It seems there are two distinct groups, one which is doing relatively well with Luna, Deepseek Flash and similar models while other seem to be satisfied only with the state of the art.

Depends on how in-the-loop you want to be. I personally delegate all the writing of the code to agents, but I maintain a clear mental model of the architecture, which I come up with by iterating and prototyping with agents. I can use Luna for all of this, although I switch depending on the task. It's nice to be able to throw a 1,000 word rough spec at Fable and get a personal tool that works perfectly though. I expect that as the models get better, I'll continue to be in the loop, but operate at increasingly higher levels of abstraction.

Having worked with both, it seems like a control thing to me. Either you're cool with Fable spitting out tons of code you'll never read, or you're cool with Luna doing targeted work while you manage the main work thread.

(I'm in the second boat so long as I'm responsible for the code I PR)

I'm ok with not-Fable until I need anything design-related: a nice HTML page, LaTeX typesetting, UI design. Sol is especially incapable of doing anything sensible.

Is there any alternative model with design sensibilities?

Did you add some skill for this? I've been using a frontend design skill with Sol and it's reasonable (for my purposes). I don't remember where I got that skill.md though, it probably was from OAI's own blog about this a few months ago.

Kimi K3 is amazing

fable is good at it but I find it uses the same slop in different variants every time. Even the words it uses for the different alternatives it proposes are the same (cartography, atlas, bench, signal, etc). At least you develop a good nose for slop ;) it becomes a struggle to steer it off the same path every time.

GP kinda explains why: "You have to lead it by the nose".

If you're happy to "lead it by the nose" you can do well with a lot of very low end models.

If you want to kick off a "/goal run until [complex verification passes]" and let it run for a week with minimal intervention, then not so much.

You can make do with cheaper models for long running agentic runs too, but it tends to require a lot of extra scaffolding and additional review steps.

I'm happily in both depending on what it is. Even Sol / Fable cannot do some truly novel stuff and if you rely on it too heavily you get detached from the underlying systems to the point that it's both uncomfortable and detrimental.

Yeah, it's about, do you guide it, or does it guide you.

People who know what they want and know how to describe what they want with sufficient detail, and everyone else.

I’ve just been using it, with a chat interface. Basically, as a “consultant.”

For me, and my projects, it’s been great. It’s made an enormous difference.

I guess my workflow may seem “quaint,” to many folks, here, but the end results speak for themselves.

I suspect that one vocation that could get heavily impacted by AI, is the consulting business. That’s where many experienced people go, as they reach their career peak.

In my last project (just about to ship), ChatGPT replaced a whole bunch of services that would usually be supplied by external advisors.

But these are also services that I would normally not be able to afford, otherwise, and would just have to “make do” with. This release will have a level of polish that I have would never been able to achieve, unassisted by AI (I had originally used “on my own,” there, but the reality is, it actually was “on my own”).

The thing about consulting is that someone needs to verify the output, know what questions to ask in the first place, and provide a throat for the client to choke in the event of an issue. Also, professional insurance. I could be wrong but in the worlds I live in professionally, accountability is still a thing.

Yup. There's some places that we'll need that accountability. I suspect that this may be filled by folks that act as "LLM brokers," using AI in the background, while dealing with the legalities, in the foreground.

But in my case, it wasn't nearly so exotic. The LLM helped me to do a much better job, preparing the App Store presentation, Web support, privacy policies, budget prognostication, and app glossary.

I have just had an extremely complex app, pass App Review, in record time (from going into review, to approval). No niggles or bounces at all.

I'm thrilled.

I'd be curious to pick your brain about the process you went through for this. My mental gap here is not even knowing what to ask for a process like this.

Happy to do so. Probably not something a lot of folks here would find interesting, but I'm easy to contact, from my Web sites. People here, often do that.

Basically, my needs are different from others. I'm not working on the next NORAD upgrade, much of my work is open, and the more ChatGPT knows about me, and the app I'm designing, the better. One reason I chose it, was because of this "memory."

TL;DR: I feed it just about every scrap of information about my project as I can. Source files, documentation, screenshots, videos, information about the organization, information about the target demographic, etc.

With all that information, it gives me very useful advice.

It created a great tutorial. I usually write way too complicated ones. It did much better.

In the case of the App Store stuff, it helped me to choose the right privacy report, generated the privacy manifest, and helped me to compose all the copy on the storefront.

I'll probably be releasing the new app, soon. It's already passed review, but I want to make sure that everything is kosher, before releasing. It came together so quickly, that I have the luxury of time. I just need to release before (or as) iOS27 comes out.

When using LLM's to help write things like tutorials, how do you reduce the verbosity firehose?

Even though I use MD/skills and other methods, I have remind models that they are not paid by the word multiple times a day.

Oh, I don't really do much more than have feedback loops, where I review the output, then ask for things like less verbosity, or a lower-level vocabulary, etc. I like to apply this at each application, rather than make a blanket rule, as each page may have a different audience.

For example, I have made a tutorial, which is meant to be a "quick reference," from within the app (Use Safari to view the page), but I am also developing a "walkthrough," to show possible funders (we're an NPO). The walkthrough is a higher-level vocabulary than the tutorial. The LLM deals with stuff like making sure to keep the glossary consistent, etc., but I like to have the final say on the output.

I'm pretty sure that I can force the LLM to use certain levels of vocabulary, through the .md file that describes the default setup, but choose not to do it.

I am still in that "trust, but verify" stage of my relationship with LLMs.

Pro tip: use 5.6 sol, and tell IT to lead luna by the nose with subagents.

Why do you need to involve IT?

"it"

Same, all I need is speed to execute editing faster than I could in vim. Luna is cheap, intelligent enough, and fast enough I don’t lose the sense of flow.

I feel the same way with Cursor Composer 2.5.