AI-Native MVP Stage
Goal
Help founders ship the smallest product that proves the core customer outcome while keeping AI-generated work testable, secure, and maintainable.
Required Inputs
If the founder provides a structured brief, use these inputs:
Validated customer/problem:
MVP outcome to prove:
Current product status:
Technical stack:
Data/security constraints:
Available builders/tools:
Deadline:
Desired output:
Guided Intake
Do not require the founder to know all implementation details upfront. If the request is thin, ask up to five questions first:
1. What customer problem and user outcome has already been validated?
2. What is the smallest workflow the MVP must prove?
3. What exists today: mockup, prototype, manual workflow, or no product?
4. What technical or data constraints matter most?
5. What do you want next: MVP scope, architecture, coding-agent task plan, eval plan, or milestones?
After the user answers, infer reasonable defaults, mark unknowns explicitly, and produce a build recommendation. Do not block on stack details unless the requested output is technical architecture.
Workflow
- Define the MVP proof target: the user outcome that must become measurably easier, faster, cheaper, or better.
- Cut scope to the smallest workflow that proves that target.
- Use
references/mvp-scope.md to separate must-have proof from distracting surface area.
- Use
references/technical-architecture.md for architecture, coding-agent guardrails, security, and technical debt prevention.
- Use
references/evals-and-feedback.md to define evaluation, telemetry, bug intake, and customer feedback loops.
- Return a build plan with milestones, risks, evals, and acceptance criteria.
AI-Native Workflows
Use generic AI roles:
- Coding agent: implement bounded tasks with tests and explicit file ownership.
- Architecture critic: review data flow, security, and maintainability.
- Evaluation assistant: create test cases, golden examples, and failure taxonomies.
- User-research assistant: convert feedback into product decisions.
Exit Criteria
The MVP stage is complete when:
- the core workflow works for real users;
- the product has enough instrumentation to learn;
- the team can distinguish product issues from AI quality issues;
- critical data and security risks are controlled;
- the next launch audience is clear.
Common Failure Modes
- Building a broad product instead of proving one workflow.
- Letting coding agents create unreviewed architecture.
- Shipping AI behavior without evals or regression checks.
- Ignoring data permissions, privacy, and failure recovery.
- Treating demo quality as customer value.
Recommended Outputs
Return the most useful artifact for the request:
- MVP scope brief;
- technical architecture review;
- coding-agent task plan;
- eval and feedback plan;
- milestone roadmap.
1---2name: ai-native-mvp-stage3description: Scope and plan an AI-native MVP after the problem and customer are credible. Use when a founder needs MVP scope, product architecture, coding-agent workflow, evaluation loops, technical debt control, security review, build milestones, or a practical plan for shipping the first useful version.4---56# AI-Native MVP Stage78## Goal910Help founders ship the smallest product that proves the core customer outcome while keeping AI-generated work testable, secure, and maintainable.1112## Required Inputs1314If the founder provides a structured brief, use these inputs:1516```text17Validated customer/problem:18MVP outcome to prove:19Current product status:20Technical stack:21Data/security constraints:22Available builders/tools:23Deadline:24Desired output:25```2627## Guided Intake2829Do not require the founder to know all implementation details upfront. If the request is thin, ask up to five questions first:3031```text321. What customer problem and user outcome has already been validated?332. What is the smallest workflow the MVP must prove?343. What exists today: mockup, prototype, manual workflow, or no product?354. What technical or data constraints matter most?365. What do you want next: MVP scope, architecture, coding-agent task plan, eval plan, or milestones?37```3839After the user answers, infer reasonable defaults, mark unknowns explicitly, and produce a build recommendation. Do not block on stack details unless the requested output is technical architecture.4041## Workflow42431. Define the MVP proof target: the user outcome that must become measurably easier, faster, cheaper, or better.442. Cut scope to the smallest workflow that proves that target.453. Use `references/mvp-scope.md` to separate must-have proof from distracting surface area.464. Use `references/technical-architecture.md` for architecture, coding-agent guardrails, security, and technical debt prevention.475. Use `references/evals-and-feedback.md` to define evaluation, telemetry, bug intake, and customer feedback loops.486. Return a build plan with milestones, risks, evals, and acceptance criteria.4950## AI-Native Workflows5152Use generic AI roles:5354- Coding agent: implement bounded tasks with tests and explicit file ownership.55- Architecture critic: review data flow, security, and maintainability.56- Evaluation assistant: create test cases, golden examples, and failure taxonomies.57- User-research assistant: convert feedback into product decisions.5859## Exit Criteria6061The MVP stage is complete when:6263- the core workflow works for real users;64- the product has enough instrumentation to learn;65- the team can distinguish product issues from AI quality issues;66- critical data and security risks are controlled;67- the next launch audience is clear.6869## Common Failure Modes7071- Building a broad product instead of proving one workflow.72- Letting coding agents create unreviewed architecture.73- Shipping AI behavior without evals or regression checks.74- Ignoring data permissions, privacy, and failure recovery.75- Treating demo quality as customer value.7677## Recommended Outputs7879Return the most useful artifact for the request:8081- MVP scope brief;82- technical architecture review;83- coding-agent task plan;84- eval and feedback plan;85- milestone roadmap.
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