December 2027
Intermediate
350 pages
1h 13m
English
Overview
For engineers who already build and deploy AI agents, the next challenge is engineering the system around the model, not just making the model more capable. Harness Engineering shows you how to treat your harness as the operational intelligence and reliability layer of your agent system, governing what the model perceives, executes, retains, and improves over time.
AI researcher and practitioner Nicole Koenigstein provides a practical methodology for turning scattered implementation details into a unified, inspectable architecture. You'll learn how to optimize operational signals to improve system resilience without altering the underlying model. Ultimately, this book offers a strategic framework for building adaptive agent systems that know what should be explicitly engineered, what to internalize, and what to let the harness learn.
- Design harness architectures for production AI agents
- Create and test modular, versioned skill artifacts
- Build a runtime context compiler for task-specific assembly
- Structure multi-agent handoffs and capture useful traces
- Optimize cost and latency through tracing, pruning, and retry discipline
- Govern adaptive harnesses with permissions, identity boundaries, audit trails, and human oversight
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