What I’m more worried about is feature identification and how to monitor them. How can you get the product to the next level?

Honestly I’m not worried about code anymore in my codebase I’ve not had bug problems for a while and incidents get fixed automatically.

I monitor new features with an agent who checks recordings.

Most actually good features need still 20-30 iterations to design the userflow to actually be interactive, but then there is also another challenge to translate usage patterns into features and how to present functionality with the least amount of friction as possible.

How to efficiently run monitors without wasting your token spends. A best 'monitor' best practice would be nice.

Still this article was very helpful and gave me a lot of new ideas.

Idk Jev doesn’t seem like a thinking model and more like a semantic matching.

Or they use it as marketing wording to get liked by devs.., which is most likely given we know that’s typesafes usp

I mean i’m solodeving and on my github 30 commits a day is light green. Record probably was 280/day, but I’m not sure if every commit is merge to them. or if they just count PRs

I think they’re over reading code, but this almost sounds like they dont even read features/changes anymore. In theory I can imagine it. You have an agent to optimize a certain feature, you have an agent to clean up, you have an agent to develop a support strategy and so on.

They all would analyze data and suggest apple changes themselves.

Do you guys think that’s how it works? Is anybody already operating at that scale, how do you even validate stuff.

Like I think I could run my whole software now only on agents, but not sure how it would turn out.

I’m curious about your curiosity driven queries. Mind to share?

I'm not the person to whom you're replying, but I just tried one of mine:

"I'm interested in understanding the rate of VOC dissipation from fresh oil paint on a surface versus the ventilation rate in the room in ACH. I would prefer solid academic studies of this, followed by analytical evaluation, followed by references to non-quantitative sources. Tell me what's known about this."

that I had run in ChatGPT earlier this week. (Yes, we just had our bedroom repainted, and it's TERRIBLE and I hate it, why do you ask? :-).

I didn't try it first in Gemini Flash, but I did try it in whatever model is used for Gemini Live and the answers were terrible. The ChatGPT answer (I think on medium) was pretty good but it threw in extraneous formulae that weren't actually germane to the analysis. The Argon 4 query I just ran was honestly the best of the answers I've gotten -- it was clear and really well-structured from the perspective of "here are the three big phases that researchers break down paint drying into and what the differing effects of ACH are on those phases".

I'm totally going to give this one a try, after basically giving up on 3.8 flash for most things despite having a free $20 pro subscription (from buying a phone).

Edited to add:

Argon4 transcript: https://share.gemini.google/18Gr5liH1YWR

ChatGPT transcript: https://chatgpt.com/share/6acedc72-ff18-83ea-8909-104cdbc6ac...

Lately, I've been having a lot of Socratic conversations with agents to understand these kind of topics, this helps me a ton, thank you so much!

Kinda odd there's no mention of room humidity.....

I am a professional bassoon player. I asked about multiphonic fingerings. It could actually suggest corrections for the fingerings that did not work.

I‘ve been on both camps and been critized for it (see my comments), and now I think these are some of the most useless disussions on HN, as they are heavily skewed by all of our life situations.

Hmm... interesting opinion. I disagree, and will insult you for it. With any luck, this comment chain will devolve into a thread of unsubstantiated opinions and ad hominems.

Eventually someone will bring up Hitler, or Nazis and the thread will be complete.

Oh, wait...