Engineering leadership for the teams behind lifestyle brands.
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Latest Writing
The gap between your senior and junior engineers is compounding in ways most leaders aren't watching.
A junior engineer told me he wasn't sure he understood everything the AI was outputting for him. He was reading it, checking it, shipping it. But he couldn't reliably tell if it was right. That conversation opened a harder question about what AI is actually doing to the engineers who never built the foundation first.
The governance gap nobody talks about when your team ships AI-generated code
Technical leaders are being asked to set AI standards, define acceptable output quality, and govern what gets into production. You cannot do any of that if you've lost your own connection to how your team builds. Here's what the drift looks like, and what it costs you when AI has already doubled your team's output.
AI usage numbers can look healthy while your engineers quietly stop being able to explain their own systems
When I reviewed my team's AI adoption dashboard last quarter, every number was moving in the right direction. What the dashboard couldn't show me was who had stopped understanding the systems they were shipping. Adoption metrics and skill development metrics are not the same thing. I had been treating them like they were.