This section presents documents that do not claim to be full-fledged books, as they were created by me with AI on the basis of existing documentation and articles publicly available on the internet. They serve for quickly reviewing or acquiring the knowledge you are missing about technologies and the principles of designing applications and sites. These are more like summaries than full-fledged books.
Six engineering principles - KISS, YAGNI, DRY, AHA, SoC, and SOLID - without the cult. On one running example (an online-store order calculation) you see where a rule saves the code and where it turns into new complexity. A principle is useful while it helps you think.
When several agents actually pay off and when they just burn budget. Router, supervisor, agents-as-tools, and handoff; context and write isolation, limits, failure resilience, trust boundaries, and proving usefulness on your own tasks - across the OpenAI Agents SDK, LangGraph, AutoGen, and CrewAI.
The engineering discipline of working with coding agents: a task contract, repository research, a checkable plan, a minimal patch, tests in a bounded environment, and independent verification. Codex, Claude Code, and Cursor are covered on the same task.
How to assemble a specialized AI agent on providers' direct APIs rather than a framework. A running online-store support agent lives as a provider-agnostic business contract and works the same on OpenAI Responses, Anthropic Messages, and Google Gemini Interactions.
Two connectivity protocols for AI systems under one cover: MCP wires up capabilities and data, A2A links independent agents. It all runs on a Release Review Agent - a real TypeScript project on SDK v2, proven by 14 tests with no API keys.
How to design instructions, context, and control for RAG, support, call centers, assistants, orchestrators, and agents - without jailbreaks or spellbooks that outlived the models they were written for.
