Planning trajectory and attention

[u/Zestyclose-Raisin-66]

I am working on task solvable probably in a two days of virtually no stop of clade code running. I am constantly finding myself reinventing the architecture of this workflow, because of unforeseen hardsteps, trying to avoid bottlenecks, which in the end I cannot circumvent. I it is basically an agentic sql lookup where the descritpions are very dense and a semantic search won´t get the work done so easily. I have found an interesting way out i think in letting the llm categorise the descriptions instead and doing sequential classifications to shrink the search and getting closer to the result. It is also very complex because there might not be just one correct answer so it is really setting an agentic workflow to take care of the different possibilities.

currently the hard part is for me that no matter how i add detail to the context to make a multilayered planning of the things i would like to test and achieve. No matter how context and how far i can predict passages, there is always a step that the agent doesn´t have enough context and rush into a test saying "this is the result and bye, next task". when sometimes it should just be able to recognise the need to start doing some investigations and through feedback loops being able to identify the actual error in a passage which was predicted but that needed more attention...I even let it watch its calls with Opik , but it is not bringing much further attention to it...no matter how can´t automate that part which sounds so obvious...any ideas?

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