Software Developers keeping making this same mistake with AI agents, your confusing instructions with enforcement.
You create an AGENTS.md file, you tell the agent to run tests, review its code, clean things up, AND follow your engineering standards.
But... what happens when the agent skips a step?
What happens when it confidently tells you everything is working, but nobody actually verified the results?
If your quality gate is "the AI said it checked," you don't have a quality gate. This is where agentic engineering gets REALLY interesting.
Instead of hoping the model follows instructions, you can build workflows that enforce certain actions, capture results, and prevent the next step from happening until requirements are satisfied.
Another agent reviewing the work can help, but that alone isn't the same as deterministic verification.
We got into this on the latest episode of The Programming Podcast, including how tools like Atomic are approaching verifiable agent runtimes.
The real unlock isn't getting AI agents to do more work.
It's engineering systems that can verify the work they're doing.