Seven Stories About
Intelligence at Work
A collection of articles exploring what it really means to lead, build, and grow in the age of artificial intelligence — written for practitioners, not theorists.
Every technology revolution produces two kinds of writers: those who explain the tools, and those who illuminate the human experience of living through the change. The articles in this collection aim squarely for the second category.
They began as a question I kept hearing from managers, architects, and developers in my teams: “Where do I even start?” Not with ChatGPT prompts. Not with vendor demos. But with the deeper, messier question of how a seasoned professional rebuilds their instincts for a world where AI is a collaborator, not just a feature.
Each piece below is a chapter in an ongoing conversation. Read them in order for a structured journey, or jump to whichever title pulls you in first. Either path leads somewhere worth going.
Most MCP tutorials stop at “hello world.” This one doesn’t. Walk through building a real integration step by step — the architecture decisions, the gotchas, and the moment when the abstraction finally clicks.
Read on Medium →What if you explained the Model Context Protocol through the lens of a detective who has informants everywhere? A narrative metaphor that makes the architecture stick in ways diagrams never could.
Read on Medium →Managing engineers was already complex. Managing engineers who build with AI is a different discipline entirely. This guide tackles structure, culture, and the new cadence of delivery.
Read on Medium →A comprehensive playbook for engineering leaders navigating AI-assisted development — from estimation and planning to delivery risk and team velocity in the new normal.
Read on Medium →Not another list of tools to learn. A structured progression for IT professionals who want to build durable AI competency — grounded in what employers are actually hiring for right now.
Read on Medium →The uncomfortable truth behind AI-assisted coding speed: faster shipping can mean faster accumulation of debt nobody fully understands. A candid warning for teams celebrating their productivity numbers.
Read on Medium →Written for the practitioner who’s been in the industry long enough to be skeptical of hype — and wise enough to know they can’t afford to ignore the shift. A grounded, actionable learning path.
Read on Medium →