# PRD for OpenAI Codex — spec before the agent runs

> Give OpenAI Codex a build-ready spec: prioritized features, typed data model, and an explicit non-goals list — so it works from a scoped brief, not a guess.

Canonical: https://draftlytic.com/prd-for/openai-codex
Last updated: 2026-07-11

OpenAI Codex is an agentic coding tool: point it at a task and it can read your codebase, make changes, and run commands with real autonomy. That autonomy is only as good as the brief it starts from — a one-line prompt leaves the data model, scope, and priorities for the agent to invent, and those inventions rarely match what you had in mind.

Draftlytic turns a one-line app idea into a structured, editable spec built for exactly this kind of agentic workflow: a prioritized feature list, a typed data model, a navigation map with API endpoints, and an explicit non-goals list that tells the agent what NOT to build. Export it as Markdown to paste into a Codex session, or push it straight to the GitHub repo the agent is already working in.

## How a Draftlytic PRD fits OpenAI Codex

- Push your PRD straight to the GitHub repo where Codex operates, so the agent reads a scoped brief from source control instead of a pasted prompt.
- The sequenced implementation plan export breaks the build into ordered phases that match how an agentic tool works through tasks step by step.
- Explicit Non-Goals keep an autonomous agent from adding scope you never asked for.
- A typed data model (entities, fields, types) gives the agent concrete schema targets instead of letting it invent its own.
- The screen and API-endpoint map tells the agent which routes exist before it writes new ones.
- Per-feature acceptance criteria at Detailed depth give the agent a testable definition of done, not just a description.

## FAQ

### How do I get my Draftlytic spec into a Codex session?

Export the PRD as Markdown and paste it in as your task brief, or push it directly to a connected GitHub repo on paid tiers so the agent reads it as part of the codebase it's already working in.

### Why not just prompt Codex directly?

A short prompt leaves data model, priorities, and scope undefined, so the agent fills the gaps itself — and each guess can drift from what you meant. A structured spec with acceptance criteria and non-goals gives it concrete constraints before it touches any code.

### Does Draftlytic work for any project I'd hand to Codex?

Yes. Whether it's a web app, an API, or a CLI tool, Draftlytic's structured output — features, data model, tech stack, external services — covers the cross-stack decisions an autonomous coding agent needs to make.