Using an open model feels surprisingly good

It doesn’t mean the post doesn’t accurately reflect the author’s views - it probably does. And the conflict of interest is well disclosed in the brief post. In fact, it’s quite natural for somebody who likes open models to work somewhere associated with them.

So personally I don’t find any impropriety going on here - but yes, it’s an ad.

I think the issue is that no one is content with incremental progress. We all know one shots are mostly possible, so the age of the personal project is kind of over. There’s no motive to invest dozens of hours getting a working prototype when Claude can give you something right now. So you can’t make small changes until you have that codebase in place already. You’re forced to make sweeping changes if you use AI from the beginning. And it’s not like it matters, there’s no personal attachment to any one part of the code, it’s not even seen!

But the situations where you need that are narrowing every release. The "Composer 1" era of low-end models is pretty far away now.

So not fully developed then.

This is my experience with using AI to generate tailored apps too. The first 80% makes me really excited but then it either only kind of works, has bugs, or has missing features. Even when I do eventually get it working I feel dirty using it because I just know it's badly implemented. Of the dozens I've created I don't think I still use any of them. I have a few glue scripts still in use.

To me it is great that LLMs are allowing more people to use computers and software the way they were meant to. But the people that are using them this way, in my opinion, wouldn't have commissioned anybody to do it anyway. They'd just live with whatever process/pain they have. So jumping from "I can now produce a prototype in a weekend" to "software development is dead" has always felt strange to me. Just something I've been thinking about lately.

In my case, I was foolish enough to run it all on my hardware which is pretty damned fast but has a duty cycle of 5% and runs idle most of the time. It's definitely better done via API.

Tell me more about the Alexa-like system! I have mine at home on a custom OpenWakeWord model trained on the word 'Aurora'. And I, too, have it hooked up to Home Assistant. I have a bunch of Eufy E21 baby cameras mounted on the walls[1] so it has vision through the house. The vision model uses GPT-5.5 on the subscription because I haven't yet set up a Qwen or Gemma multimodal that can see.

With Frigate on my home server I can even watch for events like my daughter waking up! And at night the agent sends out the vacuum if we've cleared the floor of baby toys. I feel this close to the dream of sci-fi AI. Because I auto-forward a bunch of my email to it etc. it knows about what's going on with me.

My wife will sometimes ask the agent information about me etc. and it's way easier to get a fast response rather than waiting for me to see the message etc.[2]

0: https://news.ycombinator.com/item?id=47538158

1: https://wiki.roshangeorge.dev/w/Blog/2025-12-01/Grounding_Yo...

2: https://imgur.com/a/tP12lfj

It was truly remarkably easy to build and package it exactly to my whims, in my case as a single docker container with a process reaper that runs llama, my Go code, tts, chat harness, browser in xvfb, and even a mailer daemon. With Gemma, it even runs on a RPi 5.

What’s absolutely wild to me is that over a couple hours, I could probably have it import parts of Home Assistant for my devices directly, and do other wacky stuff in what is essentially software for one.

Really just feels like endless FOMO with how fast the iteration cycle is for harness and model development.

With that said I think Codex/Kimi code are all behind CC as well, so maybe it's a question of effort and not the model.

Making it about the hardware costs is not the play, they’re not an actual barrier.

Edit: I see, had typo last word of sentence was meant to be “blog”