ai-agent-book

Discover how incomplete context leads to AI agent hallucinations, KV-Cache invalidation, and unreliable decisions. Learn about 6 critical architectural failures.

Understand the Correction function in the Harness architecture. It validates LLM actions, applies fallbacks, and logs adjustments for diagnostics. Learn how it ensures reliable agent behavior.

Discover verification's crucial role in the AI agent harness layer. It ensures safe tool calls, validates results, and provides auditable evidence for reliable workflows.

Discover the Constraint function in Harness Engineering. Learn how it transforms business rules into enforceable logic for feasibility checks, safety gates, and agent validation. Understand its purpose and code implementation.

Understand the distinct roles of Agents and Environments in the Instagit framework. Agents make decisions, Environments provide context and data for execution.

Understand how skill documents differ from tool descriptions in AI agents. Learn about natural-language workflows and structured JSON-Schema metadata for agent capabilities.

Discover ACI principles for tool design. Learn how to treat tool APIs as agent interfaces with capability expression, tool description, and parameter passing for better AI agent integration.

Discover how context dictates AI agent decision-making. Explore the bojieli ai-agent-book repository for insights into how information quantity and quality set agent capabilities.

Understand the five essential components of LLM API calls for agents: System Prompt, Tool Definitions, User Messages, Assistant Messages, and Tool Results. Learn how they enable multi-turn reasoning.

Explore the five stages of AI application engineering evolution: Prompt, Context, Harness, Loop, and Graph Engineering. Understand the journey from static prompts to autonomous systems.

Discover how harness engineering provides a competitive advantage for AI agent systems. Learn how it transforms LLMs into production-ready agents with context management, tool interfaces, and safety.

Discover the stable prefix role in a ReAct loop. Learn how this constant prompt element enhances efficiency, cuts costs, and secures your AI agent by enabling prefix caching.