Aug 18, 2026
Notes on AI adoption in the enterprise (small sample size, very uninformed, but probably roughly correct):
- on the ground there is no such thing as AI adoption in the enterprise
- there is meeting transcription/summarization no one reads, email autocomplete no one uses, marginally useful document search (roughly equivalent to using claude for web search, but worse). Real engagement metrics on this stuff are atrocious
- meaningful adoption (coding, first line customer support, etc.) is happening through specialized vertical products. There are only a couple of categories that are working, but when it works, it _really_ works
- there is tons of experimentation due to executive pressure and incentives. People are really trying, some of it looks exciting at first, but the output is mostly slop and gets abandoned after a while. Some inroads here and there do exist, but they're tiny
- forward-looking ppl (from majority user perspective) talk to personal claude/chatgpt subs all the time and copy-paste tons of stuff. You're technically not supposed to do that but everyone does it anyway and IT departments can't shut it down because that would eliminate 98% of legitimate AI usage
- this forward-looking crowd is a small (but sizable) percentage of mostly young employees. Vast majority of employees don't use AI at all (or maybe here and there to help them write an email they don't know how to phrase)
- lots of internal workshops on how to use AI, demos of successful AI use, etc. None of it is really working
- the mind boggling demand for inference compute is coming from the few massive use cases like coding that are _really_ working, plus chat, plus all the long tail stuff that will eventually take completely different shape since current attempts don’t provide tangible value
- all of this makes me __extremely__ bullish about the future. There is crazy demand for compute and inference APIs already, but barely anything is working! Imagine what happens when the models get good enough to really start transforming workflows?
- when that happens demand for compute will go up 10^6x or 10^9x or whatever practically overnight. I have no visibility into the buildouts space but I can't even begin to imagine how we're gonna build out all this capacity
- one thing that worries me is that we're in a race between investor sentiment and model capabilities. Everything is getting really frothy-- you can't go to a normie bbq without ppl talking about their AI trades. This is not a good sign. If for whatever reason publicly available capabilities temporarily stall (e.g. holding back out of safety concerns, geopolitical stuff, regulatory environment, datacenter nimbyism, who knows what else) and investors blink, we're gonna see the mother of all AI winters
- it would be extremely sad if that happened. It would delay progress by maybe a decade which means a lot of ppl will needlessly suffer/die from disease which otherwise wouldn't need to occur
- if by the grace of god capabilities outpace investor sentiment and we somehow solve alignment, omg I cannot even begin to imagine the next decade