u/Gil_berth

>Mr Musk said earlier this year that AI would allow "output" per Tesla worker to get "nutty high".

>But the push to use AI has led to soaring bills, as the cost of using these systems rises with demand. There are fears that staff are also wastefully using AI to carry out menial tasks in an attempt to demonstrate they are using it.

>Several companies are now seeking to rein in staff use. Uber, which had told employees to use AI as much as possible, recently limited usage to $1,500 per month, while Meta, Walmart and Coinbase have all said they will introduce caps.

>The limits mark an about-turn from the "tokenmaxxing" trends in which staff were measured by how many tokens, a unit of AI usage, they were consuming.

>A pull-back on corporate AI usage has stoked fears of a potential stock market crash. Heavy spending on AI infrastructure by labs has helped propel markets to new heights, but this investment is predicated on rapid adoption of the technology.

https://preview.redd.it/uuxhnucn30bh1.png?width=1199&format=png&auto=webp&s=19746e058c4485c9c5953539fb4e6a4845cd2e0c

Drop what you have been building with Claude Fable 5 in the comments.

Can someone working as a software engineer (not vibe coder) give me explanation what is so hyped about it? Few past days I’ve been comparing Fable to Opus by running same prompt for same task. To be precise, I’d switch to opus, run prompt, create branch. Then clean the state again, switch to fable, and do the same thing. The branches are obviously slightly different, but I don’t see any meaningful differences so far. Doesnt seem to be worth to pay 2x.

Edit: my prompts are not too basic. I’ve tried comparing both for various tasks - coding (asking to implement jira ticket, planning, or asking it to dig holes at my plans.

This video shows the true and scary power of Fable 5. The model works for 3 hours and consumes the equivalent of 180 dollars in tokens, the result? A first person shooter template. The game is not fun because you can't die, the enemy bots are retarded, the buy menu is broken(you can buy the same gun many times), the main menu mentions a planting and defusing bomb mechanic that seems to be missing, you can only play as a counter terrorist, you can't pause the game(but it tells you that you can), the game is full of visual glitches and you can easily fall out the map. Obviously, the guy from the video overreacts and says the game it's awesome(he sells an AI newsletter were he helps you to use AI "better").

Now, this guy "only" consumed $180, I know there are people out there willing to squander thousands of dollars on Fable 5 to make the game of their dreams, so I expect that steam, itchio and other stores will be inundated with Fable made games in the next weeks and months. It will be difficult to sift through the slop. Interesting(or tragic?) times lay ahead.

Here is the game: https://fable5-cs27126.vercel.app/

Everyone hates this guy, with reason, but he has a point. If you use closed models, you are practically giving away your IP without creating anything of value. Weirdly, he seems to be trying to pop the bubble in this video and implying that none is making money and that frontier labs are stealing everyone's work. He also says open models with a good harness can be as good as SOTA closed models, which I think is true for certain tasks. This terrible person says in the video what everyone is thinking:

>If it was so valuable, wouldn't I say: "I make you a billion dollars and I want 30%", why are they charging you for tokens if it is so valuable?

If LLMs are so useful, why are they selling them to you? Why don't they use them to make money themselves and keep that advantage? Why help the competition by giving them this "PHD intelligence"?

With Fable 5 back, Vibe coders now can make their dreams a reality. While Fable 5 was away, I've read crazy stories about its capabilities, like it could "one-shot everything". If this is true(which I don't believe), what is the excuse now for not making that gym tracker app that you've been thinking of for years?

EDIT: I'm answering to nearly all comments, but they do not seem to appear for people 🤷‍♂️

https://preview.redd.it/ptwynkzmcmah1.png?width=1980&format=png&auto=webp&s=a09a3b56808afef92aeb65f422e981e9b47182a6

I run a few projects, but around 95% of this went into one of them. The reason the number is this stupid is that I barely write code by hand anymore. I built a set of custom /issue commands where Claude Code takes a single ticket and runs the whole loop itself: research the codebase, plan, implement in an isolated git worktree, review its own diff, fix its own review comments, take Playwright screenshots to check the UI, draft the changelog, and deploy to staging. I mostly open issues and approve merges.

A few hundred agent runs a day is how you turn $62,021 into 71 billion tokens. The second screenshot is 5 maxed accounts in parallel, because one Max plan cannot feed that throughput.

AMA about the spend, the pipeline, the multi-account juggling, or cost control (there is none).

https://preview.redd.it/0eyaqjzmcmah1.png?width=1304&format=png&auto=webp&s=ca95b6d16cebb2473b1c56b13b030905091680c9

Eric Morrison, a software engineer and fledgling youtuber, show us the allegorical, deranged and psychosis infused presentation of the CEO of SoftBank(the principal financier of Sam Altman), Masayoshi Son, where he explains(entirely seriously) how the LLM economy works by using an analogy of a Goose laying golden eggs…

Godot maintainers are being overwhelmed by a slew of new PRs that show obvious signs of being made using LLMs. Godot is a niche open source game engine with a small pool of reviewers, so they can't keep up with the amount of work necessary to filter through the noise:

>This problem is compounded by the recent increase in AI-generated contributions, both by AI agents and by humans submitting AI-generated code. The amount of effort required to make a PR has gone down (and number of PRs has increased as a result), while the amount of work to review PRs and the amount of people available to review has stayed the same. This reviewer shortage was already a problem, but it was one that we successfully ignored. We can no longer ignore it.

This is exacerbated by the fact that reviewing LLM generated code is a pain in the ass:

>AI contributions have the added pain of being demoralizing. Reviewing PRs is already tedious work, but it is rewarding because reviewers generally feel that their efforts are contributing to educating a new contributor (who may become a future maintainer/reviewer). If your feedback on PRs is just being absorbed by a machine and not going towards mentoring a potential future maintainer, it becomes much harder to justify spending your free time on PR review.

The Godot project wants to teach and train the next generation of contributors, so accepting AI slop is not an option. Going forward, they will focus on the following(verbatim from the blog post):

• Encouraging new contributors to become future maintainers, that involves teaching and growing the understanding of new contributors.
  • LLMs can’t learn from specific feedback and thus can’t benefit from maintainers providing feedback.
• Ensuring all contributions are made by humans who can take responsibility for their code and be able and willing to fix it when needed.
  • AI cannot take responsibility, and we can’t trust heavy users of AI to understand their code enough to fix it.
• Adding barriers to low-effort slop.
  • Unfortunately, this means we need to add barriers to contribution, but want to do it in a way that does not cut off our maintainer pipeline.
• Increasing the incentive to review PRs.
  • PR review is the largest bottleneck in the engine right now. We need to ensure that people who choose to review PRs feel their time is well spent.

The Godot project will ban from their GitHub repo anyone that uses autonomous agents or vibe codes. It will also not accept contributions where large parts of the code is AI generated, AI assistance should be limited to "menial things (like code completion, regex, or find and replace)." and will not tolerate AI generated text in human-to-human communications: "Our maintainers do not want to talk to a machine. This is a basic principle of respect."

The Trump administration has asked OpenAI to limit the release of its next frontier model, Chatgpt 5.6, citing security reasons. The news source says the model was on par with the infamous(and also restricted) Mythos model from Anthropic. Apparently, only government-approved partners would be able to use the model.

Fable 5 launched to a lukewarm reaction, but after being restricted, some people began to clamor its return. It seems Chatgpt 5.6 would not even have the chance to be tested by the general public.

It's hard to think that this model release will be more than a incremental release, like Fable 5 showed, but with some new cyber security capabilities. Of course, vibe coders will lament this and protest its release, because they had the hope that one of these next models could be the one that finally fixes that annoying bug, or that terrible problem, that their app has been presenting. Or finally, this will be the SOTA model that can implement their amazing idea that could make them a millionaire. If SOTA models stop releasing to the general public, what would happen with all those unfinished vibe coded apps? What would happen with all those idea guys and their billion dollar apps ideas?

Another round of disingenuous and scammy ads by vibe coding companies...

I read this and I was curious, since nobody has proved that LLMs improve productivity by this much so far, as far as I know. The best that LLMs can show is a ~25% in programming, according to some studies, without evaluating if this speed up was worthy and not offset by other negative factors. Obviously, this politician would say these silly things, but I'm still curious, is there other studies that show an increase in productivity in other areas outside of programming?

Deepseek secured its first round of funding were, its own founder and CEO, Liang Wenfeng, was the primary investor. Deepseek raised $7.4B USD at almost a $60B valuation. Interesting tidbit from the article:

>While Liang has long resisted the idea of raising outside capital, he came around earlier this year because DeepSeek has been losing talent to local rivals. The funding round would establish a valuation benchmark, giving DeepSeek employees a better sense of their equity value and helping stem poaching amid the intense competition for talent, sources told the SCMP earlier.

I'm told everywhere that Deepseek is an example of a successful LLM business model, they themselves say that they have high margins on inference and millions of active users. In China, electricity is cheap, salaries low and Deepseek has distilled western models, so training costs are a fraction of the western ones. Deepseek offers its models at a very low cost, arguing they can do this for many of the reasons listed above. But the above quote seems to imply that they have problems keeping employees by paying them competitive salaries, so its CEO leads a funding round to stem the exodus of employees by inflating their equity with an imaginary valuation.

Of course, everything is opaque from a private company, and more so from one from China; but if a LLM company has a chance to be profitable, that could be Deepseek. If Deepseek is not profitable and needs external funding to keep going, can you imagine what is happening inside western companies?

Archive link: https://archive.ph/20260620065450/https://www.ft.com/content/1d37cc08-e0aa-45a4-a45d-4ad282529314

This is a paradox that I have been pondering on, as jobs shift to reviewing AI generated code, how can people effectively review code if their abilities are being continously being atrophied?