BUILDING LLM AGENTS THAT WORK: A Practical Guide to Designing, Building and Prompting AI Agents
English | September 23, 2026 | ASIN: B0HKT3QKWM | 120 pages | Epub | 140.69 KB
An AI agent doesn't just answer questions. It plans, uses tools and takes action. That makes agents powerful, and easy to get wrong.Building LLM Agents That Work is a hands-on guide for software engineers, founders, technical product managers and AI builders who want to design, build and prompt LLM-based agents that are reliable, testable and safe.You'll learn how to
ecide when you need an agent, and when a prompt or workflow is enoughDesign clear goals, scope, autonomy levels and human handoffsUse proven patterns: chaining, routing, parallelization, orchestrator-workers and evaluator loopsBuild tools agents can actually use, with clear descriptions, helpful errors and tight permissionsManage memory, context and retrievalWrite system prompts, plus planning, reflection and error-recovery promptsCoordinate multi-agent teams without chaosBuild a working agent loop with budgets, guardrails and loggingEvaluate agents with test sets, graders and tracesDefend against prompt injection and design for safety and privacyDeploy, monitor and maintain agents in productionInside you'll find 35+ ready-to-use prompts, tool-agnostic code examples, checklists, a troubleshooting guide, a 30-day practice plan, an agent design canvas and a complete capstone project from first idea to launch.The techniques work with any model provider or agent framework, so what you learn stays useful as the tools change.Ready to build agents you can trust with real work? Get your copy today.
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