AI Coding
Vibe coding requirements to tasks
A practical vibe coding requirements workflow for turning rough ideas into task breakdowns, acceptance criteria, constraints, non-goals, and implementation-ready AI prompts.
Opening summary
Vibe coding works better when the first prompt is not the first draft of the app. The best starting point is a small requirements workflow that turns a rough idea into tasks, constraints, non-goals, and acceptance criteria before any code changes happen.
This guide shows how to convert an idea into an implementation-ready task breakdown. Use it when you want an AI coding agent to build with less guessing, fewer surprise features, and a clearer definition of done.
Who this guide is for
- Founders who have a product idea but need a clear first build scope
- Developers using AI coding agents to break features into reviewable tasks
- Product managers turning discovery notes into implementation prompts
- Designers handing off AI-generated product concepts to engineering
- Teams that want vibe coding to move fast without skipping requirements
Step-by-step workflow
- Start with the user, outcome, and real problem before naming features.
- Write the smallest workflow that proves the idea.
- List what is explicitly out of scope so the AI does not overbuild.
- Define constraints: framework, existing components, data source, device support, auth, SEO, and performance expectations.
- Convert the workflow into tasks that can be implemented and reviewed one by one.
- Add acceptance criteria for each task, including edge cases and failure states.
- Ask the AI to identify ambiguity before it edits files.
- Prioritize tasks by dependency: data shape, route, UI, action, validation, verification.
- Turn the task list into a prompt that includes the stopping point.
- Review the first diff against the original scope before expanding the feature.
Recommended tools
Common mistakes
- Asking the AI to build from a vague product sentence
- Starting with UI polish before the user workflow is clear
- Forgetting non-goals, which invites the AI to add extra routes and features
- Writing tasks that are too large to review
- Omitting acceptance criteria and then judging output by taste
- Letting the AI choose architecture without checking existing project patterns
- Expanding scope after the first working screen instead of finishing verification
Practical example
Weak prompt: build a client portal with AI.
Better prompt: turn this into implementation tasks for a client portal where a freelancer can share project updates with one client. First version includes a dashboard route, static project cards, a project detail page, and an empty state. Do not add billing, file upload, team accounts, notifications, or real database writes. Define data shape, route structure, UI states, acceptance criteria, and verification before coding.
The better prompt gives the AI a user, outcome, scope, non-goals, constraints, acceptance criteria, and a clear first vertical slice.
FAQ
Q: How detailed should requirements be before vibe coding? A: Detailed enough to define the user, outcome, scope, non-goals, constraints, acceptance criteria, and verification. Do not write a full product spec before every small task.
Q: Should the AI ask clarifying questions first? A: Yes when scope, data, auth, payment, privacy, or user roles are unclear. A short clarification step is cheaper than rewriting generated code.
Q: What is the best task size? A: A good task can be reviewed in one diff and verified with one test or manual path. If a task touches unrelated systems, split it.
Q: Can non-technical users use this workflow? A: Yes. Keep the first task small, avoid sensitive data, and require manual verification after each generated change.