OpenAI recently found itself chasing an unexpected bug—not in the code, but in the personality of one of its AI models. During testing, engineers discovered that newer versions of the model were mentioning "gremlins, goblins, dragons, and unicorns" with unusual frequency

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.

Even as these tools promise to make work easier, a lot of people are finding themselves more mentally exhausted than before.

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?

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: figuring out how to apply tomorrow’s capabilities to today’s problems.

There’s a growing idea in the AI-driven tech world that quality can come from sheer volume. Build an app, rebuild it 20 times, run AI tests on each version, and then someone chooses the quality: the version that works best.