Podcast

We've reached a point where "AI" has become a catch-all explanation for everything from bad customer service to failed software rollouts, even when the technology itself isn't to blame.

OpenAI recently found itself chasing an unexpected bug—not in the code, but in the personality of one of its AI models.

When most people think about AI at work, they picture it as writing code or answering questions. What we've found is that AI can do things that help our entire business.

For years, software teams have organized themselves around one core assumption: writing code is the hard part.

People who thrive during technology shifts are usually the ones who play with the tools early, not necessarily the ones with the most credentials.

People who thrive during technology shifts are usually the ones who play with the tools early, not necessarily the ones with the most credentials.

Should private AI companies should be allowed to draw ethical boundaries around their technology, and what happens when those boundaries collide with government priorities?

The era of “just let the AI do whatever it wants” may not last very long.

We asked our software engineering team a question: “Given how fast AI changes, how has your job changed in the past 6 months?” Their answers suggested that software engineers need to be a little like time travelers with a crystal ball: figuring out how to apply tomorrow’s capabilities to today’s problems.  Just a few months ago, AI-generated code still felt unreliable. Developers would use it to code quickly, but with the expectation that they’d have to come back later and fix everything themselves. When something broke, they dove into the details to repair it. Now, the role is becoming less about writing code and more about directing systems. Instead of fixing problems line by line, developers explain what’s wrong, point to evidence, and let AI handle the implementation. The skill is moving up a level—from doing the work to guiding it. Less typing, more directing. Less fixing, more diagnosing. Even routine tasks reflect this shift. Rather than manually enforcing standards, developers can teach AI to do it for them: run the right tools, follow the right rules, and [...]