prototyping: 19 proof points
Rows on the facts page whose own text or source section carries "prototyping". The product name links the page with the full text. All skills.
| Role | Product | Situation | Task | Action | Result | Year | Skills |
|---|---|---|---|---|---|---|---|
| Senior Product Manager at Novo Nordisk | Wegovycare Wegovycare, a digital service to drive retention and repeat prescriptions for Wegovy | The brief was a set of standalone features the business thought would help, but nobody had talked to the patients. | Find the lever that would keep patients on treatment and coming back for repeat prescriptions. | Talked to patients: everyone wanted the same three things, how much weight they will lose, whether this is normal, whether they are on track. Made those the core loop; built a weight-loss prediction model in Excel to answer the first, then a profiling engine to personalise the rest. | 10% penetration in the first national market. Fastest-scaling and biggest-adopted digital product at Novo. | Mar 2020 - Feb 2022 | algorithm, API, regulated, pharma, healthcare, patients, discovery, prototyping, ways of working, growth, retention, roadmap, 0 to 1, marketing, team leadership, stakeholders, consumer |
| Senior Product Manager at Novo Nordisk | Wegovycare Wegovycare weight-loss prediction model | Patient research showed everyone wanted the same three things: how much weight they will lose, whether this is normal, whether they are on track. Nothing in the brief answered them. | Make those three questions the core loop of the product, and find the growth lever inside them. | Built a weight-loss prediction model answering the first question: a predicted trajectory for the individual to check progress against. Started as an Excel spreadsheet on a laptop; the maths worked out with the strongest backend engineer, then taken from concept to prototype. The same check-ins fed the profiling engine. | Patients could see whether they were on track against their own projection. The model was later spun out as a Bayesian API service, a product in its own right, and the team extended it from weight to HbA1c. | Mar 2020 - Feb 2022 | algorithm, API, regulated, pharma, healthcare, patients, discovery, prototyping, ways of working, growth, retention, roadmap, 0 to 1, marketing, team leadership, stakeholders, consumer |
| Senior Product Manager at Novo Nordisk | Wegovycare Wegovycare, a digital service to drive retention and repeat prescriptions for Wegovy | Applied for a SaMD product role at Novo; put forward instead for a digital solution for a then unheard-of weight-loss medicine. The final-round brief was solution-first: standalone features the business thought would help. Nobody had spoken to patients. | Persuade the business to set the brief aside and start with the problem, then use that as a mandate to change how they worked. | First product team at Novo to interview patients, run discovery, build prototypes and co-create with markets. Led a cross-functional team of 10 across the full product lifecycle; it took persuasion and a leap of faith from stakeholders. | Launched on time and on budget. 10% penetration in the first national market, the biggest adoption of any digital solution at Novo; still live. Asked to scale the ways of working across the organisation and promoted to Associate Product Director. | Mar 2020 - Feb 2022 | pharma, healthcare, patients, discovery, prototyping, ways of working, growth, retention, launch, 0 to 1, team leadership, stakeholders, budget |
| Associate Product Director at Novo Nordisk | GenAI proof of concept for automating compliance reviews Agentic RAG proof of concept for compliance reviews, with a Figma plugin | Every release of health software needed sign-off from medical, legal and regulatory reviewers. The process was built for marketing materials, not software: every screen was manually captured as a PDF and reviewed manually, stacking the regulatory risk to the end of the development cycle and sometimes adding months to delivery. | Test whether an LLM could take on the review so product teams could shift left: fail in design, not at review. Two acceptance tests set up front: useful to product teams, and catches what the manual review catches. | Used an internal LLM sandbox to build a RAG model of the guidelines and regulations, producing a full audit trail per submission. Built a prototype agent that plugged into Figma so designers could query the guidelines before investing effort. Pitched it to senior leadership & tested with product team. | Product team loved it. The proof of concept showed a clear path to much faster release cycles, but the timing was 12 months too early & the business was not ready for AI. Tom moved to help the Wegovy Pill launch. | Feb 2022 - Feb 2026 | AI, GenAI, regulated, compliance, pharma, healthcare, discovery, prototyping, ways of working, launch, marketing, team leadership, stakeholders |
| Associate Product Director at Novo Nordisk | CagriSema Digital discovery programme for CagriSema, the company's top drug asset | CagriSema was the first drug to span two therapy areas, diabetes and obesity. Each business unit ran independently with their own priorities and budgets. | Define what digital initiatives should accompany the drug, get both business units to agree, and get it funded. | Started with the problem, and uncovering the new user journeys to create a shared understanding of the problem space across both units. Then ideation: 128 candidate ideas, cut to a shortlist of 5, assumption-tested with prototypes, 4 recommended, each with a funding-gated rollout. Navigated the programme through internal governance. | Funding secured for a portfolio of 4 digital initiatives (a first). Aligned two business units on a common digital strategy (also a first). | Feb 2022 - Feb 2026 | AI, GenAI, regulated, compliance, pharma, healthcare, patients, discovery, prototyping, incubation, ways of working, growth, retention, funnels, experimentation, launch, brand, team leadership, stakeholders, consumer, budget |
| Senior Product Manager at Novo Nordisk | Wegovycare Wegovycare profiling and customisation engine, delivered as an interactive magazine | Research showed every patient journey is different and every patient has different needs. A linear app would not work, and the drop-off risks were different for each person. | Identify each patient's drop-off risks and act on them automatically, with a system that coped with real people who do not check in on schedule. | Tom's own idea and pattern, most of the algorithm his. Built a continuous profiling engine combining clinical data, usage signals and PROMs. Applied a consumer marketing playbook to act on the top risk: it decided what content was shown and could trigger a messaging flow. Ran on fuzzy logic, tolerating gaps and misuse. Output to the patient: an interactive magazine that changed with them. | Every patient got a personalised experience from one product and one codebase. Part of the launch that reached 10% adoption in the first market and became the fastest-scaling digital product at Novo. | Mar 2020 - Feb 2022 | algorithm, API, regulated, pharma, healthcare, patients, discovery, prototyping, ways of working, growth, retention, roadmap, launch, 0 to 1, marketing, team leadership, stakeholders, consumer |
| Senior Product Manager at Novo Nordisk | Wegovycare Wegovycare, digital patient platform for obesity medicine, built to scale | Every market needed its own version of every digital product, so nothing at Novo had ever scaled beyond one country. | Build one product that many markets could adopt and adapt without forking it. | Designed for scale: modular architecture, feature flags, an integrated CMS and a translation pipeline. Systematised co-creation with the markets so they shaped the product rather than waiting for it. | Novo's first digital health product adopted by multiple markets. First digital Novo product to scale. | Mar 2020 - Feb 2022 | algorithm, API, regulated, pharma, healthcare, patients, discovery, prototyping, ways of working, growth, retention, roadmap, 0 to 1, marketing, team leadership, stakeholders, consumer |
| PM/GM at LEO Innovation Lab | Diagnosis App Prototype smartphone app diagnosing skin conditions with machine learning | A moonshot: could a smartphone camera diagnose skin conditions? A 12-person team of data scientists, ML and computer vision engineers, wired for logic and certainty, in the deep uncertainty of product discovery. His first deep experience leading an ML team. | Lead the product direction, prioritisation and strategy, and get a working prototype that could be evaluated. | Worked with dermatologists to redesign closed-loop diagnosis and the ML training platform. Bootstrapped the ML engine with clinical decision trees. Designed the pipeline for data collection and analysis. Models were evaluated against a set of pre-tested images the dermatologists had all voted on. Not a medical device by design: disclaimers made clear it was not a diagnosis. Evaluated go-to-market and identified seven paths to market. | Over 80% accuracy across three skin conditions. Doubled the labelling output of the in-house image labelling platform. | Nov 2018 - Jan 2020 | AI, machine learning, computer vision, healthcare, discovery, prototyping, growth, launch, team leadership |
| PM/GM at LEO Innovation Lab | BetterVisitBot a pre-briefing chatbot for doctor consultations | Patients sometimes get intimidated by the doctor, and don't get the most out of their consultation, or forget what was said. | Prototype it with GPs. | Hid a dermatologist in an adjacent room to simulate a consultation chatbot. | Right idea, too early. Now it isn't. | 2016 to 2020 | AI, machine learning, computer vision, healthcare, patients, discovery, prototyping, growth, launch, team leadership |
| Solo projects, building with AI | TomBot TomBot, a chatbot CV at takenbyninjas.com | Tom wanted to create a novel way of presenting his CV, and find out first-hand what AI can and cannot do. Accuracy of recall was the key criterion: a CV bot that hallucinates is worse than no bot. | Build something real with AI and ship it, in his own content and voice. | Built with Claude Code on the Claude API: chunked RAG vector store, eval suite, guard-rails. Question-to-question matching against a bank of pre-mapped questions rather than searching raw content: it limits the chatbot nature but keeps the answers accurate. Content and tone of voice his own. | Live January 2026. Linked from every CV with a UTM tag per employer so each application's traffic is visible. Pinned on LinkedIn. | 2026 | AI, GenAI, regulated, compliance, prototyping, team leadership |
| Solo projects, building with AI | kittenpm.com kittenpm.com, a free browser-based product management training SIM inspired by Lemmings | Wanted a portfolio piece that is not a portfolio, aimed at product peers and recruiters. | Generate reach and demonstrate product skills by teaching product trade-offs as a game. | Built with React, TypeScript and Phaser, using Claude as the engineering team. Players practise balancing product trade-offs in real time; those who complete the game get a digital certificate to embed on LinkedIn, which drives further reach. | Live July 2026, in public beta. | 2026 | AI, GenAI, regulated, compliance, prototyping, team leadership |
| Solo projects, building with AI | deathspiralorgoldenage.org deathspiralorgoldenage.org, a weekly public poll, live sentiment tracker and open economic model on AI's economic impact, with CC0 data | A thought experiment that spun out from a discussion at a Claude meetup with Anthropic. | Build a public, open-data way to track the question over time. | Researched and built with AI. Content is human; the site is engineered and researched with AI. Weekly poll, sentiment tracker and an open economic model, all data released CC0. | Live September 2026. | 2026 | AI, GenAI, regulated, compliance, prototyping, experimentation, team leadership |
| PM/GM at LEO Innovation Lab | prototyping and user interviews Ways of working across LEO Innovation Lab's product teams | Anthropologists were on staff at the lab, but product teams outsourced the investigation and got learnings second-hand. | Raise the quality bar across the lab, not just his own team, without a mandate over the other teams. | Championed design sprints and user testing. Made rapid prototyping and direct user interviews standard practice across all product teams. First product lead to present mistakes and learnings at the company all-hands. | Prototyping and user interviews became the norm across the lab. The monthly all-hands moved from vanity metrics to mistakes made and lessons learnt. | Nov 2016 - Jan 2020 | AI, computer vision, pharma, healthcare, patients, prototyping, incubation, ways of working, turnaround, 0 to 1, startup, team leadership |
| PM/GM at LEO Innovation Lab | testing beats opinions How design disagreements get settled | At Host Europe, as design manager in a PRINCE2 waterfall setup, a passionate argument with a graphic designer, each convinced their idea was right. Neither knew about testing. | A decade later, at LEO Innovation Lab, the same disagreement with a product designer: he preferred A, Tom preferred B. | They agreed to test it that afternoon. | Users preferred something entirely different, option C. The poor decision was anchoring on their own ideas and locking out better alternatives. Detaching from ego changed everything: it is not about who has the best idea, it is about creating space for learning. | 2005 and about 2017 | AI, computer vision, pharma, healthcare, patients, prototyping, incubation, turnaround, startup, team leadership |
| Senior Product Manager at Novo Nordisk | Wegovycare releases Wegovycare release process | Release cycles for digital products at Novo were yearly. Every release carried heavy documentation for a high-regulation environment, and the documentation was written by hand. | Release often enough to learn from patients, inside the same regulatory rules. | Automated the documentation and the release workflows so the compliance paperwork fell out of the build rather than being written afterwards. | Release cycles went from yearly to bi-monthly. Fast for pharma. Iterative learning became possible. | Mar 2020 - Feb 2022 | algorithm, API, regulated, compliance, pharma, healthcare, patients, discovery, prototyping, ways of working, growth, retention, roadmap, 0 to 1, marketing, team leadership, stakeholders, consumer |
| Senior Product Manager at Novo Nordisk | Wegovycare roadmap Wegovycare roadmap | A project-model organisation steered by deliverables and dates. Nobody on the product had a way of saying what mattered next, or why. | Own the product vision and the backlog, and steer priorities by what patients did and said rather than by the plan. | Set the vision. Implemented OKRs, as in every product, else how do you know you have succeeded. Owned the backlog end to end: problem statements, user stories, acceptance criteria, sprint-by-sprint prioritisation with a cross-functional team of 10. Steered priorities and the roadmap with qualitative and quantitative signals together, patient interviews beside usage data. | A roadmap that traced back to patient evidence and a definition of success the stakeholders had agreed up front. The product hit 10% adoption in its first market against that definition. | Mar 2020 - Feb 2022 | algorithm, API, regulated, pharma, healthcare, patients, discovery, prototyping, ways of working, growth, retention, roadmap, 0 to 1, marketing, team leadership, stakeholders, consumer |
| PM/GM at LEO Innovation Lab | Diagnosis App data pipeline Image labelling platform and data pipeline for the diagnosis app | Labelling by dermatologists was critical for model performance, and a significant bottleneck. | Get more labelled data through the system without lowering its quality. | Interviewed every dermatologist on the labelling work to understand how they actually worked, then redesigned the in-house image labelling platform around that. Designed the pipeline for data collection and analysis to feed it. | Doubled dermatologist labelling throughput. Less of their time on labelling training data, more labelled data for the models. | Nov 2018 - Jan 2020 | AI, machine learning, computer vision, healthcare, discovery, prototyping, growth, launch, team leadership |
| PM/GM at LEO Innovation Lab | Diagnosis App paths to market Go-to-market evaluation for a moonshot ML prototype in dermatology | A functioning prototype, but heavy regulatory barriers and no clear path to market. | Work out how, or whether, a moonshot prototype could reach a market. | Evaluated go-to-market systematically and mapped the options with the team. | Identified seven paths to market, with the trade-offs of each, for the lab to decide on. | 2019 | AI, machine learning, computer vision, regulated, healthcare, discovery, prototyping, growth, launch, team leadership |
| PM/GM at LEO Innovation Lab | LEO lab model LEO Innovation Lab as an operating model | LEO Pharma could see digital disruption coming to healthcare. Its answer was an arm's-length innovation lab: better to disrupt ourselves than let a competitor do it. Keeping it separate made sense: different thinking, different ways of working, experts from all sorts of fields. A true melting pot. | Build and ship ventures inside that model, and get them home to the core business. | They did. The lab was incredibly agile, with rapid learning cycles and brilliant peers, but too remote: the innovations struggled to find a home in the core business. | The lab worked in isolation; the parent ship sailed on unchanged, and the model was not sustainable. Disruption cannot be outsourced to a separate unit and grafted back on later; the parent has to change too. That conclusion took Tom to Novo to try the harder bet from inside. | Nov 2016 - Jan 2020 | AI, computer vision, pharma, healthcare, patients, prototyping, incubation, ways of working, turnaround, startup, team leadership, remote |