AI: 16 proof points
Rows on the facts page whose own text or source section carries "AI". The product name links the page with the full text. All skills.
| Role | Product | Situation | Task | Action | Result | Year | Skills |
|---|---|---|---|---|---|---|---|
| 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 |
| Associate Product Director at Novo Nordisk | Digital Incubation Digital incubation unit for branded digital engagement, evaluating build, buy and partner solutions | Asked after Wegovycare to scale its ways of working across the product organisation: to work across silos and help move the organisation from solution-first project thinking to a product model with an outcomes focus. | Build the unit that shapes the organisation's next big bets, and make problem-first the default. | Built the incubation unit entirely through influence. Designed a portfolio model and a gated incubation pipeline. Wrote the discovery playbook. Coached the incubation PMs. Secured funding and managed resourcing and cross-charges for the incubation teams. Evaluated build, buy and partner options for each bet. | Moved the business from solution-first to problem-first, and from output to outcomes. | Feb 2022 - Feb 2026 | AI, GenAI, regulated, compliance, pharma, healthcare, patients, discovery, incubation, ways of working, growth, retention, funnels, experimentation, launch, brand, team leadership, stakeholders, consumer, budget |
| Associate Product Director at Novo Nordisk | Product Operations standards, artefacts, ways of working | A wider remit across the product pipeline, to complete the move to a product operating model. | Establish metrics across a portfolio of 12 products. | Set product artefacts and quality standards: gate model and deliverables, product-ops metrics, portfolio reports, business case templates, problem and north-star statements. | Helped product teams connect work to commercial outcomes. | Feb 2022 - Feb 2026 | AI, GenAI, regulated, compliance, pharma, healthcare, patients, discovery, incubation, ways of working, growth, retention, funnels, experimentation, launch, brand, team leadership, stakeholders, consumer, budget |
| Associate Product Director at Novo Nordisk | Head of Patient Products Patient Solutions, a portfolio of consumer engagement products (companion apps adjacent to the medicines) | Interim reorg of product teams before the Wegovy Pill project. | Lead 6 experienced PMs building consumer engagement products, managing by outcomes; for a period, before moving into the pill team where the need was greatest. | Individual coaching and weekly experiment sharing; made individual product metrics public. | Broke product silos, established weekly demos and experiment sharing, encouraged learning loops. | Feb 2022 - Feb 2026 | AI, GenAI, regulated, compliance, pharma, healthcare, patients, discovery, incubation, ways of working, growth, retention, funnels, experimentation, launch, brand, team leadership, stakeholders, consumer, budget |
| Associate Product Director at Novo Nordisk | project steercos Chaired project steercos. Flipped the format from status updates to interactive co-creation | Steercos were project management checklists: project not product focused, and unsuited for high-uncertainty discovery-stage products. | Chair project steercos. | Flipped the format from status updates to interactive co-creation. | Cross-functional VPs moved from product sceptics to advocates. | Feb 2022 - Feb 2026 | AI, GenAI, regulated, compliance, pharma, healthcare, patients, discovery, incubation, ways of working, growth, retention, funnels, experimentation, launch, brand, team leadership, stakeholders, consumer, budget |
| 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 |
| 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 |