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Having strong sandboxing and observability around the models is clearly a hard requirement if you want to run these things autonomously.

In my experience, small teams put security off because someone on the dev team has some security experience, or thinks they do. But it is never the priority, there is always something more urgent to ship, and nobody has real skin in the game because it is not their job. Then shit happens. They rush to hire a security team, and that team spends the next few years fighting the culture.

Recently I decided to create my own VM manager for Mac (think of VMWare / Parallels). It now supports containers, Linux, Mac and Windows vm and local mac accounts. It has support for GPU acceleration too and it is agentic.

I would like to think that I could have done it without AI if I had the time and energy to do it.

I wouldn't have attempted to do this project without AI!

3 years ago the best model was GPT-3.5 Turbo with 16,385 tokens context window.

This is not a good metric IMHO. I would expect new projects to have bigger changes initially as they try to find a suitable architecture. That is not slop. This is no different than rewriting a project 2-3 times pre-AI to find out what sticks and how to organise it better.

All interesting projects that I have seen in recent times are all done with AI.

The latest frontier models no longer produce slop. The code is pretty good in general - better in fact in many situations compared what a human might have produced with limited time, resources and experience.

The argument against AI-assisted programming just doesn't hold anymore.

I will get downvoted for this comment on this forum but I will call it out.

You wont be able to review or understand code for much longer.

There will be just too much of it. The vastness of code libraries in 5 years are hard to imagine by today's standards.

We need to develop tools that help us understand.

I am super excited about this.

While right now Mac Studio is not a budget device and it certainly costs more than the subsidised subscription, the promise that one day we can run these models on commodity hardware is exciting.

I don't understand why you would want to remove well-balanced and relatively small local-inference models that ship with every mac.

Sure, not frontier levels but fine for basic tasks and they are off-the-cloud.

I don't really think there is much future for TypeSafe but I wish them well. In fact, I like them.

Jev is just a reminder that you can use more "traditional" forms of AI (that are not LLMs) and still get remarkable results.

We tend to forget that.

That was a surprise and that is why it went viral.

It will be nice if it had persistent URLs and and SDK for desktop applications. It could solve a lot of small issues for a project I am currently busy with.