Codex Workflow For Full-Stack Operators

A strong Codex workflow uses one operating doc, tight per-task specs, and a hard review gate. Codex spans terminal, IDE, and web, and can run tasks in parallel cloud environments, so the temptation is to launch a dozen jobs and merge whatever comes back. Resist that. Parallelize implementation, centralize judgment: scope each task narrowly, read each diff, and let acceptance criteria — not the agent — decide what is done.

Codex is built for delegation. Cloud tasks and parallel worktrees mean implementation is no longer the constraint. But when implementation gets cheap, the real constraints move upstream to scope and downstream to review. The operators who win with Codex are not the ones who launch the most tasks. They are the ones whose tasks were specified well enough to be reviewable.

1. 01

   Set the operating context once

   Keep an AGENTS.md at the repo root so every Codex surface — terminal, IDE, and cloud task — starts from the same product context, stack rules, and verification commands.

2. 02

   Write the task as a spec, not a wish

   Each task gets a concrete goal, acceptance criteria, and explicit non-goals. A vague task run in a cloud environment is a confidently wrong diff you have to unwind.

3. 03

   Delegate in parallel, deliberately

   Run independent tasks concurrently when they do not touch the same seams. Keep tasks that share files or data contracts sequential so parallel diffs do not collide.

4. 04

   Review every diff before you apply it

   Use auto-review to catch obvious issues, then do the real review yourself: unrequested changes, fake data, missing states, and whether it actually meets the acceptance criteria.

5. 05

   Verify and integrate at the seams

   Run typecheck, lint, build, and browser plus mobile QA. Pay special attention to where parallel work meets — shared types, routes, and data contracts are where merged agent work breaks.

• Unified surfaces: the same execution model across terminal, IDE, and web, so you can move a task between contexts.
• Cloud tasks and worktrees: parallel work on isolated copies, useful for fanning out independent slices.
• Auto-review and MCP: a built-in first-pass review and connections to your tools and data.
• A strong agentic base model, which raises the floor on implementation but not on your scope or QA.

Before you launch a Codex task, especially a cloud one you will not be watching, write it down at this level. It takes two minutes and saves an hour of unwinding.

# Task: add CSV export to the reports table

## Goal
Let a signed-in user export the current filtered reports view as CSV.

## Acceptance criteria
- Export button on /reports respects active filters
- CSV columns match the visible table columns and order
- Empty result exports headers only, no crash
- Loading and error states handled

## Non-goals
- No background jobs or emailed exports
- No new dependencies; use existing utils

## Verify
- npm run typecheck && npm run lint && npm run build
- Manually export filtered and empty views

• Launching cloud tasks with no spec, then merging confidently wrong diffs.
• Treating auto-review as QA and skipping your own acceptance check.
• Parallelizing tasks that share files, so the diffs collide at the seams.
• No operating doc, so each surface and task interprets the project differently.
• Optimizing for tasks launched instead of slices shipped and verified.

The operating loop here is the same one in Claude Code Workflow For Building Real Software — only the delegation surface changes. If you are still choosing tools, read Cursor vs Claude Code vs Codex For Real Projects. To get the AGENTS.md, spec, and QA templates this workflow runs on, get the Operator Kit, then learn the full Spec-to-System method in the course.