Nostr Web Client

Taken literally, we agree. What seems to be happening is that people vibe code something, it doesn't work, and they declare that AI "isn't real yet". Another defeatist take is to ask a very specific question that you know very well, and watch it inevitably come back with a lame answer.

What I want people to notice is that most things are hard. It's very likely that given "more tokens" in the abstract sense, current AI would eventually settle on the correct answer.

It's important to realize this because even if something takes an LLM agent two days and $200 worth of tokens, the same task would probably take a person weeks or months and cost an order of magnitude more.

And that's just today. Actually, that was just last week, because Kimi-K2 and Qwen Coder can basically do what Claude Sonnet does for 1/10 the token cost, and it isn't going to stop there.

Stay buoyant 🌊

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Discussion

ESE 5mo ago

I appreciate the clarification — it confirms that the original claim was about tokens alone. Given enough tokens, current LLMs will eventually arrive at the correct answer, regardless of whether they have memory, structured loops, or agent scaffolding.

But that’s precisely where we differ. Increasing the number of tokens expands cache size, not capability. To use a metaphor, transformer inference remains a stateless forward pass — no structured memory, call stack, global state, or persistent reasoning—just a bigger microservice payload.

If reasoning occurs, you’ve added an agent loop, scaffold, or retrieval — a system that uses tokens but is not solely just tokens. These aren’t accidents; they’re part of the architecture.

So we’re left with two incompatible views:

1. “Tokens alone” eventually suffice (your original assertion),

2. Or they don’t — and the real breakthrough lies in the surrounding structure, which we build because tokens alone are inadequate.

Happy to debate this distinction, but we should probably choose one. Otherwise, we’re just vibing our way through epistemology 😄

ynniv 5mo ago

I don't mean "tokens alone"

ESE 5mo ago

Appreciate the clarification attempts. But to be fair, this all started with a confident claim that “more tokens” would eventually get us there — not loops, not memory, not scaffolding — just “tokens,” full stop. That’s not a strawman; it’s quoted:

“It’s very likely that given ‘more tokens’ in the abstract sense, current AI would eventually settle on the correct answer.”

— Posted July 22, 2025 · 12:27 PM

And in case that was too subtle, a few days earlier:

“Use more tokens, kids.”

— ynniv · 4d ago

This was in direct reply to:

“You’re not scaling reasoning, you’re scaling cache size.”

— Itamar Peretz · July 20, 2025 · 08:37 AM

If your view has since changed to “I don’t mean tokens alone” (July 24, 2025 · 1:10 PM), that’s totally fair — we all evolve our thinking. But that’s not what was argued initially. And if we’re now rewriting the premise retroactively, let’s just acknowledge that clearly.

So here’s the fulcrum:

Do you still believe that scaling token count alone (in the abstract) leads current LLMs to the correct answer, regardless of architectural constraints like stateless inference, lack of global memory, or control flow?

• If yes, then respectfully, that contradicts how transformers actually work. You’re scaling width, not depth.

• If no, then we’re in agreement — and the original claim unravels on its own.

In either case, worth remembering: you can’t scale humans. And that’s still what fills the reasoning gaps in these loops.

ynniv 5mo ago

I don't believe, and never have, that scaling context size alone will accomplish anything. I do believe, and always have, that people give up too early. I'm not sure why you're fixated on "winning" this argument – it's not an argument per se, and there are better things to do right now

ESE 5mo ago

I’m not fixated on “winning,” and certainly not looking to drag this out. But if we’re walking back, let’s be honest about what’s being walked.

“Use more tokens, kids.”

— ynniv · 4d ago

“It’s very likely that given ‘more tokens’ in the abstract sense, current AI would eventually settle on the correct answer.”

— July 22, 2025 · 12:27 PM

“I don’t mean ‘tokens alone.’”

— July 24, 2025 · 1:10 PM

“I don’t believe, and never have, that scaling context size alone will accomplish anything.”

— July 24, 2025 · 7:53 PM

If the position was never “tokens alone,” I don’t know what to do with these earlier posts.

So I’ll ask one last time, gently:

Was “more tokens = eventual convergence” a rhetorical device, or a belief you now revise?

We probably both agree that scaling context is not equivalent to scaling reasoning and that transformers aren’t recursive, stateful, or inherently compositional.

I was only pointing out that. If we’re aligned now, we can close the loop.

ynniv 5mo ago

https://sourcegraph.com/blog/revenge-of-the-junior-developer

ESE 5mo ago

That’s a great blog post — I actually like it.

But let’s not mistake narrative for argument. I’m not disputing that experimentation, iteration, and persistence can lead to real progress. In fact, I’d argue that’s precisely why it’s worth being clear on what is being tried.

My only point is that your original phrasing clearly emphasized tokens:

“Use more tokens, kids.”

“Given enough tokens… current AI would eventually settle on the correct answer.”

Then later, you clarified:

“I don’t mean ‘tokens alone’.”

If that was always your intent — that architectural context (loops, agents, structure) matters more than just throwing tokens — I think we’re in violent agreement.

But let’s not retroactively apply that nuance to the initial bold claim unless that was the design all along.

Persistence is valuable, yes. But clarity helps the rest of us persist in the right direction.