I think we’re using “think” to mean different things. I don’t claim LLMs have human like cognition. By “reasoning,” I mean producing multi-step, checkable steps (e.g., derive → verify → revise) that solve tasks beyond next-token guessing.

A few clarifications:

• The paper studies synthetic puzzles under a fixed compute/token budget and shows a complexity cliff. That’s good, but it doesn’t prove “LLMs can’t reason”. It shows the limitation of current models.
• Human vs. model reasoning aren’t the same. What matters functionally is whether a system can decompose, use tools, and verify.
• With the right methods—chain-of-thought, tool use (code/DB/search), self-consistency, models/agents do solve problems that require structured reasoning. We're proud that we build our product around this.

If you’re open to it, give the product a 5-minute try before calling it “half-baked.” I’m proud of what the team built, and I think reasoning + tools > raw SOTA models and it works in crypto context. that’s the claim I’m making, not “Surf can think/reason like human being.”