A 30-day series on what changes when an engineering team — not just an individual engineer — adopts AI as a first-class part of how they work. From culture and workflows to governance and the human side.

A structured 30-day blog roadmap covering Claude Code, GitHub Copilot, Microsoft Copilot Studio, agentic AI, coding agents, and AI in SDLC — from a Lead AI Engineer with 11 years of experience.

CrewAI's role-based model makes multi-agent collaboration intuitive to design and reason about. How to structure enterprise workflows as agent crews, integrate MCP tools, handle the enterprise deployment requirements, and where CrewAI's model excels over LangGraph's.

A complete production-grade research agent built with LangGraph: typed state, tool execution, human-in-the-loop review, PostgreSQL persistence, and error recovery. The patterns that make LangGraph agents reliable in production.

Agentic systems that work at 10 users per day face different problems at 10,000. Horizontal scaling, async processing, caching, rate limit management, and the reliability patterns that keep agents working when the underlying LLMs don't.

An agent that takes 47 steps, calls 12 tools, and costs $0.23 to run is a black box without proper observability. Tracing, metrics, and cost attribution for agentic systems — what to instrument and how to make the data useful.

How do you know your agent is getting better rather than worse? Evaluation for agentic systems is harder than for single-turn LLM calls — tasks span multiple steps, outputs are open-ended, and human review doesn't scale. The evaluation architecture that makes continuous improvement possible.

The EU AI Act's main obligations entered full enforcement in August 2026. This is what the Act actually requires of engineering teams building AI systems — not the legal overview, but the specific technical and documentation work that compliance requires.

Autonomous agents can take actions that are hard or impossible to reverse. The engineering principle of blast radius control — limiting what can go wrong when an agent makes a mistake — and the specific patterns that implement it.

Prompt injection is the attack surface that didn't exist before LLM-based agents. An agent that reads external content — web pages, emails, documents, database records — can be manipulated by that content. The attack taxonomy and the defences that actually work.