@Codex_jisen: For anyone who feels anxious every time they make a change after building an app with Codex, wondering "Is it safe to touch this?" — OpenAI has published real-world examples of using Codex for app maintenance. For instance, code that appears to be unused. Rather than deleting it outright, it follows ① F…
Summary
OpenAI has published examples of using Codex for app maintenance. The workflow uses AI to detect candidates for unused code, verify them against actual runtime data, and generate small, incremental fix proposals — with humans handling the final review.
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Cached at: 10/19/26, 01:17 AM
For those who built an app with Codex but now feel anxious every time they make a change — “Is it safe to touch this?”
OpenAI has published a case study on using Codex for app maintenance.
For example, when there’s code that appears to be unused:
Instead of deleting it right away, we proceed in this order:
- Look for spots that may be unnecessary
- Back it up with evidence from actual runtime logs and other data
- Propose small, broken-down changes
Even if code normally seems to do nothing, there are processes that become necessary during incidents — so humans should do the final check.
If you’ve just left your AI-built app sitting untouched, start by asking: “Point out one area that could be improved, with evidence” 👇
Rodrigo Roim (@rrroim): Software maintenance is changing. A few months ago, I had to tell Codex exactly where to look for dead code. Now it can find candidates in Slack, check them against production telemetry, and draft cleanup PRs. Here’s how we do this at OpenAI.
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