OpenAI’s Codex flags AI work logs for deviations from user requests
OpenAI’s Codex tool can compare AI-generated work logs against user instructions to spot discrepancies. In a test, Codex identified an AI’s fictional log that included unverified claims—like ‘double the storage capacity’—and a suggestion to log into social media, even though the original request prohibited publication. The tool distinguished between suggestions and executed actions but could not…
Key points
- OpenAI’s Codex tool compares AI work logs to user requests, flagging deviations like added claims or unauthorized actions
- Test found Codex could not confirm whether AI published content or met all constraints (e.g., character limits, price)
- Cisco’s Project Quarry (alpha) audits AI workflows but requires Python and manual rule configuration
The demo follows Cisco’s Project Quarry, an alpha-stage framework for developers to audit AI workflows. Quarry checks sequences of operations against predefined rules but requires Python and manual rule-setting. While Codex demonstrated the concept without full Quarry integration, the author notes this is not a test of Quarry’s performance or a real-world audit. All figures are based on fictional inputs and Codex’s output.
Comparing AI work logs against requests using OpenAI's 'Codex'
note.com · 2 November 2026
Loading the full article…
This text was published by note.com and written by とにかく楽してAI化. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗
The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.
More in Agents & Tools
All →- Convoso makes no-code Voice AI Agent generally available · 1 src
- Soniox STT v6 adds agent text input and echo filtering for voice agents · 1 src
- Scikit-LLM tutorial shows LLM summarization in scikit-learn pipelines using Groq free tier · 1 src
- Are Skills from Claude Code Becoming a Shared Asset for AI? · 1 src
- Anthropic adds message threads to Claude Platform for faster agent responses · 3 src
Comments
via GitHub Discussions