AI agents are moving beyond prompt-response into long-horizon, tool-using autonomy — but the model alone isn't production-ready. The agentic harness is the orchestration and governance layer that wraps an LLM agent to provide what it can't on its own: reliability, safety, observability, memory, and human oversight.


The harness concept is emerging simultaneously across industry (AgentCore, LangGraph, CrewAI, AutoGen) and research (Reflexion, Constitutional AI, ToolEmu, TrustAgent), but these communities aren't yet talking to each other. This workshop bridges that gap and explores the harness as a framework-agnostic architectural pattern, examining its core components and the open research problems in each.




Session (30m each)


Topic


Description


1


The Agentic Harness Pattern


Why agents fail in production. Six core components, real-world use cases, and clarifying harness vs. scaffolding vs. orchestrator vs. framework.


2


Guardrails & Safety


Red-team evaluation of guardrail implementations. Domain-specific constitutional safety case study (SafeLab): multi-agent debate + Reflexion vs. generic filtering.


3


Memory & Observability


Comparing memory architectures (in-context, RAG, vector store, hybrid). OpenTelemetry-based tracing for non-deterministic agent systems.


4


Live Demo


SafeLab live — attendees submit proposals, watch multi-agent safety debate in real time.


5


Panel Discussion


Is harness engineering a new discipline? Build vs. buy. Framework portability. What gets commoditized as models improve?


6


Open Q&A & Wrap-up


Audience discussion, open research priorities, collaboration opportunities.