# Ai Native Mvp Stage

> 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.

- **Type:** Skill
- **Install:** `agentstack add skill-hades-hy-li-ai-native-founder-playbook-skills-ai-native-mvp-stage`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [Hades-HY-LI](https://agentstack.voostack.com/s/hades-hy-li)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [Hades-HY-LI](https://github.com/Hades-HY-LI)
- **Source:** https://github.com/Hades-HY-LI/ai-native-founder-playbook-skills/tree/main/skills/ai-native-mvp-stage

## Install

```sh
agentstack add skill-hades-hy-li-ai-native-founder-playbook-skills-ai-native-mvp-stage
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# 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:

```text
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:

```text
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

1. Define the MVP proof target: the user outcome that must become measurably easier, faster, cheaper, or better.
2. Cut scope to the smallest workflow that proves that target.
3. Use `references/mvp-scope.md` to separate must-have proof from distracting surface area.
4. Use `references/technical-architecture.md` for architecture, coding-agent guardrails, security, and technical debt prevention.
5. Use `references/evals-and-feedback.md` to define evaluation, telemetry, bug intake, and customer feedback loops.
6. 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.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [Hades-HY-LI](https://github.com/Hades-HY-LI)
- **Source:** [Hades-HY-LI/ai-native-founder-playbook-skills](https://github.com/Hades-HY-LI/ai-native-founder-playbook-skills)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-hades-hy-li-ai-native-founder-playbook-skills-ai-native-mvp-stage
- Seller: https://agentstack.voostack.com/s/hades-hy-li
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.