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The productive ones will just fork and accelerate faster. I understand the need for the mental muscle, this framing just sounds terrible at this point. Something something human scrutiny is not even an option the people want to consider.

> The productive ones will just fork and accelerate faster.

Zig has had a similar policy for a while. Where are these myriad forks which accelerate faster, and the communities behind them?


Yeah, where are they?

Let's see when they deliver real features alone which are widely adopted and battle-tested in production.

https://www.ign.com/articles/we-vibe-coded-a-new-epic-games-...

It's not hypothetical to say that an LLM can write widely adopted, battle-tested, production code.

Claude Code would be another example.

Linux is still mostly human, but even Linus Torvalds has warmed up to the idea that LLMs are tools a skilled user can use to contribute there.

There's a lot of quieter, private examples where some company rewrote their entire back-end or internal tooling with an LLM. You just tend not to hear about it because "we used AI" is currently negative marketing/PR, so why say it out loud?


Remember when the Claude Code devs compared their TUI to a game engine while trying to explain why it was so buggy and slow?

https://x.com/trq212/status/2014051501786931427

Remember, game engines can render millions of triangles per frame, and Claude Code struggles to render a few hundred characters on a monospace grid. I wouldn't hold it up as a shining beacon of quality.


> widely adopted

What a poor example. Epic Games’ launcher is popular despite its software, not because of it, and in large part because they give away free games every week.

> battle-tested

You’re just throwing words around. You can’t in good faith call something that is barely out “battle-tested”.

> Claude Code would be another example.

Claude Code is widely regarded as a mess and bad software, and for good reason (see sibling comment).


Everyone is making better software than NVIDIA today with AI, to the extent they are un-nerfing hardware and making stuff run 2x faster. Why would anyone in their sane mind pay NVIDIA anything when they can vibe engineer a faster library?

because NVIDIA can force them

... they can force them and they will - I think it is telling that they are beginning to consider extracting software rents, which could indicate they are beginning to prepare for some lack of sustainability in hardware sales - though right now they cannot make them fast enough, 'em chips.-

They've got no hardware moat and they somehow think people will pay more money for slow software?! Hmmm ....

Not that I necessarily agree with their rationale, but you're framing it differently.

> Lack of sustainability in hardware sales

Doesn't necessarily imply competitors will be eating market share, it can imply the market will shrink. e.g. data center commitments and AI dries up. Or, it can imply hardware development will slow or become "good enough" and slow sales of latest and greatest.


Totally agree, and was more my thinking: Commitment weakening (we are seeing signs of that overall, I believe) and to some degree hardware being sufficient (baring some qualitative paradigm shift ...).-

With jailbreaks coming in everywhere, gamers have a better future with piracy than what any of these console companies are going to "give" them.

Me: Let's make LLMs use that programming language.

The author already did and they were pretty good at it.

On simple tasks, sure. Once a model reaches 100% I'll build a harder benchmark task set.

I need this for my M6 Mini.

Good enough small models are the way.


Insert stick in bicycle meme.


It was amazing back in the day. Wonder why Google really shut it down. I do thank Orkut for Orkut. It's where I met my wife.


L take.


Of course it's a sponsored post.


I really think the authors in FT are not considering:

- The innate value of the models come from not training chips nor hosting, but the actual quality of thinking traces, inference costs and usage. Anthropic shines here, but not for long.

- The variety of skills and evals on new tiny open models proves Claude is expensive and not extremely better than these models today, and math benchmarks alone do not cut it.

- Enterprises are realizing that they can just buy some regular Macs and do their own inference far cheaper than invest in Claude Subscriptions, and Claude given tools are losing their edge to harnesses such as Pi and Opencode.

- Nobody needs Hacking Tools unless they are red-teaming their own code. The niche of people wanting this could write their own tools and workflows to test the effectiveness of many LLMs on these workflows and see how far they can push it.

- The amount of collusions, hypes and fear mongering do not sit well with many people (including myself) - stick to the science and make usage safe, like everything else we do with software in production.

- The IPOs often get priced down with market discovery and anyone who's buying it ONLY is interested in the long run, not inflated valuations not hype not any of these lies used to sell this stock. I am bearish about the IPO at this rate.

- For me, reasons for SpaceX money investments are NOT due to AI *That part is a true waste of money* but good enough due to manufacturing, supply chains and actually building useful Satellite infrastructure; I still am bearish about them launching NVL72 nodes in space, not because of the space part - I just don't trust those chips enough for it to sustain that long.


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