey, copy a survey (with unique component ids), copy a draft survey, staff edit mode, editing closed surveys, editing survey and question categories after send, and 'greater control of live surveys'.

  • Prevented survey submissions after the close date as the counterpart safety fix

Survey Builder and Planner

Technology used

Node.js
Opened up lifecycle control incrementally: pause a live survey, copy a survey, copy a draft, staff edit mode, editing closed surveys, editing categories after send, and reopening live surveys — each needing its own validation rules about what is safe to change once responses exist.
MongoDB
Fixed copy-a-survey not regenerating component ids, so the copy shared identifiers with the original and answers could attach to the wrong survey.
React
Built the corresponding builder and dashboard controls, including the users-removed dialog for approved surveys.
GraphQL
Added the mutations and kept them permission-gated, since several of these are staff-only.
TypeScript
Modelled survey status transitions explicitly, which is how the counterpart fix — rejecting submissions after the close date — was made safe.
2021–2026Production incident diagnosisRegular front-line diagnosis of live incidents, from performance spikes after releases to database and load-balancer failures.Platform and reliability

What I built

Regular front-line diagnosis of production incidents: CPU spikes and 503s correlated to a master release, DynamoDB write throttling, MongoDB connection-pool exhaustion and intermittent connect failures, ALB target-group health checks pointing at the wrong path, deployment failures across every service, and a duplicate-user incident where hard deletes without events left dangling mirrors and magic links.

  • Worked from Atlas metrics and Sentry rather than building staging replays
  • Established that Atlas Query Insights truncates compound arrays at 64 entries, which had been misleading the team's query analysis

Observability and Reliability

Technology used

Sentry
Front-line diagnosis from the logs and traces we'd built: correlated CPU spikes and 503s to a master release that had started eight minutes earlier, and traced a duplicate-user incident reported as 'SSO is broken' to records hard-deleted without emitting events, leaving dangling mirrors, magic links and survey tokens.
MongoDB Atlas
Worked from Atlas metrics rather than building replay environments — including establishing that Query Insights truncates compound arrays at 64 entries and reports Docs Examined: 0 on $search pipelines, so the samples several people were reasoning from were fictional.
DynamoDB
Investigated a write-throttling incident with the CLI and CloudWatch and sized autoscaling to the real spike instead of the 13,000 fixed WCU recommended.
ECS
Diagnosed connection-pool exhaustion under automation load, and an ALB target group failing health checks because they pointed at / rather than the health endpoint.
Terraform
Fixed autoscaling schedules that weren't in UTC and so fired at the wrong hour, and increased deregistration delay to stop deploy-time 503s.
2021–2026Caching for the busiest parts of the platformAdded caching with correct invalidation to the highest-traffic requests, reducing load on the database and services.Platform and reliability

What I built

Introduced stable cache-key generators and applied caching across the highest-traffic paths: attributes and segments, roles, the global user verifier, external API user creation, organisation averages, response filters, and asset lookups — with matching invalidation on write.

  • Chased down a class of bug where segment/attribute writes did not bust the cache
  • Cache key generation standardised behind one stable key generator

Observability and Reliability

Technology used

Redis
Introduced stable cache-key generators so two callers building a key from the same inputs get the same key — before that, key construction was ad hoc and cache hits were accidental.
Node.js
Applied caching to the hot paths: attributes and segments, roles, the global user verifier, external-API user creation, organisation averages, response filters and asset lookups. Then chased the harder half — invalidation — after finding segment and attribute writes weren't busting the cache, so a new segment stayed invisible.
MongoDB
Chose what to cache from real query cost, and added a cache-library no-op on an empty key list after a delete-with-no-keys threw.
TypeScript
Refactored the cache library so a cached function declares its key inputs and TTL in one typed place.
2021–2026Cloud infrastructure and cost optimisationOne of two engineers trusted to change production infrastructure. Cost-optimised logging and autoscaling, and switched development environments off overnight.Platform and reliability

What I built

One of two engineers able to apply Terraform to production. Delivered cost-optimised access logging for CloudFront, ALBs and HTTP API Gateway; DynamoDB autoscaling; same-account Lambda ECR pull grants on every repo; Sentry resources; nightly autoscaling deferral for development environments; enhanced container insights; and a long tail of scaling, alarm and timing corrections.

  • Investigated a DynamoDB write-throttling incident with the AWS CLI and sized autoscaling properly instead of accepting a 13k-WCU recommendation
  • Found autoscaling schedules were not in UTC and were firing at the wrong time
  • Consolidated crons and increased deregistration delay to stop deploy-time 503s

Cloud Infrastructure and Cost

Technology used

Terraform
One of two engineers with production apply rights; 337 distinct .tf files touched. Built cost-optimised access logging for CloudFront, ALBs and HTTP API Gateway; added DynamoDB autoscaling; granted same-account Lambda ECR image pull on every repo; and declared the Sentry resources and alerting.
ECS
Sized CPU and memory per service (organisation and auth services, GraphQL to 2 GB), enabled enhanced container insights, and increased the deregistration delay after correlating deploy-time 503s to targets being pulled before draining.
CloudFront
Configured access logging with the cost-optimised storage path rather than the default, which was the expensive part of the request.
DynamoDB
Investigated a write-throttling incident with the AWS CLI and CloudWatch and configured autoscaling shaped to the real spike, instead of the 13,000 fixed WCU the tooling recommended.
AWS Lambda
Provisioned the Lambda estate — function URLs, provisioned concurrency aliases, SSM parameter namespacing — and fixed a pipeline that wasn't repointing the provisioned alias at the new version on publish.
Buildkite
Maintained the per-package deploy pipelines and the Terraform plan/apply steps, including targeting a single resource when a full apply was too risky.
TypeScript
Kept the Lambda and service configuration typed where it crosses into application code — SSM parameter names and env contracts — so an infrastructure rename surfaces as a build failure.
2020–2026Feature flag platform and early-access programmeImproved how features are switched on per customer, and added an in-app early-access banner so customers can opt in to new versions.Developer experience

What I built

Refactored Hive's feature flag layer and repeatedly extended it: SDK upgrades, audience automation on organisation creation, audience condition rule priorities, legacy flag cleanup, and per-user opt-in flags surfaced through an in-app Early Access banner.

  • Built a Claude skill that creates a flag in the shared flags library and Optimizely in one step
  • Per-user opt-in let customers self-select into the new Question Dashboard

Developer Experience and AI Engineering

Technology used

Optimizely
Own the flag layer: SDK upgrades, creating the audience automatically on organisation creation, and fixing audience condition rule priorities that were being applied in the wrong order so the wrong variation served.
TypeScript
Refactored the feature-flag library so flags are a typed enum consumed by both backend and frontend — adding a flag means adding it to the enum and building the library, which is exactly why I later wrote a skill for it.
React
Built per-user opt-in on top of the org-level flag: an in-app Early Access banner letting a user opt themselves into the new Question Dashboard, rather than a big-bang cutover.
Node.js
Used flag values as configuration, not just on/off — per-organisation AI model selection is a flag value.
2019–2026Data integrity and operational scriptsWrote much of a toolkit of around 60 scripts that check data consistency, find duplicates and produce adoption reports.Developer experience

What I built

Authored a large share of a ~60-script operational toolkit: MongoDB/Elasticsearch integrity comparisons per collection, duplicate email and duplicate invitee detection, permission matrices, potentially-vulnerable attribute detection, feature adoption reports, response-rate and metric reports, organisation anonymisation, authentication record sync, and a subject access request generator.

  • Integrity-check scripts were the evidence base for deleting Elasticsearch indices safely
  • Subject access request script produces a complete per-user data CSV for GDPR requests
  • Standardised on shared database and per-tenant iteration helpers so scripts are safe across every tenant

Quality Engineering and Automation

Technology used

MongoDB
Wrote the integrity-comparison scripts that compared MongoDB and Elasticsearch document counts per collection per tenant — those were the evidence base for deleting search indices safely, not a nice-to-have. Plus duplicate-email and duplicate-invitee detection, answers missing a creation date, and a regex hunt for capital letters in email addresses.
Node.js
Standardised on shared database and per-tenant iteration helpers so a script is safe across every tenant database by construction, rather than each script re-implementing iteration and connection handling. Added oxlint to the repo.
Elasticsearch
Built the messenger deep audit comparing messages, conversations, participants and relations between ES and Mongo before that service's cutover.
TypeScript
Wrote the subject-access-request generator producing a complete per-user data CSV for GDPR requests, the permission matrix, potentially-vulnerable-attribute detection, feature-adoption reports and the top-managers-by-authorised-segments analysis.
2025Front-end data caching fixesUpgraded the front-end data client and fixed a long tail of cases where screens showed stale data after changes.Front end and accessibility

What I built

Upgraded to the latest Apollo Client and then worked through a long tail of cache-update failures — user creation, load-more users, messenger, recognition categories, my-hive dashboard — plus fragment adoption and a fix for the case where Apollo was caching nothing at all.

  • Added an ErrorBoundary inside ApolloProvider and a switch to surface Apollo errors during development
  • Switched the organisation query to GraphQL fragments to keep read and write shapes identical

Frontend Platform and Design System

Technology used

Apollo Client
Upgraded to the latest client and then worked through a long tail of cache-update failures — user creation, load-more users, messenger, recognition categories, my-hive dashboard — including a case where Apollo was caching nothing at all.
GraphQL
Switched the organisation query to fragments so read and write shapes are identical by construction, which is the actual fix for most manual cache-update bugs, and used fragments for the user response queries for the same reason.
React
Added an ErrorBoundary inside ApolloProvider and a switch to surface Apollo errors during development, plus handling for failed chunk fetches after a deploy.
TypeScript
Fixed the underlying cause of several 'destructuring from null' crashes by making nullable GraphQL fields nullable in the types instead of assumed present.
2025Fine-grained permissions modelled on AWS IAMReplaced fixed user roles with flexible groups and policies, so one rule can express "managers see their own team" across a whole organisation.Security and access

What I built

Architected and implemented a fine-grained authorisation system modelled on AWS IAM — Groups, Policies and Statements evaluated through CASL — replacing coarse role checks. Delivered the organisation setting, backend create/update endpoints, resource schemas, and the full frontend for creating and renaming groups, adding and removing users, filtering the users grid by group, and authoring policy statements.

  • Statements can reference the principal user's own attribute value, so one policy expresses 'their own team'
  • A managed-by subject selectable in a statement, backed by the line-manager graph
  • Legacy routes and permissions removed once the new model was live

Users, Roles and Authorisation

Technology used

CASL
Evaluated the Groups/Policies/Statements model through CASL so one rule set serves server-side enforcement and UI reasoning, rather than duplicating the logic per surface.
MongoDB
Modelled groups, policies and statements, and implemented schemas for every protected resource so a statement names a real resource type.
Node.js
Built create and update endpoints for groups and their statements, added a name to a policy, and removed the legacy routes and permissions once the new model was live. Also fixed the authorisation middleware not evaluating rules correctly.
React
Built the frontend: create and rename groups, add and remove users, filter the users grid by group, author policy statements, and select the principal user's own attribute or their line manager as the statement subject.
GraphQL
Exposed groups, policies and statements with their mutations, permission-gated — and deliberately routed the frontend through the GraphQL layer so the authorisation model is enforced on the same path it describes.
Zod
Defined the statement schema so an unparseable policy can't be persisted — the risk being a malformed statement evaluating permissively.
TypeScript
Modelled the principal-attribute reference as a type so 'their own team' is one policy for every manager rather than one per manager.
2025Confidentiality control for combining report filtersAn organisation setting that stops users combining two allowed filters to narrow results down to one person.Security and access

What I built

Added an organisation confidentiality setting that governs whether facets can be combined, and enforced it in the UI on both the survey dashboard and the question dashboard — closing a differencing attack where two permitted filters could be intersected to isolate an individual.

  • Frontend enforcement shipped first as phase 1, with backend enforcement tracked as follow-up

Security and Privacy

Technology used

Node.js
Added an organisation confidentiality setting — the control that stops a user intersecting two permitted filters until one person is left, which is a differencing attack, not a UI preference.
React
Enforced it in the UI on both the survey dashboard (disable combining facets) and the question dashboard (disable breakdown by segment) as phase 1.
MongoDB
Stored the setting on the organisation with a safe default of disabled, so an existing customer doesn't silently gain the ability to combine facets on upgrade.
GraphQL
Exposed the setting through the schema so the survey dashboard and question dashboard read one source of truth, rather than each inferring whether combining is allowed.
TypeScript
Modelled the setting so the enforcement points reference one flag rather than each deciding — with backend enforcement tracked as the explicit follow-up, since frontend-only is not a security boundary.
2025Secure sign-in overhaulReplaced long-lived browser tokens with secure, revocable sessions and passwordless magic links.Security and access

What I built

Moved platform authentication off JWTs in local storage onto secure session cookies: a sessions collection holding refresh tokens, cookie-based sessions, token refresh, logout-session handling, a refactored LogoutDetector, magic-link redirect sessions, and a change to the i18n headers Lambda@Edge function to read the session cookie.

  • Generates a magic link when a user arrives with an expired JWT rather than dumping them at a login screen
  • Removed password-based logins in favour of magic-link authentication

Authentication and Sessions

Technology used

MongoDB
Added a sessions collection holding refresh tokens, which is what makes revocation possible — the previous JWT-in-local-storage model could only wait for expiry.
Node.js
Implemented cookie sessions, token refresh and logout-session, and set up a session on magic-link redirect so the transition didn't dump users at a login screen.
Lambda@Edge
Modified the edge function that sets language headers to read the session cookie at the CDN edge — a constrained runtime with a hard 50 MB bundle limit, which later needed tsdown to stay under it.
React
Refactored the LogoutDetector for cookie sessions, fixed sign-in redirects and the refresh of sign-in state, and unset an expired cookie on successful redirect.
AWS Lambda
Made the magic-link function issue a link when a user arrives with an expired JWT, which is how we removed password login rather than migrating it.
TypeScript
Typed the session record and its refresh state so an expired session is a distinct case, not a missing field.
2025Customer-configurable engagement metricsTurned fixed engagement metrics into ones customers can define themselves, from storage through to the survey builder.Product features

What I built

Made Hive's fixed indexes customer-configurable: list/update REST endpoints, GraphQL layer, migration of global metrics into the database, component source stored on answers, a Metrics management page, and full create/edit/delete in the survey builder.

  • Metric labels threaded through the dashboard, questions tab, overview and key drivers
  • Organisation-level setting to control exposure

Survey Analytics and Reporting

Technology used

Node.js
Made Hive's fixed indexes customer-configurable: list and update endpoints, migration of the global metrics into the database, and storing the component source on answers so a metric can be recomputed from history.
MongoDB
Moved global metrics from code into per-tenant data and added the missing engagement-index metric questions to the Question Bank, with migration timeouts and connection cleanup handled.
GraphQL
Added the metric queries and mutations, and threaded metric labels through the dashboard, questions tab, overview and key drivers — including fixing the label not decoding.
React
Built the Metrics management page and full create/edit/delete in the survey planner, with a coming-soon state while it was flag-gated.
Zod
Defined the metric schema once so the REST route, GraphQL layer and builder validate identically.
TypeScript
Refactored the survey-questions lookup to return the question's source, which is what let a custom metric reference library and custom questions together.
2025Fast manager-scoped reportingStored each person's line manager alongside their data, so "show me my team" reports can use an index instead of walking the org chart on every query.Security and access

What I built

Introduced a parent reference on each user and denormalised the line manager onto anonymous feedback, peer recognition and survey models, computed by batch, so manager-scoped reporting could be answered by an index rather than a graph traversal at query time.

  • Deliberately denormalised rather than using $graphLookup at read time

Users, Roles and Authorisation

Technology used

MongoDB
Added a parent reference to the user and denormalised the line manager onto anonymous feedback, peer recognition and survey documents, deliberately instead of $graphLookup at read time — a graph traversal per query wouldn't have held up under manager-scoped reporting.
AWS Batch
Computed the line-manager field in a batch job, and switched it to database queries rather than in-process traversal once the denormalisation existed.
Node.js
Kept the denormalised field in step on user update, since a reporting-line change has to propagate.
TypeScript
Typed the manager reference so a policy statement can reference the line manager safely.
2025Node 24, strict TypeScript and much faster buildsUpgraded the platform runtime and tightened type checking across ten services, which allowed a build change that cut internal build times from over 30 minutes to under 10.Platform and reliability

What I built

Upgraded the platform to Node 24.7 and enabled TypeScript strict mode service by service — storage, auth, organisation, messenger, suggestion, recognition, integration, user and survey — then switched services to relative imports so Node's native type stripping could consume TypeScript directly, and moved the Lambdas to Node 24.

  • Removing the compile step between internal libraries cut monorepo build times from 30+ minutes to under 10
  • Ten services taken to strict mode in a fortnight, one PR each

Platform Modernisation and Upgrades

Technology used

Node.js
Upgraded to Node 24.7 and adopted native type stripping so services consume TypeScript directly, removing the compile step between internal libraries — internal builds went from 30+ minutes to under 10.
TypeScript
Enabled strict mode service by service — storage, auth, organisation, messenger, suggestion, recognition, integration, user and survey, one PR each — and switched services to relative imports, since path aliases don't survive type stripping. Also removed TypeScript enums in favour of object equivalents for the same reason.
Docker
Moved the base Node image and every Lambda image to Node 24, having done the same for Node 14, 16 and 20 before it.
pnpm
Handled the workspace and peer-dependency fallout, and upgraded pnpm to 10.20 as part of keeping the toolchain able to do this.
2024–2025New survey products and templatesAdded a 360-degree feedback survey type and ready-made engagement survey templates.Product features

What I built

Added new survey products: an MVP 360 survey type, Engagement Pulse and Baseline templated surveys, and onboarding/exit survey metrics and campaign-dashboard indexes.

Survey Builder and Planner

Technology used

Node.js
Added the 360 survey type as an MVP, then Engagement Pulse and Baseline templated surveys, plus onboarding and exit survey metrics and their campaign-dashboard indexes.
MongoDB
Modelled a template as a survey shape that can be instantiated, and added the campaign-dashboard indexes for the new index types.
React
Surfaced the new types in the builder and the campaign dashboard, and fixed the exit index not displaying for exit surveys.
GraphQL
Added the queries for the new survey types and their metrics, and fixed the Exit Index not resolving for exit surveys because the metric lookup keyed on a library id the templated question didn't carry.
TypeScript
Migrated the survey type IDs from a TypeScript enum to its object equivalent as part of the enum-removal work, so it survives type stripping.
2024Account settings redesignRebuilt the account settings area and the management of recognition and feedback categories.Security and access

What I built

Built the new Edit Account Settings page (156 files) and the create/update/retire lifecycle for suggestion and recognition categories, plus improved image management for logos and category images.

  • Automatically creates the Hive Support user and default categories on organisation creation

Users, Roles and Authorisation

Technology used

React
Built the new Edit Account Settings page — a 156-file change — and the create/update/retire lifecycle for suggestion and recognition categories, plus category and logo image management.
Node.js
Added the retire semantics (rather than delete) so historical feedback keeps its category, and made organisation creation seed the Hive Support user and default categories, which had been manual.
GraphQL
Added the settings mutations, gated so only staffs can change the internal-only options.
MongoDB
Modelled the category lifecycle and fixed broken peer recognition and suggestion categories created at organisation setup.
TypeScript
Modelled a retired category as a distinct state so it stops appearing in pickers but still resolves for reporting.
2023–2024Live recognition display for shared screensRebuilt the office-screen board that shows new recognitions as they happen, with secure, expiring share links.Product features

What I built

Rebuilt the shared-screen recognition status board: polling for live updates, confetti and sound on new recognitions, a UI refresh, expiring share tokens, and a deploy pipeline change to ship audio assets.

  • Added mp3 support to the app deployment pipeline to make the sound work

Peer recognition

Technology used

React
Rebuilt the shared-screen recognition board: polling for live updates, confetti and sound on a new recognition, and a UI refresh. Had to make the confetti handling stable, since it was re-firing on every poll.
Node.js
Added expiring share tokens so a board URL on a wall screen isn't a permanent unauthenticated window into recognition data, and trimmed the board user's permissions to the minimum.
GraphQL
Kept the polling query's payload deliberately small — only the fields the board renders — because it polls continuously on a wall screen and a fat query would have been a standing load.
TypeScript
Typed the board's token payload and expiry so an expired token is a distinct state, not a failed query.
2023–2024Survey reporting rebuild (Survey Dashboard 2.0)Rebuilt survey reporting with overview, per-question, heatmap and benchmarking views, released in stages alongside the old version.Product features

What I built

Built the replacement survey reporting experience: overview tab with metric averages and comparison cells, Questions tab with per-question graphs, a faceted Filters sidebar, a Heatmaps tab, the Benchmarking modal, survey report generation, organisation-average columns, manager access throughout, print styling and full test-id coverage.

  • New GraphQL query and hook to fetch all facet segments for a survey
  • Organisation average statistics cached to keep the overview tab fast
  • Redirected the legacy dashboard and removed its code once adoption was complete

Survey Analytics and Reporting

Technology used

React
Built the replacement reporting experience: overview with metric averages and comparison cells, a Questions tab with per-question graphs, the faceted Filters sidebar, the Heatmaps tab, the benchmarking modal and report generation. Added print styling and full test-ID coverage, then redirected and deleted the legacy dashboard once adoption justified it.
GraphQL
Added the query returning all facet segments for a survey plus the frontend hook, so the sidebar builds itself from data rather than a hardcoded list.
Recharts
Built the per-question result charts and the overview visualisations, with the chart type selected per question type rather than one generic chart forced to represent scale, eNPS and option answers.
MongoDB
Added the supporting invitee indexes — several rounds, including a compound index for invites and removing superseded ones — and cached organisation-average statistics because the overview recomputed them per view.
Elasticsearch
The stats were still ES-backed at this point; this is the dashboard whose statistics I later migrated to Atlas Search.
Node.js
Implemented manager access through the filters and heatmaps so a manager's view is scoped server-side, not filtered in the browser.
TypeScript
Introduced a top-level loading context and component so the tabs share one loading contract instead of each inventing its own.
2020–2024Two-factor authenticationBuilt two-factor sign-in from scratch using Twilio, then improved its reliability over several years.Security and access

What I built

Implemented two-factor authentication from scratch on Twilio, fixed delivery failures and manager profile-edit interactions with 2FA, stopped codes being logged, and later enhanced the Twilio integration.

Authentication and Sessions

Technology used

Twilio
Implemented two-factor authentication from scratch on Twilio, then fixed messages not arriving, and later enhanced the integration. Also stopped TFA codes being written to logs — a code in a log is a code in a log aggregator.
Node.js
Built the enrolment, challenge and verification flow, and fixed managers being unable to edit their profile once 2FA was enabled.
React
Built the enrolment and challenge screens, and fixed the interaction where enabling 2FA locked managers out of editing their own profile — the challenge was being required on a route that couldn't present it.
TypeScript
Modelled the challenge state so an unverified session can't be treated as verified.
2023Protection against malicious content in user inputSanitised all user-generated content at every entry point, which made it safe to allow rich text in feedback and recognitions.Security and access

What I built

Introduced a sanitisation library, exposed it as a shared Zod schema type, and applied it at every user-generated-content entry point — Messenger messages, recognitions, suggestions and CSV exports — then enabled rich text input on suggestions and recognitions.

  • Sanitising inside the Zod schema meant validation and sanitisation could not drift apart
  • Also handled escaped HTML in the translation lambda

Security and Privacy

Technology used

Zod
Exposed sanitisation as a shared Zod schema type, so sanitising happens inside validation and the two cannot drift apart — a validated string is a sanitised string by construction.
Node.js
Introduced the sanitisation library and applied it at every user-generated-content entry point: Messenger messages, recognition creation, suggestion creation and CSV export. Also handled already-escaped HTML in the translation Lambda, which was double-escaping.
TipTap
Enabled rich text on suggestions and recognitions on TipTap, which is what made sanitisation necessary rather than optional.
React
Wired the rich-text editor in and later masked it out of Sentry replays, since its contents are exactly the confidential free text we must not record.
TypeScript
Typed the sanitised-string brand so raw user input can't be passed where sanitised HTML is expected.
2023Shared database library and major upgradeCreated one shared database access library, moved the whole codebase onto it (618 files), then upgraded it to Mongoose 7 (542 files).Data and search

What I built

Created a shared Mongoose library (connection pooling, soft delete, multitenant helpers), ported the external Mongoose packages into it, and migrated the entire codebase onto it — 618 files — then upgraded Mongoose to 7.x across 542 files.

  • Two of the largest single changes in the repository's history
  • Required Node 14.20.1 then Node 16 upgrades as prerequisites

Data Platform and Migrations

Technology used

Mongoose
Created a shared Mongoose library with connection pooling, a soft-delete schema pattern and multitenant helpers, then upgraded Mongoose to 7.x across 542 files — including removing a nested subdocument that broke and filtering deleted docs out of countDocuments.
MongoDB
Migrated the entire codebase onto it — 618 files, the largest single change in the repository — and drove the prerequisite MongoDB and driver upgrades.
Node.js
Ported the previously external Mongoose packages into the monorepo, and fixed answer models inheriting toJSON from their parent document, which was leaking fields into API responses.
TypeScript
Made the schema generic (Model<T extends Base>) so a model declares its document type once and consumers get it everywhere.
2023Consolidated shared code into the monorepoBrought internal packages that were published separately into the main codebase, removing version drift between services.Platform and reliability

What I built

Pulled a scattered set of externally published internal packages into the monorepo as first-class libraries: shared utilities, a new HTTP client and a refactored cache library.

  • Reduced cross-repo publish/consume cycles that were slowing every change

Platform Modernisation and Upgrades

Technology used

pnpm
Pulled scattered externally published internal packages into the workspace as first-class libraries (shared utilities, a new HTTP client and a refactored cache library), removing publish-then-consume from the change loop.
TypeScript
Re-exported the merged APIs so call sites changed their import path only, not their usage — that's what made a repo-wide migration tractable.
Node.js
Created a single shared HTTP client with consistent timeouts and error shapes, replacing per-service axios configuration.
2022–2023Multi-tenant search libraryA search library that scopes every query to the right customer automatically, removing a class of data-isolation mistakes.Data and search

What I built

Built a new Elasticsearch library with automatic tenant scoping and migrated the survey service onto it, then consolidated three external packages into it and refactored the user service's sync.

  • Consolidation removed cross-repo dependencies ahead of the monorepo build-time work

Data Platform and Migrations

Technology used

Elasticsearch
Built a library that scopes every query to the organisation's index automatically, so tenant isolation is structural rather than each caller remembering, and migrated the survey service onto it.
TypeScript
Consolidated three separately published search packages into it, removing a cross-repo publish/consume cycle from every change.
Node.js
Refactored the user service ES sync onto the new library and improved its logging, which is where the duplicate-conversation and stale-document problems became visible.
2020–2023Notification job queue replacementReplaced the notification service's job queue and added monitoring of queue health.Platform and reliability

What I built

Replaced the Kue job queue, added Bull queue management routes to the notification service, built a reporting function for queue metrics, and handled deleted users and missing notification channels gracefully.

Observability and Reliability

Technology used

Bull
Replaced the Kue job queue with Bull, then added routes to the notification service to inspect and manage the queues, and built a reporting function to emit queue-depth and job-count metrics.
Redis
Bull is Redis-backed, so this covered the queue's Redis configuration and the connection lifecycle — including waiting for Mongo to connect before starting the handlers, after a startup race.
Node.js
Made the handlers tolerate deleted users and missing notification channels rather than throwing, which had been taking the service down.
MongoDB
Fixed the notification service's user lookups to handle soft-deleted users, which were throwing and taking the queue handler down with them rather than skipping the notification.
AWS Lambda
The queue-metrics reporter runs as a scheduled Lambda; corrected it to read the queue counts it actually needed.
TypeScript
Typed the job payloads so a producer can't enqueue a shape the consumer won't accept.
2022Live reporting views for business intelligencePer-customer database views so the business intelligence tools read live data without breaking customer data isolation.Data and search

What I built

Created tenanted views over surveys v1, survey v2 components, survey categories, distributions, invitees, engagement index and eNPS metrics so the BI stack could read platform data without breaching tenant isolation.

  • Resolved a case where survey invitee attributes had maxed out Redshift's allowed column count

Data Platform and Migrations

Technology used

MongoDB
Created tenanted database views over surveys v1, survey v2 components, categories, distributions, invitees, engagement index and eNPS metrics — views rather than an export, so the BI layer reads live data without a copy that can drift.
Redshift
Shaped the views for the Redshift ingest, including resolving a case where survey invitee attributes had exceeded Redshift's maximum column count — the attribute model is per-customer, so a wide customer broke the load.
Node.js
Automated view creation per tenant database, since each organisation has its own.
TypeScript
Generated the view definitions from the existing schemas so a model change surfaces in the view rather than silently diverging.
2021–2022Customer-defined webhooksLets customers subscribe their own systems to platform events, taken from proof of concept to production.APIs and integrations

What I built

Took webhooks from proof of concept to production: a self-service UI, persistence in MongoDB, and SNS/SQS-backed delivery through Lambda so customers could subscribe to platform events.

  • Ran as a self-development project before becoming a roadmap item

Public API and Developer Platform

Technology used

AWS Lambda
Built the delivery path as a Lambda invoked from the queue, with its own container image, taking it from a self-development proof of concept to production.
SNS/SQS
Fanned platform events out through SNS to SQS so delivery retries and slow customer endpoints can't back-pressure the platform, and added the organisation ID to the message so the consumer can scope correctly.
MongoDB
Modelled subscriptions per organisation plus a delivery record per attempt, so a customer can see what we tried to send and when it failed — the delivery log is the support tool.
React
Built the self-service UI for registering and managing webhook subscriptions, and decoupled it from the Integrations screens once they were separate concerns.
Node.js
Signed the payloads and verified signatures on the inbound side, and fixed the deploy package.json for the function.
TypeScript
Typed the event payloads so a new platform event has to declare its webhook shape.
2021Send a survey to a one-off listLets admins send a survey to an ad-hoc group of people without creating a saved distribution list first.Product features

What I built

Added the ability to send a survey to an ad-hoc list rather than a saved distribution list: draft persistence, send, review, recipient counts, and flagging of inactive users in the table.

Survey Builder and Planner

Technology used

MongoDB
Persisted ad-hoc recipient lists against the draft survey so a part-built list survives leaving the page, and fixed the list not loading past 100 users.
React
Built the list builder, the review step and the recipient counts, and flagged inactive users inline in the table so a sender knows before sending.
GraphQL
Added the queries behind counts and validation, and fixed the recipient count staying at 0 when date-based segments were used.
Node.js
Implemented send-with-ad-hoc-list in the survey pipeline alongside saved distribution lists.
TypeScript
Modelled an ad-hoc list as a distinct type from a saved distribution list so the send path can't confuse them.
2021First external APIThe platform's first external API, with documentation generated from the code and published automatically on every deploy.APIs and integrations

What I built

Led the build of Hive's first external API in Node/Express: attributes, integrations, integration mappings, locales, timezones, organisation info and user create/update, with automatic OpenAPI spec generation from inline Swagger comments and automated upload to Readme.io as part of the deploy pipeline.

  • Documentation published to Readme.io automatically on deploy
  • Extensive caching added across create-user, the global user verifier and user endpoints
  • Tenancy lookup endpoint for global users spanning multiple accounts

Public API and Developer Platform

Technology used

Express
Built Hive's first external API in Node/Express — attributes, integrations, integration mappings, locales, timezones, organisation info, and user create/update — including a tenancy-lookup endpoint for global users spanning multiple accounts.
OpenAPI
Generated the OpenAPI spec automatically from inline Swagger comments on the routes, then uploaded it to Readme.io as a deploy-pipeline step so published docs can't lag the API. Also fixed an invalid OpenAPI 3 definition and a validator that wasn't actually rejecting bad requests.
Redis
Added caching to the create-user endpoint, the global user verifier and the user endpoints once the integration partner's call volume made the uncached path the bottleneck.
MongoDB
Added a compound multikey index on user attributes to support the attribute-read endpoints, and deleted user mappings when a user is deleted.
Node.js
Improved create-user validation so a username-generation failure returns a usable error instead of a 500, and raised body-size limits where the partner posted larger payloads.
TypeScript
Typed the request and response contracts, which is what let the generated spec be trustworthy.
2021In-app developer toolbarA hidden toolbar that makes it faster to debug issues in live environments.Developer experience

What I built

Built a developer toolbar in the application to make debugging live environments faster.

Developer Experience and AI Engineering

Technology used

React
Built an in-app developer toolbar so live-environment state (org, user, flags) is visible and switchable without opening a console — this predates most of our observability work and was the fastest route to seeing what a customer's session actually had.
TypeScript
Gated it on environment and permission at the type level so it can't be rendered into a customer build by accident.
2021Faster service-to-service callsAdded DNS caching and connection reuse to internal service calls, cutting overhead on every request between services.Platform and reliability

What I built

Improved the internal RPC library's network behaviour: added a DNS cache, enabled HTTP KeepAlive, and added an RPC surface to the integration service.

  • DNS caching and KeepAlive removed per-call connection overhead across every inter-service hop

Observability and Reliability

Technology used

RPC
Added a DNS cache and enabled HTTP KeepAlive in the internal RPC library, removing a DNS lookup and a TCP handshake from every inter-service call — the cost was per-call and invisible until you look at connection counts.
Node.js
Added an RPC surface to the integration service so it could be called by other services rather than reached through the API.
TypeScript
Kept the RPC client generic and typed so a caller gets the method's real return type rather than unknown.
2021Token issue and revocationAdded the ability to issue and revoke access tokens in the authentication service.Security and access

What I built

Built create-token and revoke-token routes in the authentication service, brought the external authorisation package into the monorepo, and made the authorisation middleware work with the new token format.

  • Improved error handling in the Express auth library

Authentication and Sessions

Technology used

Node.js
Added create-token and revoke-token routes to the authentication service — revocation being the point, since the previous model could only wait for expiry.
Express
Brought the external authorisation package into the monorepo as a library and made its middleware work with the new token format, then improved its error handling so an auth failure says which check failed.
MongoDB
Persisted issued and revoked tokens so revocation is durable across service restarts.
TypeScript
Typed the token claims so a consumer reads a known shape rather than indexing a decoded blob.
2019–2021Replacement survey builderBuilt large parts of the new survey builder end to end, from editing and design through scheduling, translation and sending.Product features

What I built

Built large parts of the replacement survey builder end to end: Apollo/GraphQL app configuration, Edit Survey page, Design tab, survey CRUD and backend validation, survey preview, distribution lists, schedule tab, review tab and send, recipient counts, machine translations, and the landing page.

  • Shipped to production in 2020 and retired the previous planner in 2022
  • Performance work on a landing page that was fetching recipient counts for every survey
  • Made the builder usable at 1024px and on smaller devices

Survey Builder and Planner

Technology used

React
Built the replacement survey builder's screens — Edit Survey, the Design tab and its component add/edit views, survey intro, question detail, schedule and review tabs — and made the builder work down to 1024px after it was simply disabled at small sizes.
Apollo Client
Configured the app's GraphQL client from scratch, and later did the Apollo upgrade investigation and upgrade.
GraphQL
Designed the queries and mutations behind survey CRUD, and removed a landing-page query that fetched a recipient count for every survey in the list — the cause of it being "slow AF".
MongoDB
Implemented survey create/read/update/delete and the backend validation behind it, plus distribution-list persistence and deletion.
Node.js
Wrote the survey validation service and the preview rendering path, including making preview work again after page templates and typed ids landed.
Webpack
Maintained and upgraded the build, including the dependency upgrades taken for build performance.
TypeScript
Kept the new app strictly typed while the legacy app was not — this package was the proving ground for the patterns later adopted app-wide.
2020Consistent, accessible button statesStandardised colour and keyboard-focus states for buttons across the whole application in one change.Front end and accessibility

What I built

Reworked the Button component's colour and focus states across the application — a 317-file change that standardised interactive state styling.

  • Focus states were the accessibility-driven part of the change

Frontend Platform and Design System

Technology used

React
Reworked the design-system Button's colour and focus states across 317 files — the focus state was the accessibility-driven half, since the previous states were only distinguishable by colour.
styled-system
Expressed the variants through the theme's colour scale so a new variant is a token choice, not a new block of CSS.
Storybook
Updated the app's .storybook config and webpack config so the component's states were reviewable side by side while changing them.
2020Customisable employee experienceLet customers brand and customise what employees see when they respond to surveys or send recognition.Product features

What I built

Delivered the customisable employee-facing journey: 'Choose your adventure' landing experience, customisable peer recognition and survey submitted modals, customisable holding notification for suggestions, co-branding, and configurable positioning.

Survey Builder and Planner

Technology used

React
Built the customisable employee-facing journey — the "choose your adventure" landing, customisable peer recognition and survey-submitted modals, the holding notification for suggestions, and configurable positioning and co-branding.
react-intl
Made every piece of that copy translatable rather than hardcoded, since it is customer-configurable and multi-locale.
Node.js
Persisted the per-organisation customisation and served it to the unauthenticated employee app, which meant the config had to be fetchable by org slug before any user context exists.
TypeScript
Modelled the customisation options as a typed configuration rather than a loose object, so an unsupported option is a compile error.
2020Unified form handlingMoved form state onto the same model as the rest of the application, so forms behave consistently.Front end and accessibility

What I built

Migrated form state off Formik onto Redux (146 files) to unify form handling with the rest of the application's state model.

  • Reversed direction in 2026 with a redux-form → Formik migration once React 19 made legacy context untenable

Frontend Platform and Design System

Technology used

Redux
Migrated form state off Formik into Redux across 146 files so form state lived with the rest of the application state.
Formik
Removed Formik as the form state owner here — worth noting I reversed this direction in 2026, moving redux-form to Formik once React 19 made legacy context untenable. Same problem, opposite answer, because the constraint changed.
React
Reworked the affected form components' submit and validation wiring as part of the move.
TypeScript
Typed the form state slices so field names are checked rather than string-keyed.
2020Older-browser support and first accessibility fixesMade the platform work in Internet Explorer 11 for customers who required it, and fixed the first issues from a customer's accessibility audit.Front end and accessibility

What I built

Ran a compatibility programme for IE11 across the employee app and the admin console, and made the first dedicated accessibility fix — an inaccessible dropdown question raised by a customer's accessibility audit.

  • Earliest accessibility work; became a full WCAG programme in 2026

Accessibility

Technology used

React
Ran an IE11 compatibility programme across the employee app and the admin console, including an app that crashed outright after sign-in on IE11 locally.
CSS
Fixed the flexbox and layout differences that IE11 and Firefox rendered differently from Chrome, rather than shipping a separate stylesheet.
TypeScript
Fixed the dropdown question raised as inaccessible by a customer's accessibility audit — my first dedicated accessibility work, which became the WCAG programme in 2026.
2020Confidentiality messaging for employeesThe screens that explain to employees how their identity is protected before they respond, which is central to honest feedback.Security and access

What I built

Built the in-app confidentiality commitment page and identity protection messaging shown to employees before they respond — the user-facing half of Hive's confidentiality promise.

Security and Privacy

Technology used

React
Built the in-app confidentiality commitment page and the identity-protection messaging shown before an employee responds — the user-facing half of the promise the confidentiality maths enforces.
TypeScript
Drove the copy from the organisation's actual confidentiality configuration, so the page cannot promise a threshold the backend isn't applying.
2020Multi-language supportAdded an in-app language selector, upgraded the translation library across the app and made translation builds faster.Front end and accessibility

What I built

Refactored locale handling, built the in-app language selector, upgraded react-intl across the app (244 files), and made message extraction substantially faster.

  • Machine translation support in the survey builder
  • Later added support for 10 additional locales

Frontend Platform and Design System

Technology used

react-intl
Upgraded react-intl across the app — a 244-file change — and refactored locale handling so locales are resolved in one place rather than per component.
React
Built the in-app language selector and fixed the popovers that broke as a result of the react-intl upgrade's render changes.
TypeScript
Made message extraction substantially faster, and typed the message catalogue so a missing key is caught at build time rather than rendering the id to a user.
2020Kiosk mode for shared devicesLets employees without their own device answer surveys on a shared tablet, resetting between people.Product features

What I built

Built kiosk mode for shared-device surveying, including an inactivity timeout that resets the session between respondents and kiosk-specific notification handling.

Survey Builder and Planner

Technology used

React
Built kiosk mode for shared devices, including the inactivity timeout that resets state between respondents so one person's partial answers can't be seen by the next, and kiosk-specific notification handling.
TypeScript
Modelled the kiosk session as an explicit state machine rather than scattered booleans, because the reset path is the security-relevant part.
2019–2020Product usage analyticsConnected product usage data to customer accounts, so usage could be understood account by account.Platform and reliability

What I built

Instrumented the platform for product analytics: Pendo tagging, defensive guards around visitor lookup, staging secrets in the deploy pipeline, and piping the HubSpot company ID through the platform into Pendo so product usage could be tied to accounts.

  • Later extended to pull a user's highest active platform permission through as Pendo's 'role' field

Observability and Reliability

Technology used

Pendo
Instrumented the platform for product analytics — tagging, and a guard around visitor lookup because the Pendo object isn't always present on window when the call fires, which was throwing on first paint.
React
Threaded the identifying context through the app shell, including passing the HubSpot company id into Pendo so product usage ties to accounts, and later a user's highest active platform permission as Pendo's role.
TypeScript
Declared the window.pendo shape rather than reaching through any, so the missing-object case is a type-level concern.
2019–2020First internal component libraryCo-created the team's first component library, built for accessibility. The whole team now builds with it.Front end and accessibility

What I built

Co-created Hive's first internal component library, built on Reakit for accessible primitives and styled-system for design tokens, documented in Storybook. Personally built Modal, Panel, Checkbox, Switch, Time Input, Header Bar, Collapsible Panel, Toggle Switch, icons and the colour theme.

  • Chose Reakit specifically for accessibility and composition over inheritance
  • Fixed Storybook under IE11 and restructured story ordering for discoverability
  • Became the pattern the whole team now contributes to

Frontend Platform and Design System

Technology used

Reakit
Chose Reakit for the primitives specifically because it ships accessible behaviour (focus management, ARIA, keyboard) rather than styling — the components I built on it were Modal, Panel, Checkbox, Switch, Time Input, Header Bar, Collapsible Panel and Toggle Switch.
styled-system
Built the theme and colour scale and expressed component styling as style props, so spacing and colour come from tokens instead of ad-hoc CSS.
Storybook
Documented every component in Storybook, fixed the config so stories rendered under IE11, and restructured story ordering so the library was navigable rather than alphabetical noise.
React
Composed the components as function components with hooks from the start, deliberately not the class/HOC pattern the legacy app used.
TypeScript
Typed the component props and the theme so a style prop that isn't in the scale fails at compile time.
2019Type-safe API calls in the front endIntroduced code generation so front-end API calls are checked against the API's types at build time.Platform and reliability

What I built

Added the codegen script, generated GraphQL types across the app and fixed the resulting build errors — the start of type-safe GraphQL operations in the frontend.

Platform Modernisation and Upgrades

Technology used

GraphQL Codegen
Added the codegen script and wired it into the build, generating operation and schema types from the SDL instead of hand-writing them.
GraphQL
Introduced generated types across the app's operations, which immediately surfaced a batch of latent build errors where queries and components disagreed.
TypeScript
Fixed the resulting type errors rather than loosening the generated types — that was the value of doing it.
2019Reporting accuracy fixesFixed rounding errors in percentage and response-rate figures so reports add up correctly.Product features

What I built

Series of fixes to percentage-favourable and response-rate calculations, including segment-level rounding errors and font/presentation defects in the reporting UI.

  • "Make reports great again" — consolidated reporting correctness pass

Survey Analytics and Reporting

Technology used

Node.js
Corrected percentage-favourable and response-rate maths, including segment-level rounding where per-segment rounding then summing produced totals that didn't reconcile.
Elasticsearch
Traced the wrong figures back to how the aggregation buckets were being combined before rounding, rather than patching the number at the presentation layer.
TypeScript
Tightened the metric types so a percentage and a count can't be passed interchangeably, which was how one of the defects arose.
2019Retired the legacy manager roleWrote the data migrations that moved customers off an old, inflexible manager role.Security and access

What I built

Wrote the data migrations that moved the platform off the base manager role, including the Elasticsearch re-sync required to keep search documents consistent with the new role model.

  • Deduplicated missing segments so they were not added multiple times during migration

Users, Roles and Authorisation

Technology used

MongoDB
Wrote the migrations that removed the base manager role, including deduplicating missing segments so the same segment wasn't appended repeatedly across runs.
Mongoose
Updated the role and user models and their references as the role model changed shape.
Elasticsearch
Triggered the ES re-sync as part of the migration, because role changes affect authorisation-filtered search documents and leaving them stale would have silently changed what managers could see.
Node.js
Made the migration re-runnable, which mattered because it had to be applied per tenant database.
2019Reminder emails that scaleRewrote reminder jobs to process records as a stream instead of loading them all into memory, removing a limit on large customers.Product features

What I built

Reworked recognition and suggestion reminder jobs to stream records rather than materialise them in memory, removing a scaling ceiling on large accounts.

Peer recognition

Technology used

Node.js
Converted the recognition and suggestion reminder jobs from materialising the full recipient set in memory to streaming a cursor, removing a hard ceiling on large accounts.
MongoDB
Drove the stream from a cursor rather than .toArray() — the same class of fix I later applied to survey sending.
AWS Batch
These run as containerised batch jobs, so the memory ceiling was the container's, and the fix removed the need to keep raising it.
2018Consistent answer ordering in reportsFixed multiple-choice answers appearing in a different order in different reports.Product features

What I built

Fixed multiple-choice option ordering by adding explicit ordering to the distribution result from the Elasticsearch query and to the filter options in the reporting Filters pane.

Survey Analytics and Reporting

Technology used

Elasticsearch
Added explicit ordering to the distribution aggregation result so multiple-choice options come back in their defined order — the aggregation had been returning bucket order, which is by count.
Node.js
Applied the same ordering to the reporting Filters pane options so the sidebar and the chart agree.
2018Web framework upgrade across all servicesCoordinated an Express upgrade across every service in what was then a set of separate repositories.Platform and reliability

What I built

Coordinated an upgrade of Express to 4.16.4 across every service in the then Bitbucket multi-repo estate, removing the unused Morgan logger and its types as part of the sweep.

  • Executed the same change independently across ~10 service repositories before the monorepo existed

Platform Modernisation and Upgrades

Technology used

Node.js
Ran the same upgrade independently across roughly ten separate Bitbucket service repositories, before the monorepo existed — the repetition is the point: there was no single place to change it.
Express
Upgraded Express to 4.16.4 and removed Morgan and its @types after establishing nothing used it; added skipLibCheck to tsconfig where conflicting type-definition versions broke the build.
2018Form validation approachDesigned how forms show errors, both next to each field and summarised at the end.Front end and accessibility

What I built

Introduced a memoised selector that pulls all field validation errors for a form out of the Redux store, plus a prop on the text and date inputs so validation could be hidden at field level and aggregated at the foot of the form.

  • Created a memoised selector with createSelector rather than recomputing per render
  • Restructured the Error component to show field errors and global form errors together

Frontend Platform and Design System

Technology used

Redux
Built a memoised selector that pulls every field validation error for a given form out of the store in one pass, replacing per-field subscriptions.
React
Added a prop to the text and date inputs so validation can be suppressed at field level and aggregated at the foot of the form, and restructured the Error component to show field and global form errors together.
TypeScript
Typed the selector's return shape so consumers get the error map rather than any, and corrected the type when the selector was renamed.
2018Messaging layout and browser fixesMy first work at Hive: rebuilt the messaging conversation layout and fixed cross-browser display bugs.Product features

What I built

First body of work at Hive: rebuilt the Messenger conversation view on a flex-column layout with scroll observers, replacing absolute positioning, and fixed word-wrap, overflow and avatar alignment defects across IE and Firefox.

  • Refactored messenger to use observers and a flex column approach, removing the floating message form
  • Added max-widths and overflow break-word handling for cross-browser consistency

Messenger

Technology used

React
Refactored the Messenger conversation from absolute positioning to a flex-column layout driven by scroll observers, so the message form stops floating and the list scrolls predictably. Moved styles out of the container into the presentational component so it renders standalone.
CSS
Fixed word-wrap on long unbroken strings with overflow-wrap: break-word, capped bubble and container max-widths to stop overflow of the parent, and corrected flex alignment so the avatar stays put regardless of message height. Included explicit IE and Firefox fixes.
TypeScript
Typed the message and conversation props as I went, and allowed a custom className through the MessageForm props so the modal could stop passing form styles down.
2018Blocked empty survey answersStopped answers made only of spaces being submitted and counted as real responses.Product features

What I built

Built whitespace-trimming utilities, including a recursive one, wired into the response controller and the five main question components, so whitespace-only answers and comments could no longer be submitted.

  • Recursive traversal of the answer object to trim any nested strings
  • Backed with unit tests

Survey Analytics and Reporting

Technology used

Node.js
Added the validation to the response controller so whitespace-only answers are rejected server-side, not just hidden in the UI.
TypeScript
Wrote a whitespace check and a recursive trim that walks an arbitrary answer object and trims every nested string — the answer shape differs per question type, so a flat trim wouldn't have worked.
node:test
Backed the trim utilities with unit tests over the awkward cases (nested objects, the multiple-choice other field) rather than manual checking.

Education and beyond

BSc Computer Forensics, First Class Honours

Northumbria University, 2016.

Best Undergraduate Computing StudentAwarded by Accenture, Northumbria University, 2016

Erasmus year

VIA University College, Horsens, Denmark, during the third year of my degree.

Mental health qualification

Gateshead College, 2022.

Restless Development volunteer

Three months in rural India after graduating, delivering CV and interview workshops in schools and colleges with a team of Indian and UK volunteers.

Conferences

AWS Summit London, MongoDB summits, GraphQL Conf Berlin, Front End North East and Up Front Manchester.