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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.

As AI tools become part of developers’ everyday workflows, a lot of engineering leaders assume that getting started is just a matter of buying the right software.

When was the last time a dev conference taught you something you couldn’t learn online? Probably never. But that’s the wrong benchmark - conferences were never just about information.

What if I told you that understanding AI is a bit like juggling knowledge about Marvel, DC, Matrix, Harry Potter, Lord of the Rings, and Pokémon franchises? Crazy, right? But hear me out.

Mackenzie Jackson, security researcher and advocate, told me that AI can’t catch the bugs, but it knows which ones actually matter and provides the context teams need.

For eight years, I was the only one excited to talk about accessibility - until it became law last year, everyone joined in, and I felt... hollow.

Andy Skipper, founder of CTO Craft, warns that even seasoned CTOs struggle with the pressure to deliver AI-driven productivity while balancing innovation and reality.

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.

A canary died in the open source coal mine and a hundred people showed up to argue about the autopsy.

Being the only female software developer in a team is both unique and challenging – and it happens a lot. This is my story.

What do you really think about AI? Be honest, as David Beckham would say.

I often hear AI terms used loosely, so I put together this guide to explain key concepts like agents, tools, and LLMs clearly.

Roles aren’t disappearing - capabilities are expanding, and often the problem isn’t the system, it’s the prompt. I saw that firsthand at this year’s Pragmatic Summit in San Francisco.