• 0 Posts
  • 17 Comments
Joined 3 months ago
cake
Cake day: February 28th, 2026

help-circle



  • Considering the fact that there are open weight models that are pretty close™️ to frontier has me thinking otherwise. Yes I think the frontier companies will probably be face to face with collapse, but capable (and cheap) models already exist and will continue to improve. I think it’s much more likely that companies will simply run their own models (possibly custom agent harness as well) and have all the benefits they were looking for at a fraction of the cost. That being said I do think there will be a significant plateau of capabilities in the next year or so and leadership will realize these are just helpful tools and nothing more.

    All that is to say, I don’t agree with your assertion that coders who are not using AI will have any sort of competitive advantage. In fact I think they’re hurting themselves in the long run. I think skeptical engineers who have a foot in both worlds are actually the best equipped for the future. Accelerate your workflow but not at the expense of quality/security.






  • Eh it’s the illusion of speed. Scaling brought enormous returns from GPT-3 -> GPT-4 but it’s been far less significant for every major release since. To compensate for this, every research lab is coming up with new ways to extract value of it of models: CoT, RL, Agent Harness etc

    However, these are all hacks to make LLMs more efficient or (try) to make them more reliable. They still have significant drawbacks which will take years (probably decades) to ever get them to the point where they can reliably replace knowledge workers. China knows this and is taking a far different approach to LLM development (not a tankie fyi). Scaling is a horrible idea which will burn billions of dollars with an astronomically low chance of return.