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.

Custom slash commands let you encode team workflows as repeatable prompts; hooks run shell scripts before and after tool calls — together they turn Claude Code from a smart editor into a consistent team process.

CLAUDE.md is the most leveraged file in an AI-native codebase — a poorly written one wastes every Claude Code session; a well-engineered one makes the model a reliable collaborator from the first turn.

A production-grade evaluation strategy for enterprise AI agents isn't about picking one tool — it's about defining evaluation layers, metric selection by agent type, and embedding quality gates into CI/CD.

Each agent framework has a natural evaluation partner — here's how to instrument LangGraph, Google ADK, AWS Strands, Microsoft Semantic Kernel, and Copilot Studio agents for production-quality evaluation.

Azure AI Foundry, AWS AgentCore, and Google's Gemini Enterprise Agent Platform each offer native agent evaluation that integrates directly with their deployment surfaces — here's what they actually provide.

MLflow, Arize Phoenix, TruLens, Braintrust, Promptfoo, and Ragas each solve different parts of the agent evaluation problem — here's what each one is actually good for.

DeepEval brings unit testing to LLM applications — write test cases with metric thresholds that fail CI builds when quality drops, backed by 50+ research-backed metrics.

Langfuse is the OTel-native, self-hostable alternative to LangSmith — MIT licensed, acquired by ClickHouse in January 2026, and the right choice when data residency requirements rule out SaaS.