Developer Productivity

After five years in a codebase I knew by heart, I suddenly found myself back at square one in customer-facing native iOS development, and AI became my lifeline.

Engineering teams are starting to resemble legacy Java apps hitting thread exhaustion. I believe change is unavoidable, and we need a better way to organize the work.

The jump from mid-level to senior engineer is often framed as a technical one. Michelle Brenner says the real difference is judgment: understanding the business, making pragmatic trade-offs, and knowing when to ask for help.

Your AI metrics might be measuring the wrong thing. Dr. Catherine Hicks explains how to fix the theory, not the dashboards.

At a CTO Craft Dinner in Toronto, I sat down with engineering leaders from more than a dozen tech companies and asked where AI has actually landed. The free-for-all is over and we need to be realistic.

What economist Charles Goodhart said in 1975 is completely applicable in 2026: When a measure becomes a target, it ceases to be a good measure.

Twenty developers got real about their jobs: the rush of shipping something that actually works, the way a fat paycheck can make you stay longer than you probably should, and the slow death of sitting through another meeting that should've been an email.

At Devoxx UK, I spoke with Trisha Gee - author and one of the most recognized voices in the Java space - about what really happens when teams lean heavily on AI. Her take was far darker than the conference hype.

Production incidents are a context problem. By the time an engineers understand what's happening, they've already bounced across several different tools - and the incident is still ongoing. PagerDuty thinks MCP is the fix.

92% of developers use AI coding tools, but productivity has barely moved - stuck at 10%. Here’s why using AI doesn’t automatically mean getting more done.

At the Pragmatic Summit, I heard firsthand that Uber engineers aren’t just using AI to write code anymore, they’re assigning it work. Let’s see how that plays out.

I was in the room at this year’s Pragmatic Summit when Laura Tacho dropped the numbers: nearly all developers use AI coding assistants, over a quarter of production code is AI-written - and yet productivity gains haven’t budged past 10%.

When teams don’t share information, clash on priorities, or follow unclear processes, even simple tasks can drag on for months.