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Scott Wu
Co-Founder and CEO, Cognition

AI Genius Predicts the Next 3 Years

📅 Apr 11, 2026 Joe Lonsdale 8 MIN 72146 VIEWS 13 SEGMENTS · 2 SPEAKERS
Watch the full interview with Scott Wu & Russell Kaplan here:    • How AI Agents Are Creating 12X Productivit...   Scott Wu is the co-founder and CEO of Cognition AI, a three-time gold medalist at the International Olympiad in Informatics who previously co-founded the AI networking platform Lunchclub. Russell Kaplan is the founding president of Cognition AI, having begun his career as a machine learning engineer on Tesla's Autopilot team before co-founding and selling a video data company to Scale AI. Joe Lonsdale is an American entrepreneur, investor & philanthropist. He has been a part o...

Questions asked in this interview

4
  1. 0:00What are the unsolved problems for Devin to just be doing massive projects on itself in three years?
  2. 1:50Like, why are they 100 times faster?
  3. 4:13How did he do in his interview?
  4. 4:36Like, why are you doing that? How are you doing that?
Interviewer 0:00 ↗
Let's just fast forward for fun a few years in the future. When I talk to some of the people running the top labs, they're pretty convinced things are going to keep getting better at a pretty high pace for at least two or three years. It's kind of like with Moore's law — you can't really see out what's going to get there in five years, but it feels like things are going to change a lot. So tell us about 2028, 2029 — are there certain things that just look very different, or certain things that we have to do now that we won't have to do at all there? What are the unsolved problems for Devin to just be doing massive projects on itself in three years?
Scott Wu 0:27 ↗
Yeah, I think a couple shifts. One of the obvious ones, which I'll just call out, is just much more widespread usage of all of this, and then just good knowledge on how to use these things. I think right now you have this core group of, we'll call it, agent-forward engineers, right? Or agent-forward companies that understand how to use this, and they are seeing these, you know, 5x, 10x productivity gains as a result. Obviously, all of these big organizations, or these companies, or governments, or things like that, are seeing those same results and realizing, wait, we can't just sit here and be five times slower — we have to go learn how to do this right now. And so that's really happening, I mean, even this year, I would say.
In terms of the continued capabilities gains that we're going to see — yeah, I mean, I think the models are going to get better and better. One of the stats that people talk about a lot is this METR report, which basically says for each different model that comes out, roughly how much human work can it do in an automated fashion before you have to go interrupt it and say, oh, that was wrong, let's go do this, right? And so it's like, you know, just two or three years ago the answer was like 10 seconds or something — you would have it write one line and then it's like, all right, the next line is already wrong, let's stop here, right? And at this point it's already gotten to the point where it's in the scale of, you know, 10, 20 hours is what the latest one has been. I think Opus 4.6, for example, I think it was around 18 hours.
Interviewer 1:50 ↗
This is always very weird to me because it's implying that models work in human time, though, right? Which is so weird. Like, why are they 100 times faster?
Scott Wu 1:55 ↗
Yeah, so the answer is they do typically do the tasks in less time than a human would, and then the 18 hours is basically this is how long it would take a human to do that amount of work in between each of the interruption points, right? And the AI might be doing that in one hour or two hours or something like that, right? And the thing that's really crazy about the stat is you just see it very consistently double. And I think for the last few years it's doubled about four or five times every year, you know, which is insane. Which means, you know, you wait two or three months and it's already doing twice as much work.

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Cite this transcript

APA, MLA, BibTeX
APA

Wu, S. (2026, April 11). AI Genius Predicts the Next 3 Years [Interview transcript]. Joe Lonsdale. CEOInterviews.AI. https://ceointerviews.ai/interview/2980170/

MLA

Scott Wu. "AI Genius Predicts the Next 3 Years." Joe Lonsdale, 11 Apr. 2026. Transcript, CEOInterviews.AI, https://ceointerviews.ai/interview/2980170/.

BibTeX
@misc{wu2026_2980170,
  author       = {Scott Wu},
  title        = {AI Genius Predicts the Next 3 Years},
  howpublished = {Interview transcript, Joe Lonsdale. CEOInterviews.AI},
  year         = {2026},
  month        = {apr},
  url          = {https://ceointerviews.ai/interview/2980170/},
  note         = {Speaker-attributed transcript with timestamps}
}