alt Hacker NewsPretty neat how this exponential progress hasn't resulted in exponential productivity. Perhaps you could explain your perspective on that?
Replies
Because that requires adoption. Devs on hackernews are already the most up to date folks in the industry and even here adoption of LLMs is incredibly slow. And a lot of the adoption that does happen is still with older tech like ChatGPT or Cursor.
I think this is an open question still and very interesting. Ilya discussed this on the Dwarkesh podcast. But the capabilities of LLMs is clearly exponential and perhaps super exponential. We went from something that could string together incoherent text in 2022 to general models helping people like Terrance Tao and Scott Aaronson write new research papers. LLMs also beat IMO and the ICPC. We have entered the John Henry era for intellectual tasks...
Sir, we're in a modern economy, we don't ever ever look at productivity graphs (this is not to disparage LLMs, just a comment on productivity in general)
How long before introduction of computers lead to increases in average productivity? How long for the internet? Business is just slow to figure out how to use anything for its benefit, but it eventually gets there.
It has! CLs/engineer increased by 10% this year.
LLMs from late 2024 were nearly worthless as coding agents, so given they have quadrupled in capability since then (exponential growth, btw), it's not surprising to see a modestly positive impact on SWE work.
Also, I'm noticing you're not explaining yourself :)
Writing the code itself was never the main bottleneck. Designing the bigger solution, figuring out tradeoffs, taking to affected teams, etc. takes as much time as it used to. But still, there's definitely a significant improvement in code production part in many areas.