Developers are treating multi-agent LLM systems like casual chat threads, leading to context loss and "hallucinations." This is an architectural flaw that can be addressed by implementing a formal state transition protocol, such as the Handoff Payload Pattern. This pattern structures context into a formal payload, maximizing signal-to-noise ratio, reducing algorithmic complexity, and enforcing design by contract between agents. A rigorous template for this payload is provided, outlining execution targets, state invariants, immutable interface contracts, negative constraints, and deterministic acceptance criteria for agentic pipelines. AI
IMPACT Formalizes LLM agent communication, potentially reducing hallucinations and improving efficiency in complex AI systems.
RANK_REASON The item describes a novel architectural pattern and protocol for LLM systems, supported by computer science theory. [lever_c_demoted from research: ic=1 ai=1.0]
- domain driven design
- Handoff Payload Pattern
- hexagonal architecture
- Model Context Protocol
- Slack
- transformer
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