this post was submitted on 22 Aug 2026
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Maybe it's just because Anthropic is so many more miles ahead than OpenAI, but I have not had the "it doesn't work" experience that people are talking about here. I've set up agentic pipelines with code architecture guidelines, the orchestrator calls the implementer, tester, reviewer when needed. If the developed code isn't up to standard or the work item isn't fully captured, it'll reject it and send it back to implementation. It invokes the architect if it runs into something unanticipated. The pipeline can run a feature with high accuracy and very little input.
I've even used it to run batteries of frozen experiments on self synthesized data using its own simulation harnesses to discover novel techniques that work in the real world. If it isn't helpful, I feel like you are doing it wrong.
Pretty much my experience and I didn't even have to do workflows or complex harnesses, I wrote a "dont ask" mode wrapper that gives rights to read/write a work dir & explanation that blockers & questions need to be written in a specific directory, and I listen to this directory with a GUI app that notifies me, then also a stop hook that verifies that that doc is updated when it stops, and has all the items done/blocked.
I did this cause I like the flexibility of a normal agentic chat session.
Recent LLM are smart enough to resolve many problems as is in agentic mode. Really strange to see "it doesnt work" copium instead of fighting for the means of production and looking for a way to have this setup purely local.