sample-aidlc-discovery

In the author's own words, from each skill's SKILL.md.

• aidlc-discovery

  Runs an AI-DLC Discovery workshop end to end in five phases (Signals, Working Backwards, Prototype, Validate, Handoff), from customer feedback to a Discovery brief the team builds from. Use when the user wants to start or continue a Discovery workshop, decide what to build from customer feedback, or asks where they are in the workshop. Calls one Discovery skill per job and stops at each checkpoin…

  skills/aidlc-discovery/SKILL.md on GitHub (opens in a new tab)

• discovery-gtm

  Go-to-market section for AI-DLC Discovery: drafts first adopters, positioning, business model, and launch plan in Working Backwards, then completes the viability check and the adoption and success table in Validate. Use when the user asks who adopts first, how to position the idea, how adoption will be measured, or wants the GTM or adoption plan.

  skills/discovery-gtm/SKILL.md on GitHub (opens in a new tab)

• discovery-handoff

  Handoff phase of AI-DLC Discovery: checks every required artifact exists, then writes the Discovery brief, the single document the team builds from, into the team's repository, with the personas for AI-DLC and the command that starts AI-DLC Inception from the brief. Use when the user wants the Discovery brief, to hand off to engineering, AAP, or AI-DLC, or to finish a Discovery workshop.

  skills/discovery-handoff/SKILL.md on GitHub (opens in a new tab)

• discovery-personas

  Synthetic personas for AI-DLC Discovery: generates personas from customer feedback or Signal Briefs, runs the persona critique of a prototype at the end of Prototype, and lets the team talk to a persona or run a persona panel. Use when the user wants to create personas, hear how a persona would react to an idea or prototype, run a persona critique, or hold a panel discussion.

  skills/discovery-personas/SKILL.md on GitHub (opens in a new tab)

• discovery-prototype

  Prototype phase of AI-DLC Discovery: builds a polished, clickable prototype of the core user flow, with several screens shown on a phone and in a desktop browser, in one self-contained HTML file, aimed at the riskiest assumption, then gets the persona critique and iterates with the team. Use when the user wants to build, change, or share a prototype, mockup, or click-dummy for a Discovery use cas…

  skills/discovery-prototype/SKILL.md on GitHub (opens in a new tab)

• discovery-signal-brief

  Writes Signal Briefs for an AI-DLC Discovery workshop: one-page, anonymized summaries of one customer problem each, created by the team from its own data inside its own environment, so raw data never leaves it. Use before a Discovery workshop when the team cannot bring raw customer data, or when asked to write, check, or anonymize a Signal Brief.

  skills/discovery-signal-brief/SKILL.md on GitHub (opens in a new tab)

• discovery-signals

  Signals phase of AI-DLC Discovery: turns customer feedback, Signal Briefs, or a synthetic dataset into a Signal Analysis Report and testable hypotheses, after the team writes down what it expects to find. Use when the user wants to analyze customer feedback or VoC data, combine Signal Briefs, find the top customer problems with evidence, or start the Signals phase of a Discovery workshop.

  skills/discovery-signals/SKILL.md on GitHub (opens in a new tab)

• discovery-survey

  Follow-up surveys for AI-DLC Discovery: turns the open hypotheses from Validate into a short survey for real users, as an HTML form and as questions ready to paste into Microsoft Forms or Google Forms, then builds a results dashboard from the responses and updates each hypothesis's verdict. Use after a Discovery workshop to test open hypotheses or the prototype with real users.

  skills/discovery-survey/SKILL.md on GitHub (opens in a new tab)

• discovery-team-space

  Saves an AI-DLC Discovery workshop in an Amazon Quick team Space instead of a local folder, so several people can follow, open, and take over the same workshop from their own Amazon Quick Desktop. Amazon Quick only, and optional: without a Space the workshop runs from a local folder as usual. Use when the team wants to share the workshop in a Space, take over from another facilitator, or run pods…

  skills/discovery-team-space/SKILL.md on GitHub (opens in a new tab)

• discovery-use-case-scoring

  Use case scoring for AI-DLC Discovery: ranks 3 to 5 candidate use cases, written as problems, with a gate, six weighted dimensions, a confidence rating, and a decision (build first, prototype to learn, defer, drop), then helps the team select what to take forward. Also re-scores after Validate. Use when the user wants to prioritize or score use cases, decide which problem to work on first, or rev…

  skills/discovery-use-case-scoring/SKILL.md on GitHub (opens in a new tab)

• discovery-validate

  Validate phase of AI-DLC Discovery: challenges the selected use case on the day against four risks (valuable, usable, feasible, viable), runs a pre-mortem, sets testable success criteria, prioritizes the customer problems with the hypotheses still open, and records the team's decision: commit, pivot, or park. Use when the user wants to validate a concept, challenge assumptions, run a pre-mortem,…

  skills/discovery-validate/SKILL.md on GitHub (opens in a new tab)

• discovery-working-backwards

  Working Backwards for AI-DLC Discovery: runs the five Working Backwards questions with the team, then writes the PR/FAQ, a readiness check, the PRD, and the riskiest assumption for a selected use case. Use when the user wants to write or challenge a PR/FAQ or press release, write a PRD, run Working Backwards, or name what the prototype must prove.

  skills/discovery-working-backwards/SKILL.md on GitHub (opens in a new tab)

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