Don't complain to me if someone responds using a stupid metaphor that proves the opposite of the point they were trying to make.

You cant just go “oh hey, I guess they're both cars so I’m taking your lexus away, catch a cab its cheaper” and expect people to just hug you be be like “yay, thanks! I still have a job I guess! :party:”

:P

Yes. Categorically. Anyone who tells you otherwise and that luna is “just as good” does not know what they are talking about.

Going from sol to luna is a downgrade.

It is not a question, it is a fact.

> Is sol actually worth the extra cost?

Is a question only you can answer, because it has no generic answer.

Right now, for me, being able to use sol is worth the cost, but using it all the time is not.

I’m sure going from using it to using luna feels rubbish; but there are realities about costs you have to face sooner or later.

Maybe like… give your team credits and make them pick the right tool for the job; and if they burn their credits on sol in 20 minutes, well, tough luck buddy, looks like you're coding by hand for the rest of the month.

Team will quickly shift. People hate losing access to ai.

You can’t just “spin Claude up in slack”; it can’t magically just connect to GitHub and your code.

I presume this feature basically is like… if you’re already using your agents in cloud hosted runtimes, then you can connect to those agents like you already are, but via slack.

…

Did I misunderstand?

This seems like a non feature; if you’re bring to want it, you can’t have it because you have to setup Complicated External System, and if you’re already using cloud hosted agents, you’re already using it (eg. Claude tag or whatever).

So it’s what… a diff viewer in slack? An agents tab so slack becomes like cursor?

The videos seem enormously light on examples of how it actually works, did someone find a more detailed example of usage to show why you want this?

Theres clearly no meaningful thought behind a comment like this, and all it does is stir up engagement for laughs.

The comment thread clearly shows this isn't a meaningful discussion, it’s people shouting past each other.

How can AI be bad? I only see good things! :troll face: it must be a woke left thing! :troll face:

Come on.

Without an active harness (eg. Appium) that can end-to-end deterministically verify the changes you make continue to work correctly it is almost impossible to continue to keep the same pace on the app.

Unsupervised LLMs (even fabel) are categorically incapable of running parallel unsupervised mobile app feature development.

That is my personal, first hand experience working in a team in this space.

What you are (I guess?) experiencing is user-in-the-loop light touch LLM development where you can 80% most tasks quite quickly (much faster than without assistance!) with a small number of human developers working on largely unrelated features and manually verifying they are correct and manually fixing the platform specific issues you encounter.

Maintaining a strong appium end-to-end test suite is still extremely challenging with notifications and maps.

Honestly, it blows my mind you could even being to claim that of all things, native apps using obscure languages like swift are suitable for this, compared to the much much easier path of web + react.

You might say “yeah yeah, but one month? Come on!”

…but have you actually seen how much code fabel can write in a month?

Its a lot.

So sure, you say, work at a slower pace. Don't just endlessly run a frontier model in unsupervised feature development mode.

Yes… you see, thats the point. Thats what the op is saying.

Move more slowly, and you can avoid building a spaghetti castle (ok sure! If you dont wanna, maybe don't retype every character by hand, but the point of that practice is not upping your wpm typing speed. :p It is to take the time to think, design and collaborate, not rush rush rush)

Pi has a nice guide on it (https://pi.dev/docs/latest/llama-cpp) and it is really not that hard.

How is that hypocrisy? Self hosting is somehow anti AI? Its not anti AI. Its literally using AI!

…and honestly, at a higher technical level than slapping your wallet against a token provider and running prompts in a hosted sandbox you can't even see the prompts in.

Times change.

Free services owe no one, anything. If you are joining a community, be respectful.

If you're not, and you get banned, that sucks. If it causes a whole category of your peers to be banned that sucks too.

…but its a bit rich to say, oh yeah, the promises you made before LLMs were a thing didn't include a note saying “except if you spam AI generated code”.

Come on.

They dont owe anyone anything.

Certainly not for some comment from ten years ago.

This could entirely legitimately be a case of “was this decision made the right way according to their own decision making process?” … but “is it ok for then to have made this decision?”

Yes. Its fine. It’s their platform. They can do whatever they want.

Do you work with lots of companies and see large AI success stories?

Or do you just vibe that you personally find AI useful so it must also be a business success?

Look, I honestly don’t care, but I think “it must be false” is also unsubstantiated hyperbole. If an agency says they see no AI success, I see no particular reason to believe they’re lying.

They’re not saying AI can’t be a success. They’re saying they haven’t seen it. That matches my experience too. Proven AI success stories seem… vague, when you dig into the details, in my personal experience.

It doesn’t seem surprising to me.

If you slap chat GPT on a tablet or a website or a watch or a smart fridge you can make a song and dance about how great it is.

…but bluntly, it would have been impressive 20 years ago.

It is not impressive today; at least, not to me. I’m not 6.

Did you show them the github repo, or the disappointing 5 second video of chat gpt from twitter?

I was excited too until I saw it actually running and was like… huh. ChatGPT for tablet. Righto.

What was your son so impressed by?

Those two things are the opposite of each other (evidence, but only anecdotally; you cant be both).

Anyway.

More tangible to your argument; what is your argument that this will be more effective than just prompt engineering?

Ive long believed that prompt engineering is a losers game; if there is a trivial set of tricks that improve the output, they will simply be automatically applied.

We see this playing out with the system prompts in coding agents and image gen.

The value of learning “photo realistic studio lighting…” was non existent. The nano banana api is capable of taking a naive prompt and expanding it with these tricks.

People who devoted themselves to learning these “magical incantations” wasted their time and effort; and it was obvious, from the beginning this would be true.

Now.

With managing agents; if a trivial set of management tricks can drastically improve the results, why are you better off learning them now, rather than waiting for them to be baked into cursor/codex/claude in easy mode?

What makes you believe this is a valuable investment in time and effort?

Even if we accept that right now assigning personas to agents and managing them as a manager yields good results, the horizon for change right now is so short, it seems extraordinary to suggest mass management and leadership training for engineers.

We should just wait and see.

All in investments like this would just be tokenmaxing in a funny hat.

This week, we are banned from using anything more expensive than opus 4.6 and encouraged to use sonnet (but not sonnet 5! Thats expensive!) or lower for daily tasks to help manage costs.

Weeks ago, they gave exactly the same justification as you just gave; and it makes sense!

…but maybe not over the next 6 months.

> Maybe not over the next 18-24 months

Maybe not. Probably not, I guess.

A lot of money has been invested on the expectation that the current gen of hardware is going to reap a colossal profit, and the capex to replace it, is vanishing into investor skepticism as we speak.

It seems like most people have a very very low ability to forecast long horizon change in the current environment, but, in general… it seems like until demand drops, the chances of prices dropping is dubious; at best we get a price war with chinese models or a bubble pop; and even then, there are plenty of startups lurking to snap up cheap hardware.

For individuals, the horizon for buying cheap AI capable compute doesn’t seem close, at all, to me.

> Vite+ will manage your global Node.js runtime and package manager.

What? Why?

You’re really going all-in if you adopt this; and… for what? A bit of cozy tooling around existing standard ways of doing things?

Ok, sure; I like tools, like vite.

…but even for an opinionated tool, this is extraordinarily opinionated. Like next.js

Im skeptical.

The pitch of bringing things together seems strong, but did we go too far here?

Reading reviews of people using this didn't really convince me.

It seems to be running on the coat tails of the vite name, rather than its own merit.

Here’s what they said, $$$ aside:

> That’s no longer true. We’ve entered a different regime, where spending more tokens generally results in better results. We call this “compounding correctness” — the more tokens you spend on getting a task correct

> Compounding correctness flips the calculus. If more token spend leads to better outcomes, then you’re going to want to spend a lot of time running tokens. Which sure as hell sounds like tokenmaxxing to me! The original incentives to tokenmax are gone, but eventually folks will realize that a new and more powerful incentive has take its place.

> There were ways to get loops to work, but it was hard. You had to think a lot about how to prompt the agent, which in turn required a pretty deep familiarity with how these things work.

> Now, though, it’s easy. Compounding correctness makes it easy

Go on, tell me I’m quoting the OP out of context.

It’s pretty clear this person believes in compounding correctness, while other, more serious people (1) are perhaps more skeptical.

..and Armins company owns pi. You can’t get much more all in on AI.

Compounding correctness sounds cool, but the real examples of people spending lots of tokens are not compounding correctness; they are wide parallel exploration; like Mythos. The OP is confused, and wrong; they’ve made some basic (flawed) assumptions, and based their entire reasoning on them.

…and are selling AI things. How surprising.

[1] - https://lucumr.pocoo.org/2026/6/23/the-coming-loop/

The more I play in this space, the more I’m drawn to the idea that some kind of back tracking constraint solver is a better solution than then the current naive while loop / brute force approach here.

The results I see are similar to what you get from a greedy brute force constraint solver; solves trivial problems, sometimes solves harder problems after a long time, takes too long to solve really hard problems; solutions are increasingly non optimal on average as complexity goes up.

We have so much existing knowledge about building good constraint solvers, if we could just figure out how to apply it here somehow.

The loop is basically then a while loop:

While (tests fail) { trigger agent: spec, failures list }

for bugs, write failing tests.

Its basically TDD.

Loops do nothing useful beyond making the “spec -> code” step more “hands off” and let you be confident that the code you write does what is intended.

Obviously you see the issue: writing the loop harness is > effort than not having it…

…but the idea is that you run “spec first” and are totally hands off on the code, just updating the validation step and then waiting while the agent iterates over and over to solve for some solution that passes the loop harness.

People suggest that it is possible to go, eg. directly figma/jira to harness via (random tool here), saving even more time and invoking even fewer humans, but thats currently, as far as I can tell, actually just hype.

No one is actually doing that effectively.

Loops are currently carefully hand crafted, which makes them tedious and of questionable value imo.

Tldr: you're doing it wrong but I will not show you how to do it right. I also did not run the bench using my approach but it definitely “vibes better” to me, and I reject your actual research paper.

Come on, show us some actual skills.

That one you use all the time looks a hell of a lot like “I wont a deterministic shell script for something a skill saying ‘run the shell script’”

Is that what you do? How much time do you spend on them? How do you stop the agent from making a bunch of very similar skills? How do you deal with the explosion of the total number of skills impacting your token use? Do you use skills from github, or is that bad practice? Why?

So many unanswered questions; so little content. :/