AI Agents
Made Crystal Clear
A practical, visual guide to building agents that survive real users
Everyone is being told to build agents. Almost nobody is told what an agent actually is, how its loop really works, or why the demo that dazzled on Friday falls apart the moment a real user touches it on Monday. This guide takes you from zero to an agent you can trust: the loop, tools, context and memory, guardrails, evaluation, cost, and the honest list of jobs an agent should never be given. Patterns first, frameworks second, so what you learn outlives the next SDK release.
- Pages
- 223
- Level
- Beginner to advanced
- Status
- Available
Inside the book
- 01The Agent Moment, and the Gap Nobody Mentions
- 02What an Agent Actually Is
- 03When NOT to Build an Agent
- 04Your First Agent, From Scratch
- 05Tools, the Agent's Hands
- 06Context and Memory
- 07MCP, Plugging In the World
- 08The Production Cliff
- 09Guardrails, Budgets and Stop Conditions
- 10The Trust Boundary
- 11Proving It Works: Evals
- 12Debugging a Failed Run
- 13The Money Chapter
- 14Frameworks, Multi-Agent, and What to Learn Next
You'll leave with
- Understand the agent loop: goal, context, decision, tool call, observation, stop
- Ship your first working agent, then make it fail on purpose to see why
- Tell an agent from a workflow, and know when not to build one at all
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