I've been building autonomous agents and noticed a recurring failure mode: as business logic becomes more complex, even the most capable LLMs struggle to maintain consistency. I realized the problem isn't just the "brain" (the agent), but the lack of a structured "world" for it to inhabit.
Most current frameworks are Agent-Centric, forcing the agent to manage its own state, memory, and environmental rules all at once. This post explores a shift toward World-Centric Orchestration, where we prioritize the environment's state and rules first.
In this piece, I discuss:
- The Decoupling of Agency and Environment: Why the agent should be an "actor" within a world that enforces its own constraints.
- State-Driven Reliability: Using state machines to define valid action spaces, reducing the hallucination surface.
- Pheromone-Inspired Memory: A rough approach to managing long-term context using weighted relationship graphs and lexical indexing.
The "Mind Protocol" is my attempt to formalize this architecture. I'm curious to hear from others who are moving away from simple "loop-and-prompt" patterns—how are you handling state consistency and world-building for your agents?
I'd love to hear your critiques and thoughts on this approach.
I've been building autonomous agents and noticed a recurring failure mode: as business logic becomes more complex, even the most capable LLMs struggle to maintain consistency. I realized the problem isn't just the "brain" (the agent), but the lack of a structured "world" for it to inhabit.
Most current frameworks are Agent-Centric, forcing the agent to manage its own state, memory, and environmental rules all at once. This post explores a shift toward World-Centric Orchestration, where we prioritize the environment's state and rules first.
In this piece, I discuss:
- The Decoupling of Agency and Environment: Why the agent should be an "actor" within a world that enforces its own constraints.
- State-Driven Reliability: Using state machines to define valid action spaces, reducing the hallucination surface.
- Pheromone-Inspired Memory: A rough approach to managing long-term context using weighted relationship graphs and lexical indexing.
The "Mind Protocol" is my attempt to formalize this architecture. I'm curious to hear from others who are moving away from simple "loop-and-prompt" patterns—how are you handling state consistency and world-building for your agents?
I'd love to hear your critiques and thoughts on this approach.