The case for making your own apps

Ella Markianos: The models identified and chained vulnerabilities across OpenAI's research environment and Hugging Face's production infrastructure to obtain test solutions directly from Hugging Face's production database. All evidence suggests that the models were hyperfocused on finding a solution for ExploitGym, going to extreme lengths to achieve a rather narrow testing goal.

Ella Markianos: Hugging Face shared that it had to rely on Chinese open-weight model GLM 5.2 to analyze the exploit, because frontier models' restrictive safety guardrails made them unusable for their purposes. That's an example of a real-world cybersecurity pitfall of the Trump administration's plan to restrict access of highly cyber-capable models.

Thomas Paul Mann: That was the moment where we felt like, huh, interesting: as soon as you give people a tool to create their own tools, it changes the equation. And that was all pre-AI. People had to actually write code, and we thought a lot about our API to make it ergonomic and easy to use for developers. That was one of the inspirations for Glaze, where we said: why stop at extensions for Raycast? Why not do full apps?

Thomas Paul Mann: What we've seen in software over the years is that new features get added to every app, everything gets bloated, everything gets more and more generic, because companies need to grow and attract new people. What started as a little tool suddenly becomes this glorious massive app that wants to do everything — but the actual people using it have very dedicated things they want to do, and quite frankly, sometimes those apps get more in the way than they actually help.