Free Lesson
How to Build Reliable AI Agents with Harness Engineering
30 min
Oct 21, 2026 11:00 AM
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What you'll learn
Map any agent to four engineering decisions
Prompt, context, harness and loop: what each one controls, and which to fix first when an agent fails.
See what makes an agent reliable
See how a working agent stops, uses your data, logs its work and reconciles sub-agent results.
Apply the decisions to your own agent
Map a research, operations or coding agent to the same decisions and identify what to change first.
Why this topic matters
An agent's reliability depends on the code around the model: how it selects tools, manages context, records state and checks results. This lesson uses a forecasting agent to show how a harness controls those decisions, where model judgment belongs, and how to verify the work before you accept it. Apply the same method to research, operations or coding agents.
