Google's internal compute credit market caused it to miss GPT
Shawn Wang · Why AI Labs With Unlimited GPUs Still Fail — Anjney Midha, AMP · Jun 18, 2026 · at 13:46
Shawn 'swyx' Wang critiques internal market bidding for datacenter compute during a discussion on Google's historic resource scheduling systems.
0:00 / 0:04exact quote · 4.8s
▶ Watch the full episode on YouTube → 720p mp4 · rendered on demand · StarZero watermark
“This is a thing that has been tried internally within Google, and it led to Google missing GPT.”
quote is from the automated transcript, cleaned for reading: filler sounds and stutters are removed, nothing is rephrased. names can be misheard (the analysis reads context, assessments check outside sources). how →
More from Shawn Wang
Swix: Standalone Vector Databases Are Over as a Category
“Everyone has vector indexes now, but like, I think it's fair to say vector databases as a standalone category are over.”
Swix: Pull requests and code reviews are dying, replaced by prompt requests
“The pull request is dying. Yeah. Right? It's going to be the prompt request. And then beyond that, code review is also kind of dying”
Swix: OpenAI will issue a cryptocurrency token to fund compute
“There is still one more shoe to drop, which is the non sovereign wealth funding that open AI needs to get, which they've promised to drop by the end of this year.
And my money is on, they have to do a coin.
Like it's, I'm not a crypto guy at all, but like, y…”
Swyx: AI models hit a 2T parameter wall, won't reach 10T
“As far as everyone is concerned, Claude, you know, Opus 3.5 is not coming out. GPT 4.5 is not coming out. And Gemini two, like we don't have pro whatever we've hit that wall, whatever that wall is. Maybe I'll call it like the two trillion parameter wall. Like …”
Swyx predicts coding SaaS will outlive all other SaaS
“Coding SAS will be the last SAS in the world because all the other SAS will just be buildable via coding SAS.”
Custom $50B ASICs become economically rational for $500B AI training runs
“If you have a trillion dollar or five hundred billion dollar training run, then take fifty billion of that and make an ASIC. Like, it's fine. Like you will get more than 10% efficiency from the ASIC. And like, that makes sense.”