I want to make better software, not more software. Making software development faster isn't necessarily the goal. Making it better in the many, many ways that matter (of which speed is just one part) is.

There is more software to be written than there were programmers so lots of people do indeed want more software, for example small tools and one off projects that aren't worthwhile to make pre LLM.

Many people want less software to deal with now, not more. Being forced to download and update apps on your phone that previously could be done without an app, for example.

Which people? They want the right kind of software, that which works for them, not garbage.

I'm looking forward to the making of more software. I think there are probably people who have had really useful software ideas for a long time that they'd never be able to raise money for, but now for $20 a month, they can get up and running, serving their local and/or niche communities, without having to hire a team of engineers.

Eventually we're going to reach a point where they don't have to understand the code themselves. The democratization of software creation is going to be fascinating.

The Android/iOS app store is already flooded with low quality apps. Almost 20,000 games have been released on Steam so far in 2026, that averages to about 70 games per day, every single day. Getting any kind of traction in such a environment is hopeless; every new app might as well be a scream into the void.

Exactly. Reliable abstractions are more important than ever. They're the dues the rest of us must pay to support vibe coding.

A new flavor of tragedy of the commons and free-rider problems.

Everybody wants to be the ones building cheap slop, hoping somebody else makes protections and repairs...

This is mathematicians using the solution, explicitly acknowledged to solve the original formulation of the problem, to pose interesting new questions. That is what mathematics is.

Only someone who has never interacted with mathematics outside a rote-problem-solving capacity would describe it as you have.

Or people with a vested interest in pushing the frontier labs' preferred narrative that they've achieved "AGI"...even while frontier labs continue to hire human "Account Associates", "Android Engineers", "Applied AI Engineers"...

Please. The headline is clickbait, trying to imply that OpenAI somehow screwed up.

What I've said is rather clearly spelled out in the article. Consider reading the it next time?

> It did, however, unambiguously solve the problem according to the Clay Institute’s original formulation.

I did read it. I was talking about the title.

Increasingly stingy usage limits on the subscriptions, regardless of tier.

I’m having the same issue. Hold max subscriptions on both frontier labs but I’ve been forced to use open source models because token limits are not what they used to be. So I end up using Astra and Fable for reviewing, and open source models for implementing.

Is EC2 real-world enough? From June:

https://aws.amazon.com/blogs/compute/aws-nitro-isolation-eng...

And for the PQ parts of Apple's crypto libraries, from May:

https://security.apple.com/blog/formal-verification-corecryp...

Similar from Microsoft, from July:

https://www.microsoft.com/en-us/research/blog/verifying-rust...

I'd expect they could indemnify you against hallucinations or similar if this gets good enough for that to be a very rare occurrence? Or you could buy insurance on it that's cheaper than hiring a lawyer (not a high bar to clear). I wouldn't rely on it currently, though.

No. That kills competition. I want everyone to be competing on the open playing field they are right now, with losses socialized as minimally as possible. There's nothing fundamentally special about LLM companies that would warrant nationalizing them.

To what degree are the competing Chinese labs nationalized?

And—although this is a different point—it's their flagrant exploitation of information commons that warrants their special treatment.

Society as a whole has paid into this technology: through the theft of its intellectual property, through having to deal with the pillaging of so many commons (digital or otherwise) by it, through skyrocketing energy and computing device prices, and even just through ordinary investment. Democratize the technology! At the very least, don't step in legally to prevent this from happening.

Not as many as you'd expect. The perceived difficulty of the problem leads people to more reliable pastures.

Yeah, the interesting thing to me with formal methods is where you write some (partial) specs to tell the LLM what you want. It'll do the usual stuff, plus extra proof work to make sure your intent was actually realized.

Throwing tools haphazardly at the LLM and hoping they increase the correctness of its output is expectedly pretty ineffective. Good to see this borne out in the article.