{
"item_title" : "AI Agents from Scratch",
"item_author" : [" Ray Wilder "],
"item_description" : "A systematic, self-contained guide to LLM-powered AI agents, ordered the way the field should be learned: theory first, then core capabilities one at a time, then a from-scratch build, then production concerns. You will learn what separates a workflow from an agent (and when each wins), the ReAct reasoning-and-acting loop every modern agent descends from, how tool calling actually works on the wire, planning and self-correction (Tree of Thoughts, Reflexion), short- and long-term memory including why naive RAG often fails, multi-agent orchestration with honest cost math, and production evaluation, observability, and guardrails. The centerpiece is a weekend project: a complete minimal agent in pure Python, no frameworks, followed by a failure-mode lab where you break it on purpose: infinite loops, hallucinated tool calls, context bloat, and error compounding. Every code listing runs offline and is under a hundred lines. Distilled from the field's primary sources, including the research canon (ReAct, Tree of Thoughts, Reflexion, Generative Agents) and production engineering accounts, and closed by a history of the field, a glossary, and a full bibliography. No survey filler. No framework dependency. Just the mechanics every agent is built from.",
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Overview
A systematic, self-contained guide to LLM-powered AI agents, ordered the way the field should be learned: theory first, then core capabilities one at a time, then a from-scratch build, then production concerns.
You will learn what separates a workflow from an agent (and when each wins), the ReAct reasoning-and-acting loop every modern agent descends from, how tool calling actually works on the wire, planning and self-correction (Tree of Thoughts, Reflexion), short- and long-term memory including why naive RAG often fails, multi-agent orchestration with honest cost math, and production evaluation, observability, and guardrails. The centerpiece is a weekend project: a complete minimal agent in pure Python, no frameworks, followed by a failure-mode lab where you break it on purpose: infinite loops, hallucinated tool calls, context bloat, and error compounding. Every code listing runs offline and is under a hundred lines. Distilled from the field's primary sources, including the research canon (ReAct, Tree of Thoughts, Reflexion, Generative Agents) and production engineering accounts, and closed by a history of the field, a glossary, and a full bibliography. No survey filler. No framework dependency. Just the mechanics every agent is built from.This item is Non-Returnable
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Details
- ISBN-13: 9798185648049
- ISBN-10: 9798185648049
- Publisher: Independently Published
- Publish Date: July 2026
- Dimensions: 10 x 7 x 0.13 inches
- Shipping Weight: 0.27 pounds
- Page Count: 62
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