Books

Kubernetes exposes plenty of state, but operators still have to reconstruct operational meaning from scattered Pods, Services, EndpointSlices, Events, PVCs, owner references, and status fields. This ebook uses `kctx`, a small read-only Kubernetes context engine, to show how deterministic entities, relations, signals, graphs, namespace snapshots, CRD adapters, and stable JSON contracts can turn raw cluster data into reusable context for humans, tools, and AI agents. It is written for SREs, platform engineers, Kubernetes operators, infrastructure developers, and AI tooling builders who want better primitives than raw YAML and improvised troubleshooting pipelines.

Stop maintaining CLAUDE.md and AGENTS.md as two files that drift apart. This handbook documents which file each of nine tools reads — checked on 2026-06-02 against each tool's official docs — and ranks six ways to keep one instruction file in sync, from an @AGENTS.md import to a symlink to a CI drift check. It is also precise about where official support still is not: issue #6235 was closed as completed, but the official CHANGELOG does not mention AGENTS.md anywhere, and on v2.1.246 AGENTS.md is still not loaded into the model's context the way CLAUDE.md is.

Between March and April 2026, Claude Code subscribers lived through six weeks of stacked regressions: cache TTL shortened from sixty minutes to five, a tokenizer that charged 1.35 to 1.46 times more for the same prompts, Pro access that briefly disappeared, and a third-party tool ban. This playbook turns that window into a decision instead of a guess: five measurable triggers, three paths — stay and fortify, switch, or build your own stack — and a decision tree that returns one specific recommendation, with a 30-day cost projection for each path. Edition 2 is 251 pages: ten chapters, six path supplements and four appendices, reconstructed from public GitHub issues, Hacker News threads, and independent measurement posts.

Once the five essential hooks are in place, the incidents that keep happening are the guards themselves failing, silently. Nine chapters collect the hooks (Git, credentials, token spikes, autonomous operation, multi-agent work), a chapter on hooks that do not fire, eight dated incidents from the author's own unattended operation, and a 50-point audit you can run against your own setup.

92% of developers use AI daily. Entry-level jobs dropped 73%. This isn't a story about replacement — it's about transformation. Data-driven guide with a 30-day action plan for developers who want to thrive, not just survive.

Your AI prototype works. Now ship it. Most AI frameworks are built for exploration. kdeps is built for production. Define your agent in YAML, declare its dependencies, and deploy it anywhere — Docker, Kubernetes, a standalone binary, an edge device — without rewriting a line when you switch LLM providers. AI Appliances is the hands-on guide to building autonomous AI agents and multi-agent systems with kdeps: deterministic pipelines, real error handling, real deployment, and no vendor lock-in. Write YAML. Run anywhere. Own everything.

Build defensible evaluation systems for Gen AI, RAG, agents and multimodal applications using datasets, metrics, release gates, monitoring and seven interactive labs.

A leader at a company opens Slack one morning. The brief their virtual employee wrote looks normal: same headers, same prose voice, same cadence as every other brief that week. The last line ends mid-sentence. The API returned `stop_reason: "max_tokens"`. The system shipped it anyway. No exception. No log line. No retry. That bug doesn't look like the normal kind. This book is about why, and what to build instead.

45% do código gerado por IA tem vulnerabilidades. Este livro cobre prompt injection, vazamento de dados, codificação segura com ferramentas de IA, hardening de servidores MCP, sandboxing de agentes e compliance OWASP LLM. 14 capítulos com demonstrações de ataque e código de defesa.

Guia prático para desenvolvimento agêntico com Claude Code, MCP, Claude API e Agent SDK. De modelos mentais a arquiteturas de produção — tudo que um dev experiente precisa para trabalhar de forma agêntica, não apenas usar ferramentas de IA.

As the author, I (Anshuman Mishra) have written this book with the spirit of mentorship — not just to explain how chatbots work, but to help you build one confidently and ethically. I have taught AI, programming, and computer science for nearly two decades, and I have seen countless students struggle to bridge the gap between theory and implementation.This book closes that gap. It teaches you what to do, why to do it, and how to do it right. It’s not just a manual — it’s a journey from curiosity to mastery.You are not just learning to build a chatbot; you are learning to create intelligence — responsibly, creatively, and with purpose.

As the author, I (Anshuman Mishra) have written this book with the spirit of mentorship — not just to explain how chatbots work, but to help you build one confidently and ethically. I have taught AI, programming, and computer science for nearly two decades, and I have seen countless students struggle to bridge the gap between theory and implementation.This book closes that gap. It teaches you what to do, why to do it, and how to do it right. It’s not just a manual — it’s a journey from curiosity to mastery.You are not just learning to build a chatbot; you are learning to create intelligence — responsibly, creatively, and with purpose.

«L'AI mi ha confermato X» usato come prova di X. Output che suonano brillanti ma non reggono a una rilettura severa. Una "AI policy" di tre pagine che nessuno legge. Suona familiare? "Pensare con gli LLM the Right Way" è il sistema di pensiero critico applicato agli LLM: il Triangolo del Pensare-Con (Intento / Avversario / Editore), le quattro decisioni meta di governance, le pratiche socratica e avversariale per indagare e verificare. Non prompt engineering: il metodo per non farsi rispecchiare.

Build MCP servers from scratch — from protocol to production deployment. Learn Tools, Resources, Prompts, HTTP transport, authentication, testing, and server composition. 14 chapters, one real project, complete TypeScript code.