Books

GPT-6 Astra changes the way prompting works. This practical guide explains what makes it different, why old techniques can fail and how to write prompts that deliver reliable results. Learn how to build, refine and troubleshoot prompts while finding the right balance between control and autonomy.

The field manual for solo builders shipping products with autonomous AI agents. Real systems, real receipts, honest limits.

Nine small LangGraph agents, each adding one guardrail: PII, financial actions, risk routing, human approval, memory, retrieval, plans, output and cumulative limits. Plain Python, fully tested, no theory.

This book shows you how.What you'll be able to do:Say what one resolved ticket, generated report, or active customer actually costs youFind where the money goes in a real system, in about an hourCut your bill by 40% to 70% without making the product worse, and prove it didn'tStop a code change from tripling your costs before it shipsWalk into a budget meeting with a number and an argument instead of an apologyWhat's inside: sixteen chapters. Measure what you're paying for. Apply six levers, ordered by how much they pay back. Then keep the savings from creeping away, which is the part that decides whether any of this survives the year.

AI is changing how we work, learn and live, but understanding it does not have to be complicated. This practical guide explains how modern AI and LLMs work, what they can do, where they fall short and how to use them effectively without the hype.

Stop guessing at prompts. This visual workbook gives you 50 ready-to-run workflows, command cheatsheets, and debugging checklists for Claude Code, Cursor, and GitHub Copilot — so you can open any page and immediately know what to type.

​A system-first engineering guide to building, deploying, operating, and securing production-grade Kubernetes clusters, cloud-native platforms, and AI inference workloads.

Written for people who never asked to become AI users and now are. Not a tour of the technology, but a practical guide to working with it well — the habits that make good results repeatable, and the judgement to know when to check.

AI models do not have to be huge, slow or expensive. Distilling Intelligence explores how to build smaller models that perform at scale, then secure the APIs that serve them. From compression and distributed serving to extraction attacks, observability and incident response, this book covers what it takes to run AI reliably in the real world.

Build AI agents that reason when necessary, preserve what they learn, and stop paying the intelligence premium for work they already know how to perform. Smart AI Agents combines architecture, working implementations, public source code, and measured experiments to show how agents can learn once and execute many.

AI can write code at machine speed. Can your architecture keep up? Architecture at Machine Speed shows how to build Go systems that remain coherent as humans and AI agents change them at unprecedented velocity. Through a real-world application built from the ground up, you'll learn to turn architectural intent into explicit boundaries, enforceable constraints, and automated safeguards—because when code becomes abundant, coherence becomes the scarce resource.

A vendor-neutral, mechanism-level field guide to operating and extending agentic coding harnesses (542 manuscript pages).

Unlock the full potential of Claude Fable 5.1 with practical prompting techniques built for real-world work. Learn how to get better results from coding, research and complex workflows, avoid common mistakes and build reliable AI systems with proven strategies and ready-to-use prompts.