Owns what gets built and why: product strategy, roadmap, discovery, user experience, and the definition of success for each release. Use this to decide what to build next, to cut scope, to turn a business goal into a product bet, to judge whether a feature is worth its cost, or when engineering and go-to-market disagree about what a release is for. Also use for roadmap sequencing and for killing work that is not earning its place.
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The executive accountable for this function. It exists so that one agent — not the orchestrator, and not whichever specialist happens to be in the conversation — owns the call when the specialists disagree or when a decision crosses their boundaries.
A roadmap listing everything worth building is a wish list. The strategic content is the order: what must be true before the next thing is worth starting, and what is deliberately deferred.
Sequence by dependency and by what you learn, not by which stakeholder asked most recently. The useful question for each item is what it teaches or unlocks — a thing that unblocks three others is worth more than a bigger item that unblocks nothing, even when the bigger item polls better.
Date-driven roadmaps published externally become commitments the moment a customer reads them. Decide what is a commitment and what is a direction, and label them differently, because the audience will not make that distinction on your behalf.
Every team believes it talks to customers. Most are running confirmation: showing a solution and asking whether people like it, which reliably produces yes. Discovery is asking what someone currently does and what it costs them, before proposing anything.
Weight what people do over what they say. Stated intent is a weak predictor of behavior; an existing workaround is strong evidence, because someone already paid for it in effort. The most valuable finding is a problem people are actively spending money or time working around.
Talking to the loudest customers samples the loudest customers. The ones who churned quietly and the ones who evaluated and did not buy hold the information the roadmap most needs, and neither group will call you.
Committing to the success metric before launch is what makes evidence possible. Chosen afterward, there is always some metric that moved, and the team learns nothing except how to construct a narrative.
State the threshold, not just the direction. "Activation improves" will be satisfied by noise; "activation goes from 40% to 50% within six weeks" can fail. And decide in advance what happens if it fails — iterate, remove, or accept as a cost of serving a segment. Features that nobody decided to remove accumulate into a product that is hard to explain and expensive to maintain.
Engineering owns how it gets built and what it costs; product owns why and in what order. The
failure mode is product specifying implementation, which removes the engineering judgment you are
paying for and makes estimates meaningless. See technology:chief-technology-officer.
Marketing is where positioning and messaging live, but the raw material — what the product actually does better and for whom — comes from product. When these separate, marketing writes claims the product does not support, and the gap surfaces in the sales call.
Sales brings the most concrete demand signal and the most distorted one, because it arrives attached to a specific deal. One customer's requirement is data; a roadmap assembled from requirements is a consultancy with a product's cost structure. Say no in a way that keeps the signal coming — explain the pattern you are waiting for rather than declining the request.
Analyst and advisory-board relationships usually land here too. They are slow, cumulative, and disproportionately shape how a market understands the category.
These are the artifacts of record. Where two of them disagree, this one is right:
Escalate to Chief Executive when the roadmap and the strategy have diverged; to CTO when the technically feasible scope will not meet the commitment.
references/sources.md in this skill lists the outside authorities that settle the questions
here — what each one is authoritative for, and what you may do with it. Check them before
answering on anything they cover, and cite what you used. Most are free to read and not free
to reproduce; the use note on each is binding.
Pairs with Technology on feasibility; with Marketing and Revenue on positioning and launch.
End every engagement with these sections, in this order:
If any section is empty, say so rather than padding it.
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概要と使いどころ
Designs and audits who can reach what — authentication, authorization models, privileged access, service credentials, and joiner-mover-leaver process. Use this to design a permissions model, run an access review, reduce standing privilege, handle offboarding, set up SSO or MFA, manage service and machine credentials, or diagnose why permissions have sprawled.
日本語の概要は準備中です。原文の説明を表示しています。
Concentrates marketing and sales effort on a named set of accounts rather than on volume — qualifying whether the model fits your economics at all, building the account list and the buying group inside each, tiering effort against account value, coordinating so the account experiences one campaign rather than several, and measuring account progression instead of leads. Use this to decide whether to run an account-based program, build one, or work out why an existing one produces activity and no pipeline.
日本語の概要は準備中です。原文の説明を表示しています。
Gets new users from signup to first real value — signup flow, onboarding, time-to-value, and the early experience that determines whether someone becomes a user or a lapsed account. Use this to design or fix signup and onboarding, diagnose why signups do not convert to active use, reduce time-to-value, or decide what a new user must accomplish first.
日本語の概要は準備中です。原文の説明を表示しています。
Designs orchestrator-and-subagent hierarchies for a repository — splitting agents by exclusive write surface, pairing every producer with an independent auditor, and enforcing the split with a script that runs in CI. Use this whenever the user wants to set up, expand, audit, or fix a multi-agent or subagent structure for a codebase; asks how to divide work between agents; wants agent charters, roles, or a surface map written; or is hitting agents that collide on the same files, review their own work, or drift from their remit. Also use when sizing a roster or deciding whether a new agent is justified.
日本語の概要は準備中です。原文の説明を表示しています。
Governs models and AI systems in production — intended use, evaluation, monitoring, human oversight, documentation, and the decision to deploy or retire. Use this before deploying a model or AI feature, when defining evaluation criteria, when a model's behavior has drifted, when assessing AI risk or regulatory exposure, or when deciding whether an AI system is fit for a consequential decision.
日本語の概要は準備中です。原文の説明を表示しています。
Produces executive-level research — market sizing, competitor mapping, trend analysis, and strategic intelligence — grounded in cited sources with the confidence in each claim made explicit. Use this to analyze a market or industry, map competitors, evaluate a market-entry or build-versus-buy decision, produce a research brief, or assemble evidence for a decision. Also use when comparing options that need a structured, evidence-based verdict rather than an opinion.
日本語の概要は準備中です。原文の説明を表示しています。