For a project like this, relying on AI assistance also makes it effectively dead in the water.

Why?

Time-cost for machines instead of willing knowledgeable humans. The former requires money, the latter requires passion.

Arguably, passion for a project is without price.

Someone pays for the AI? That's the new human maintainer.

Who will pay if someone, somewhere is not passionate about it?

You can spin up a model locally and pay yourself. Who will maintain the project if the passionate sole maintainer burns out?

I strictly use only local models, so I agree, but the project was built with Fable so my argument hinges on the assumption that the maintainer is going to continue using Fable and needs to pay for it.

Which model works well?

Qwen 3.6 27b at q6 works decently well on 24GB of VRAM

Hypothetically, maybe. In practice, probably not.

Plenty of important things have been born of passion without necessity.

Trust

Not convinced. I was looking for an answer like "it doesn't actually have parity with CPython." If it does, that's a decent indication that it can be sustained.

I wonder how you arrived at that number. Is it perhaps a number that we should aspire to, if we want to write high-quality, maintainable code by hand?

I've been doing some reading recently around what the literature expects a professional software engineer to produce in a day.

In ~1976 Mythical Man Month era it was around 5 lines of fully debugged assembly.

Code Complete 2nd edition ~2004 bumped that up to 10-50 delivered lines of code per day.

I found other estimates of around 20-60. I need to pull them altogether into a cited article.

Based on that plus my own experience I think 100 lines per day of production-level, reviewed and debugged code was a reasonably higher target for a professional software engineer up until just a couple of years ago.

Today I'm frequently pushing 2,000 to 4,000 - and that's not vibe coded junk (I can easily hit 10,000+ if I'm not reviewing anything), that's code that I've reviewed and am happy to put my name to.

Obviously counting lines of code is a stupid, easily gamed metric. But I still think there's signal there. If you want to build a sophisticated piece of software you're going to have to write a bunch of code to do it. Writing at 1,000+ lines of code per day vs 100 will get you there faster.

It's possible, but we're at the moment when most of us can ask Fable to implement a custom compiler to a custom target for our favorite language, and even use it as a part of custom solution. Why do I need someone else's implementation? Where's the magic in this project? What's the secret sauce?

>Where's the magic in this project? What's the secret sauce?

Someone else paying for the tokens.

Also someone seeing it through (should that come). Obviously we're not "at the moment when most of us can ask Fable to implement a custom compiler to a custom target for our favorite language, and even use it as a part of custom solution", without thousands to spare and lots of time to shape the solution.

Even if it does cost thousands (does it? I genuinely have no idea how to scope such a thing) that might be a good price if a custom compiler to your custom target is something you really want. People have paid far more for far less.

If you're a hobbyist trying to compile python to your weird little arduino based thing, then that's a lot of money and you would want to use somebody else's solution, no doubt.

But if you're an aerospace company trying to compile for a flight control computer (and I guess you really want to use python for some reason), spending thousands of dollars on tokens to make and maintain a custom compiler could represent serious savings.

The big picture impact of AI that I see/anticipate the most is SAAS dying out because AI coding makes this kind of enablement and support software easier to make in-house, and this feels like an example of that, but maybe I'm seeing what I expect to see.

Just eight years ago basically nobody wanted to pay for compilers and developer tooling, and now you're suggesting people will spend a thousand dollars for a compiler they'll have to maintain themselves just because they're willing to pay for AI generated tokens but not for finished tools?

>But if you're an aerospace company trying to compile for a flight control computer (and I guess you really want to use python for some reason), spending thousands of dollars on tokens to make and maintain a custom compiler could represent serious savings.

If you're an aerospace company you're willing to pay thousands of dollars for a compiler, because you need a DO-178C certified toolchain so that you can DO-178C certify the whole airframe. Suggesting AI here tells me you have no clue about the realities of aerospace, because you've just thrown out the entire value proposition of the commercial toolchains.

>Even if it does cost thousands (does it? I genuinely have no idea how to scope such a thing) that might be a good price if a custom compiler to your custom target is something you really want. People have paid far more for far less.

I wouldn't spend $100K in tokens to get a custom bare metal Python. Or even $10K.

And I'd guess that most devs wouldn't either, unless they spend $10K like it's nothing.

People that have "paid far more for far less" are people who have the money to buy $10K watches, or fancy multi $1000 clothes.

your first mistake is thinking this would cost that much. with DS4 this might cost far less than 1k imo

With DS4 it would have a lot more bugs, too.

It's like we invented a worse github.

To be fair, most of the training data likely came from GitHub.

Gimphub.

Then the question is why? Because that is an another way of saying donating tokens.