Strongly agree on the 'Toy App' ceiling with current DAG-based frameworks. I've been wrestling with LangGraph for similar reasons—once the happy path breaks, the graph essentially halts or loops indefinitely because the error handling is too rigid.
The concept of mapping 'exceptions as observations' rather than failures is the right mental shift for production.
Question on the 'Homeostasis' metric: Does the agent persist this 'stress' state across sessions? i.e., if an agent fails a specific invoice type 5 times on Monday, does it start Tuesday with a higher verification threshold (or 'High Conscientiousness') for that specific task type? Or is it reset per run?
Starred the repo, excited to dig into the OODA implementation.
The concept of mapping 'exceptions as observations' rather than failures is the right mental shift for production.
Question on the 'Homeostasis' metric: Does the agent persist this 'stress' state across sessions? i.e., if an agent fails a specific invoice type 5 times on Monday, does it start Tuesday with a higher verification threshold (or 'High Conscientiousness') for that specific task type? Or is it reset per run?
Starred the repo, excited to dig into the OODA implementation.