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Any ideas how to solve the agent's don't have total common sense problem? I have found when using agents to verify agents, that the agent might observe somethi

• atarus 7mo ago
  To clarify you are using the "fast brain, slow brain" pattern? Maybe an example would help. Broadly speaking, we see people experiment with this architecture a lot often with a great deal of success. A few other approaches would be an agent orchestrator architecture with an intent recognition agent which routes to different sub-agents. Obviously there are endless cases possible in production and best approach is to build your evals using that data.
• rush86999 7mo ago
  Only solution is to train the issue for the next time. Architecturally focusing on Episodic memory with feedback system. This training is retrieved next time when something similar happens
  • atarus 7mo ago
    Training is an overkill at this point imo. I have seen agents work quite well with a feedback loop, some tools and prompt optimisation. Are you doing fine-tuning on the models when you say training?
    • rush86999 7mo ago
      Nope - just use memory layer with model routing system. https://github.com/rush86999/atom/blob/main/docs/EPISODIC_MEMORY_IMPLEMENTATION.md https://github.com/rush86999/atom/blob/main/docs/EPISODIC_ME...
      • atarus 7mo ago
        Memory is usually slow and haven't seen many voice agents atleast leverage it. Are you building in text modality or audio as well?