Product strategy

Acts as a product manager for AI features who starts from the user problem, defines quality with evals, designs for wrong answers and uncertainty, and watches cost, latency and user trust.

Reframes a nonprofit or public programme as a product - who it serves, the outcome they need, evidence, riskiest assumptions and small tests - adapted to funder reporting and volunteer capacity.

Assesses product-market fit from retention curves, the very disappointed survey, usage depth and qualitative signals, by segment, and recommends what to do next.

Cuts a feature list down to the smallest testable MVP, with the riskiest hypotheses, success criteria set before launch, the cheapest MVP type and a deferred list with re-entry triggers.

Designs a free plan, free trial or reverse trial with limits tied to the value metric, conversion triggers, abuse controls, cost to serve and the metrics to judge it.

Evaluates whether and where to add an AI feature, covering problem fit, quality bar and evals, failure modes, cost, trust and a staged rollout, ending in a build, shrink or skip verdict.

Compares building, buying or adopting open source for a capability on total cost, time to value, strategic fit, lock-in and risk, then recommends one with triggers for revisiting the decision.

Evaluates whether and how to open-source a product or component, weighing goals, scope, licence models, competition, community expectations, maintenance cost and business model fit.

Acts as a product manager for physical products who thinks in BOM cost, margin stack, design for manufacture, tooling lead times, EVT/DVT/PVT gates, certification, packaging and returns.

Maps a subscriber's journey from trial through activation, conversion, expansion and renewal, with the metric, triggers, touchpoints and risk signals per stage and the moments that move revenue.

Turns an hourly or ad-hoc service into two to four packages with hour budgets, scope boundaries, add-ons, a margin and capacity check per tier, and a plan to move existing clients across.

Plans a response to a competitor's launch or price move with a facts check, impact by segment, ranked options, internal and customer messaging, a watch plan and what not to do.

Builds a ranked menu of expansion plays - seat growth, tier upgrades, add-ons, usage overage and services - each with trigger, segment, message and expected impact, plus an NRR target.

Plans retiring a feature with user and revenue impact, migration paths, a dated timeline, communications by segment, support preparation and data handling. Use when reducing product surface.

Plans a platform or API product strategy covering ecosystem participants, value exchange, cold start, developer experience, monetisation, governance and a phased plan with metrics.

Plans discontinuing a physical product with a last-time buy, stock run-down, spare parts and repair support, obligations to check, firmware or app support, take-back and customer communication.

Prepares a product manager for an executive product review with the narrative, an opening, metrics against goals, framed decisions, likely hard questions with answers and a pre-wire plan.

Takes a pricing change through gated steps, from research and options to an impact model, a communication plan and a rollout review, pausing for the owner's approval between steps.

Scores candidate countries, regions or segments on demand evidence, competition, localisation and regulatory effort, channel access and fit, then recommends a sequence and an entry test.

Reviews a range of products or SKUs on revenue, margin, growth, strategic role, complexity cost and cannibalisation, recommending keep, fix, reposition or cut with a transition plan.

Tears down a product's onboarding, value moments, pricing, retention and growth mechanics, separates observed facts from inference, and turns them into lessons for your own product.

Sets kill criteria for a product bet before results arrive, with leading indicators, continue, rethink and stop thresholds, review dates, decision rights and a wind-down outline.

Works back from target retail price through channel margins, sales tax, shipping, returns and warranty reserve to a target landed and BOM cost, showing the gap and levers to close it.

Writes requirements for an AI feature covering the user problem, behaviour with good and bad output examples, a quality bar, evals, failure handling, data, safety, cost and launch criteria.

Writes a working-backwards press release and FAQ for a proposed product, with customer and internal FAQs that expose the hard questions. Use when pitching a new initiative.

Writes five to seven ranked product principles a team can use to settle trade-offs, each with its meaning, what it rules out and an example decision, tested against real debates.

Writes a one-page product strategy with a diagnosis of the core challenge, a guiding policy, coherent actions and an explicit list of what the team will not do.

Writes a memorable three-to-five-year product vision covering the customer's future, the change the product makes, guiding principles and what it means for next year's work.

Writes a Shape Up pitch with the problem, the appetite, a fat-marker solution described in words, rabbit holes with patches and explicit no-gos. For teams using fixed-time, variable-scope cycles.