raydenvm

I want to keep track of when people talk about our products online. This includes forums, social media, blogs, and news sites. I feel we are missing out on opportunities to talk with customers and deal with their problems because we find out about them too late (or not at all). For people who are always checking how many times their brand is mentioned online:

- Which service do you use?

- How much money do you have each month for this?

- Have you ever had an important mention get lost?

I'm thinking about setting up a MiniNAS for our small development team. Mainly, for local storage of large artifacts and development builds.

I would love to hear about your real experiences with these compact NAS solutions. Any unexpected issues or limitations you discovered after you have started using one of them?

Have you had a chance to try out the latest version of Codex? How does it compare with Claude Code, which I am currently using extensively?

Everyone’s had a project that failed —startup, side project, or ignored feature. What was your recent failure, and what's your take away? Not just "validate early," but some insights that changed your approach. Curious to hear and learn from your experiences.

I assume the UI update drives people crazy like myself. The changes are so poor: - bloated and overrounded elements - battery icon is ugly looking pill - background color for app group became black ignoring my theme - left/right notification swipe separation (though, I found they left the way to disable that) - rounded notifications are so out of design - bright colors of renewed app icons - volume indicator is disgusting I don't know it feels like a junior designer in Samsung decided to copy Apple approaches and it went totally sideways.

Do you know any ways to revert the OneUI back to version 6? Or we will sit and wait?

I've noticed a trend: as more devs at my company (and in projects I contribute to) adopt AI coding assistants, code quality seems to be slipping. It's a subtle change, but it's there.

The issues I keep noticing: - More "almost correct" code that causes subtle bugs - The codebase has less consistent architecture - More copy-pasted boilerplate that should be refactored

I know, maybe we shouldn't care about the overall quality and it's only AI that will look into the code further. But that's a somewhat distant variant of the future. For now, we should deal with speed/quality balance ourselves, with AI agents in help.

So, I'm curious, what's your approach for teams that are making AI tools work without sacrificing quality? Is there anything new you're doing, like special review processes, new metrics, training, or team guidelines?