You've built prompts. You've engineered context windows. But when your agent hallucinates in production, drops tools mid-task, or spirals in a loop—that's not a model problem. That's a harness problem.


In this workshop, we explore harness engineering in -depth: the discipline of building the runtime infrastructure that wraps a foundation model and turns it into a reliable, production-grade agent and how the same pattern translates to physical AI.


What we'll cover:


1. What a harness refers to. We trace where the term comes from, how the industry interprets it today, and why it's the layer that actually determines whether your agent works.
2. The Components & Why They Matter. We break down the six core components (context management, tool registry, verification loops, state & memory, safety controls, and observability) and show why getting these right matters more than picking the "best" model.
3. Whiteboarding the Harness and production patterns . We map out real industry patterns(master loop, initializer-worker, handoff mesh, workflow graphs) grounded in real customer case studies.
4. The Harness Effect experiment. What happens when we hold the model fixed and change only the harness?, We'll go over this experiment and its results and will show how the execution layer alone can influence an agent's outcome, you also get to try it out
5. Physical AI: The Harness Goes Embodied. We'll cover how a robot's control loop (observe → encode → decide → act → repeat) uses the same harness pattern. We break this down into the core pillars of physical intelligence with real projects cases:
- Perception & Sequential Data: Handling multi-modal sensory inputs and managing continuous time-series state
- Robotics Foundation Model: Operating the central model to drive physical decision-making under real-world constraints.
- Simulation & Performance Evaluation: Establishing safe, rigorous testing environments to isolate and benchmark execution.


Come see what it takes to build an agent that actually works, then watch the same pattern navigate the physical world.