Kevin

Because building products has become much more accessible thanks to AI, the bar has had to rise a bit, or at least the expectations have become stricter.

I built my own tool, but personally, I wouldn t launch it on Product Hunt yet because it s still very basic and doesn t even have a website.

AI coding assistants have become part of my daily workflow, especially for repetitive tasks, documentation, and quick prototypes.

At the same time, I've found myself spending more time reviewing generated code than I expected, particularly around security, scalability, and edge cases.

For me, AI has become an accelerator, not a replacement for engineering judgment.

I'm curious how others are using these tools today.

With all the recent data leaks and surveillance laws, it feels like the vibe is shifting toward 100% local, on-device compute, even if it means settling for smaller models. Running things locally used to feel like a niche hobby, but with the massive leaps in open-source efficiency, it is becoming a viable daily setup for privacy-first projects.

Granted, dialing in the right hardware and dealing with speed tradeoffs is still a massive pain compared to a ready-to-go API.

Are you guys actually moving your daily workflows and tech stacks to local alternatives, or is cloud still your go-to for convenience? Where do you stand on this?