25 korrents from this recording
Every claim below is a statement made in this recording, quoted word for word and linked to the second it was said, so you can hear it rather than take our word for it. The wording comes from the transcript published alongside the recording; the sentence above each quote is our reading of the claim, not their wording.
0:06:38 · watch on youtube.com↗
Their wordsI had a lot of my own ego and identity wrapped up in my sort of compiler background. It's all It's interesting, right? But it's it's not useful in any meaningful sense anymore.
0:18:08 · watch on youtube.com↗
Their wordsI'm mad at Amazon for laying off 16,000 people and blaming AI without an AI strategy for it. Those people are not going to be able to find jobs, by and large, and they're the first of many to come and nobody has a plan for this.
0:18:44 · watch on youtube.com↗
Their wordsBecause they're all starting to spend their own salaries in tokens. And so, at least for a while, if you want your engineers to be as productive as possible, you're going to have to get rid of half of them to make the other half maximally productive.
0:19:01 · watch on youtube.com↗
Their wordsAnd so, what's happening is everybody on average is setting that dial to about 50% and we're going to lose about half the engineers from big companies, which is scary.
0:19:23 · watch on youtube.com↗
Our reading
Groups of two to thirty people will produce output that rivals what the big companies produce.
Their wordsit's also enabling engineers who have seen the light and believe the curves are going to continue to go up to actually get together in groups of two and five and 10 and 20 and 30 people and start to do things that rival the output of these big companies that are tripping over themselves.
0:20:17 · watch on youtube.com↗
Their wordsI think a lot of the people coming out of knowledge work are just anti-AI. And those people are going to struggle. I'm sorry, but if you're anti-AI at this point, it's like being anti-the the sun. You're going to have to go live underground, right?
0:22:17 · watch on youtube.com↗
Their wordsthey they're like, "Yeah, you know, I use Cursor, and I I ask it questions sometimes, and I'm really impressed with the answers, and then I review its code really carefully, and then I check it in." And I'm like, "Dude, you're going to get fired, and you're one of the best engineers I know."
0:26:28 · watch on youtube.com↗
Their wordsWhat probably the single most important proxy metric that you can have it in a company today is token burn. Because what token burn says is your engineers are trying to do stuff or your non-engineers.
0:29:11 · watch on youtube.com↗
Their wordsSo I think we're in a weird limbo for the rest of this year okay where until the UIs arrive that are good enough for everybody who can't read everybody who can't read is going to be a severe disadvantage.
0:30:38 · watch on youtube.com↗
Their wordsI think that by the end of this year and we'll see demos of it like right away, but by the end of this year most people will be programming by talking to a face. A face as in a face on the screen.
0:31:44 · watch on youtube.com↗
Their wordsif chat is completions in a loop, basically, and agents are basically chat in a loop, well, then we're going to put we're going to put agents in a loop, and that'll be an orchestrator, right?
0:40:46 · watch on youtube.com↗
Their wordsBut right now I think it's sitting somewhere between half million and five million lines of code, somewhere in there. Probably more on the half million side right now and with the next drop of an Anthropic model, we're probably going to see it jump up to a few million lines.
0:41:29 · watch on youtube.com↗
Their wordsIf you're a monolith, you're kind of hosed because I told you the ceiling's going up for what they can do, but it ain't ever going to hit your monolith. They will never fit in the context window and you're never going to be able to never in the next 18 months be able to tell a model go fix my monolith. You have to break it up.
0:42:05 · watch on youtube.com↗
Their wordsThere's a vampiric effect happening with AI where it gets you excited and you work really really hard and you're capturing a ton of value. For me, I'm doing it all for myself and it's still kind of like pushing me to my ragged edge.
0:43:16 · watch on youtube.com↗
Their wordslet's say an engineer can be 100 times as productive, just just for sake of argument, all right? Who captures that value? If the if the engineer goes to work and works for 8 hours a day and produces 100 times as much, the company captured all of that value.
0:45:41 · watch on youtube.com↗
Their wordsYou might only get three productive hours out of a person at max vibe coding speed. And yet they're still 100 times as productive as they would have been without AI. So, do you let them work for 3 hours a day? And the answer is yeah, you better.
0:51:51 · watch on youtube.com↗
Our reading
Google has produced no innovation since 2008; everything it has shipped since has been acquisitions.
Their wordsIn fact, innovation died on the vine like all together and since I don't know, 2008, there has been no innovation from Google. It's all been acquisitions. They have they've created nothing new.
0:55:33 · watch on youtube.com↗
Their wordsMy my feeling is that probably people have a low tolerance for non-determinism. And these things are fundamentally non-deterministic. So, they can't just go replace customer call center software because they they could be wrong.
0:56:54 · watch on youtube.com↗
Their wordsSo, I think what's happening is we're all looking at the big companies going, "When are you going to give us something?" And the answer is we're looking at the big dead companies. We just don't know they're dead yet.
1:02:59 · watch on youtube.com↗
Their wordsWhere an idea can take root among the agents that's incorrect. It's It's It's a wrong architecture or or wrong data flow or whatever that's that's causing an impedance mismatch for the rest of your code. And what happens is I call it a heresy because they have the tend They have a tendency to to grow and to come back and they're really hard to weed out, okay?
1:05:02 · watch on youtube.com↗
Their wordsThe bitter lesson is don't try to be smarter than the AI, okay? You think that you've got special knowledge. The humans bring special domain knowledge to this problem and we're going to teach it something to AI and it will be smarter. What we found was bigger is smarter. Always.
1:06:57 · watch on youtube.com↗
Their wordsBut, I can tell you that there are at least two more cycles left in this, and that means they will be at least 16 times smarter than they are today, and that is going to cause all of knowledge work to be subsumed by this stuff.
1:17:48 · watch on youtube.com↗
Their wordsBut I'm serious, if you're working at a company that uses that gave you Copilot, they think that they're starting to move faster and there's a barbarian horde of people using Opus 4.5 that are going to destroy your company sooner or later.
1:18:06 · watch on youtube.com↗
Their wordswe are moving into a world very quickly this year where proof of work is so important and I mean proof of work not in the Bitcoin sense but your proof of what you have done, your resume. And I don't mean your resume because nobody's going to believe that. I mean the actual work that you did which has to be visible
1:23:19 · watch on youtube.com↗
Their wordsBut right now we're in a funny place where the some languages work better than others still because they have better training data, but in the fullness of time, all languages will work equally well.