menu
{ "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.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/9/79/818/564/9798185648049_b.jpg", "price_data" : { "retail_price" : "13.99", "online_price" : "13.99", "our_price" : "13.99", "club_price" : "13.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
AI Agents from Scratch|Ray Wilder

AI Agents from Scratch : A Systematic Path from Theory to Working Systems

local_shippingShip to Me
In Stock.
FREE Shipping for Club Members help

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

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

Related Categories

You May Also Like...

    1

BAM Customer Reviews