A collection of 3 posts about codex.
I built Daytripper and RepoFinder entirely with OpenAI Codex, then turned my Claude Code tooling loose on the results. The QA and design findings are numbered in the git history, one regression test cites the report that found the bug, and both products came out better than either agent would have produced alone.
RepoFinder turns a project and a goal into a short list of open source tools that genuinely fit, then lets you interrogate every pick. Built entirely with OpenAI Codex on the Responses API: gpt-5.6-luna for extraction, gpt-5.6-terra for ranking and chat, strict JSON Schema outputs, a labeled fallback, a remote MCP tool, and 15 checked-in lessons on how Codex actually works.
I learn AI coding agents by shipping with them. Daytripper is the first app I built to learn OpenAI Codex: a travel planner built in one overnight session, deliberately zero LLM calls at runtime, with tests covering all 1,296 possible preference combinations, deployed to Cloudflare Workers. Here is what the build taught me about how Codex actually works in August 2026.