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Intermediate · 30-50 min
OpenAI Codex API agent loop for implementation tasks
A repeatable API-driven loop to plan, implement, validate, and summarize coding tasks using Codex and GPT models.
Last reviewed Feb 25, 2026
Objective
Use API calls to run a structured coding loop with explicit validation gates.
Loop design
Stage A: Plan
Prompt for:
- impacted modules
- implementation sequence
- test commands
- expected failure modes
Stage B: Implement
Apply only one logical change per pass:
- write patch
- run test command
- capture output
Stage C: Verify
Require the model to explain:
- what code path was exercised
- what remains unverified
- any assumptions still unresolved
Stage D: Summarize
Output machine-readable notes:
- files changed
- behavior changes
- evidence from test output
Why this works
- keeps code generation bounded
- makes failures visible early
- improves review quality for humans
Suggested safeguards
- fail closed on missing tests
- reject edits that exceed scope constraints
- persist run logs with timestamps