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If you are new here, start with the pieces that best explain how I think about engineering leadership, decisions, AI and agentic workflows, and the practical work of building software teams.
I would start with these essays to get a feel for how I think: raising hard questions early, staying involved when you delegate, deciding how much to trust an AI agent, and paying attention to what teams learn from your decisions, the standards you uphold, and the workarounds you accept.
The Projects AI Makes Possible
How letting an agent try ideas, including approaches that fail, makes projects worth attempting when they would take too much of my own time.
The Code Review Bottleneck In The AI Era
Why teams still need time to review and understand the code, even as AI makes it faster to write.
Let The Agent Decide When It Needs A Ferrari
Why I would like the agent to choose the model, with the option to make that choice myself when I need to.
AI Agents and the Work You Shouldn't Be Doing
On using agents for work you can do, but should not be spending your best attention doing.
Why You Want The Hard Questions
Why I want people to raise hard questions while we still have time to do something about them.
Delegating Doesn't Mean Disappearing
Giving someone responsibility also means providing context and support, and staying involved enough to help.
What Your Decisions Teach People
How people learn what gets valued and rewarded by watching the decisions you make.
Your Responsibility In Cross-Functional Communication
Explaining the risks, impact, options, and next steps so the people working with you can make decisions too.
The Curse of the Worst Acceptable Solution
Why teams keep living with costly workarounds, and how other work comes to depend on them.