The Model Didn’t Get Dumber. My Agent Skills Got Stale.
When Claude Opus 5 and GPT-5.6 arrived, I expected my coding agents to become noticeably better. Instead, some of my workflows felt worse. The agents seemed more eager, less predictable, and occasionally “dumber” than before. Naturally, I blamed the new models. Very scientific of me. Maybe it was a skill issue Then I watched Andrej Karpathy’s interview on the No Priors podcast. One idea stuck with me: when an agent fails, the capability may already exist. The problem could be how we instruct it, what memory we provide, or how we arrange the workflow. That made me question something I had mostly ignored: Were my custom skills still compatible with the newer models? I gave my agent this prompt: Can you audit our custom skills against the current models? Flag stale prompts, conflicting instructions, outdated assumptions, and anything that should be simplified or removed. Then test each skill on a representative task and propose the smallest updates needed. The audit found instructions written around the behavior of older models. Some were redundant. Some were no longer necessary. Others pushed the newer models too hard and caused them to overdo tasks. After cleaning those up and testing the skills again, the results felt noticeably better. The official guidance supports this This was not proof that every disappointing result is caused by an outdated prompt. Models can still regress, behave inconsistently, or introduce genuine breaking changes. But both Anthropic and OpenAI recommend recalibrating instructions during model migrations. Anthropic’s Claude Opus 5 documentation says the model now verifies its work without being told. It specifically recommends removing verification instructions carried over from earlier models because they can cause over-verification. OpenAI’s GPT-5.6 guidance recommends removing repeated instructions, simplifying tool descriptions, and running the same evaluations after each change. In OpenAI’s internal coding-agent evaluations, leaner sys