"The Cognitive Revolution"
00:35:03 · Nathan Labenz
[00:35:03] S0: I think the general concern is always just that we have so much agent activity flying around, doing so many things. You know, we can't really make sense of it anymore. And before you know it, we're kind of in a zoo of our own creation where the AIs are really running the show and, like, hopefully, we're, like, cared and fed for, but we sort of lose the ability to even understand, let alone, like, rearchitect the superstructures that surround us.
00:35:31 · Samvit Ramadurgam
[00:35:31] S3: Yeah. Yeah. I think I think that that ties to, like, one of the questions on AI alignment. So AI alignment, I think, has, like, two parts. There was, like, have an AI execute on the genuine intentions of the person who asked to do something in a in a skillful way. To avoid the paperclip stuff and all that. I think that's one one part of it. The other part of it, which I think people talk less about, is obviously, like, who are you aligning the AI to? Like, what what is it being aligned to? Especially when people have disagree over what... How the world should be. And so in that world, I think you need a system that can actually get a measure in some sense of, like, what collective well-being means. And I think the way you get a measure of collective well-being is by having a system that's, like, deeply tied into the lives of many people. It's helping them, like, with their work, helping them do, like, the important stuff that they have to do. So I think that you can't... You cannot optimize something you can't measure. And so in a world where you have, like, agents that are coordinating the world, you have no idea, like, what direction that's headed in, like, what the... Know, you this kinda be like... If you imagine, like, a hand of the market is guiding the market, like, what is the direction? The hand is guiding it. If we don't know and we have no way to measure it, then I think we're in trouble. But I think to get to that as as a certain point, you have to have a really refined understanding. Like, what am I measuring? What am I optimizing for? And I think what we've we've learned mistakes from the social network world, which is that any measurement you can make, which is an objective measurement, is wrong if you're trying to optimize for certain click through rate or engagement rate or metric. Any metric you can measure is wrong because human happiness is, I think, fundamentally immeasurable. But there is a thing you can do, which is you can continually converge towards a bet... A better way of, like, measuring. The the the the the kind of, like, the way to optimize a system is not to have a static metric optimized for, to have it be continually trying to discover, like, an optimal point. Have it, like, converge towards an asymptote of, like, this kind of perfect behavior.
00:37:26 · Samvit Ramadurgam, Prakash Narayanan
Even even in the world of of behavior, I think that there's two components to good behavior. Having good intention and then just making sure you had a good outcome. Having... You can have... You can do something that's well intended and have that cause harm, and it was still, a bad action. And so being able to measure the outcome of your action at a systemic level is totally missing from the kind of zeitgeist of alignment. I think that we would hope to be in a place to contribute to that. [00:37:51] S6: What's your token usage like? [00:37:53] S3: It is very high. I think that we... So we have we have, like, an internal target we're setting for our team. This is obviously not what we're... What... Like, the way to optimize for productivity. As, like as, like, a correlate, we we want our team usage on the on the coding agent side. Each person be doing, like, a little... At this... At the current we have our infrastructure set up, like, between one and two billion tokens per day. [00:38:15] S6: One and two billion tokens per day.
00:38:15 · Prakash Narayanan, Samvit Ramadurgam
[00:38:15] S6: One and two billion tokens per day. [00:38:17] S3: Yeah. Product... Productively deployed. And so in terms of how we're building the company, this is like an agent native company. And so we have not only, like, coding agents, we have, like, coding agents that talk to each other. We have, like, an internal organization we've set up of, like, agents. So I have, like, a a chief marketing officer who reports to me, who's got, like, a bunch of different sub employees reporting to that AI. All of them are, like, long running agents that, like, talk to each other and talk to our coding agent sessions and listen to our team video calls. They're, like, are in the meetings with us and chime in and chat to build things for us while we're... Like, I had a meeting this morning where there's some issue with one of our dashboards. We just said, hey, agent. Like, fix it during the meeting. They got updated while we were talking. I think the gap between work and meetings is converging. It used to be that, like, hey. I wanna get out this meeting so I can get back to work and do real work. It's actually changing. There there is still an element of that for sure, but it's changing. It's changing because when we're in a meeting, if you have, like, a rigorous discussion, that's all creating, like, really rich context from different perspectives for an agent that then goes and, like... Then you can just have a have a debate and say, okay. Go do our conclusion with all the aspects that were mapped out there...
00:39:23 · Prakash Narayanan
[00:39:23] S6: In there. What do you feel... You know, you you had Forged Global, which you built in the kind of pre pre agentic era. What what what do you feel is like the big difference between that era and this era in terms of running a company?
00:39:36 · Samvit Ramadurgam
[00:39:36] S3: Here... Here's the metric we have. We're a small team. We're like five people, soon to be 10 people right now. And so the heuristic I have for hiring someone is, are they going to prompt me to do something different than we would have done before? We don't really... You don't really need people to do, like, work anymore for the kinds of work we're doing. You need people to have, like, visionary insight that adds to the DNA of the company, that really lets you do things that... Really, like, makes you do things that you wouldn't have thought to do otherwise, that no age... You can't prompt an agent to do it for you. So I think that we're not... We wanna build this company a way that's, like, building the machine that builds the machine and eventually have more and more agents to spin it up. So I I I think that, you know, there's there's a type of company you could start now that does with a dozen people, like previously took a thousand people. And so we... We'd like to be one of those companies and have more that go towards tokens just because let's just be really lean and move it, be really agile, and have, like, a concentration of of talent and vision. And it raises the bar too. Another thing that changes is that when you hire people now, the incremental value of interdisciplinary skills increases exponentially. So if someone is an engineer, that's valuable. Someone's an engineer and a product person and a designer, that's much more valuable than before. Because before, that person didn't have the ability to actually make use of the integration of these different skills. In the modern world, the more skills you can integrate into one system, the more you, like, coordinate all... If you cut out a lot of interhuman coordination by having it being done in your head, you can articulate a clear vision. To our agent systems, we have so much leverage that the the bottleneck is not execution manpower. The bottleneck is, like, clear articulation of good ideas. That's like the real bottleneck.