Writing
A place for essays and build notes about the operating habits behind good technical work.
While building this system, I saw completed results wait inside the system instead of reaching the person who asked for them. The failure came after execution. The system had treated a saved result as if someone had received it. That mistake is easy to make in agent workflows. We spend most of our design time…
I once watched an agent request move through a system exactly as designed. The ticket existed. The right service received it. The caller got an asynchronous acknowledgement. It looked like success. But the useful question was still unanswered: who was responsible for the meaning of the result? A Practical Architecture for Reliable Multi-Agent Systems starts…
Prompt engineering starts with a person telling a model what to do. That is useful. But a real task often needs more than a good first instruction. It needs an agent to work toward an outcome, check what happened, change its next move, and know when it is done. It may also need that agent…
Most people meet AI systems through prompt engineering. You give a model a task, useful context, and a clear output format. For one question, that can be enough. The design changes when the work keeps coming back. It crosses teams. It hits a bad source, a wrong tool, a missing permission, or a result that…
I’ve gotten closer to creating “agents” with Codex. It’s still early, and they aren’t bootable or portable digital coworkers, but they’re closer to something that behaves like a persistent operating system. The magic trick is Codex’s ability to create and message other threads while executing inside of a chat session. That allows us to create…