An agent wrote a change. It passed review, it passed CI, and then it took a production path down for about three hours. Nothing in the diff was wrong on its own, which is exactly why it got through, and the failure only existed in the combination of the edits. I have been shipping AI-generated code to production since I was fourteen, and this incident changed how I work more than anything else has. It took far longer to diagnose than an equivalent bug I would have written myself, and the reason was not the code. It was that I could not ask the author what they had intended, and none of the reasoning behind the change existed anywhere. Commit message, pull request, ticket: nothing. This talk is that incident, and then the three checks I have run ever since. Keeping a change small enough that reverting it is genuinely one step, rather than a careful unwind at three in the morning. Actually testing that the revert works instead of assuming it will. And moving the policy check to before an action executes rather than alerting after it has already landed. I will be honest about what each one costs in shipping speed, because none of them are free. Tool-agnostic, no live demo, nothing to install. If you are handing more of your pipeline to agents this quarter, this is the failure mode I wish someone had described to me first.
Artemis Leonardou is a software engineer and DevRel at NOFire AI. She has been building since she was 14 and now ships AI-generated code to production as a matter of routine, which is where most of what she talks about comes from. She was selected among the top 2000 global CS talents for Y Combinator's AI Startup School, has won first place in three hackathons, and her technical content has crossed 2 million views as Artemis Codes. She has spoken at React Summit and TechBiz, speaks at DevConf.US in September 2026, and leads a hands-on workshop at Open Conf in November. She is 19 and still a full-time student.
