I concur - it does not make sense to do in llm prompts what can be done in code. Code is cheaper, faster, deterministic and we have lots of experience with working with code.

Especially all bookkeeping logic should move into the symbolic layer: https://zby.github.io/commonplace/notes/scheduler-llm-separa...

How do you have "aggressive error detection" when one of the most common and pernicious mistakes agents make are architectural? The behaviour is fine, but the code is overly defensive, hiding possible bugs and invariant violations, leading to ever more layers of complexity that ultimately end up diverging when nothing can be changed without breaking something.

Sometimes it feels like Agents are just reinventing microservices. Except they are are doing it in the most inefficient way possible. It is certainly a good way for the LLM companies to sell more tokens

Own your control flow! A key point from 12 factor agents.

"One thing that I have seen in the wild quite a bit is taking the agent pattern and sprinkling it into a broader more deterministic DAG." - https://github.com/humanlayer/12-factor-agents/blob/main/REA...

This is straight outta 2023:

Agents aren't reliable; use workflows instead.

This is, at least in part, the promise of frameworks like DSPy and PydanticAI. They allow you to structure LLM calls within the broader control flow of the program, with typed inputs and outputs. That doesn’t fix non-determinism, hallucinations, etc., but it does allow you to decompose what it is you’re trying to accomplish and be very precise about when an LLM is called and why.

Totally agree. That's why i built it. https://backpac.xyz/cairn-cli

I had good success with hooks in claude code. Personally I feel this problem was common with humans as well. We added tools like husky for git commits, for our peers to push code which was linted, type checked etc.

I feel hooks are integral part of your code harness, that’s only deterministic way to control coding agents.

We've found that durable workflows is a much needed primitive for agents control flow. They give a structure for deterministic replays, observability, and, of course, fault tolerance, that operators need to make the agent loop reliable.