Introducing Tokens to the Future: free tokens for builders

0:00Parth, welcome back to Possible. It's been, you know, only a few months, January, since we've had you on Possible. That's five years. Yeah, that's five years in AI time. Or a hundred, who knows.

0:12Parth Patil:What's up, Doc? Like, what's changed? It has been a ride. I was actually just thinking about this just yesterday. Like, OpenClaw came out and went, I mean, OpenClaw went viral, came out in November, but went viral really in February. and I was just looking back at my own logs and I realized I installed OpenClaw on February 15th. And so it's really only been like four months since I was on OpenClaw. But for me, it feels like I've had these systems around me now working with me for years with the amount of skills and abilities that they've accumulated. OpenClaw, Hermes type agents. I think that my concept of an agent has now moved to this point of like, it's this remote worker that works for me at home 24-7, and then I have a few of them running around.

0:59Parth Patil:At the same time, tools like Codex and Cloud Code have gotten even better. We're now in the place. I think when we talked in November, I was like, yeah, I can get Codex to work for multiple hours in a row. Now we're at a point where Codex GPT 5.5 can work for multiple days in a row. It can work five days straight in pursuit of a goal. And that's very interesting. It's so hard. I mean, it's a whole new game of like, how do you evaluate something that works continuously for 50 hours, right? But it's also, yeah, you don't know what the ceiling is. We're still figuring it out. And the game is afoot.

1:39So first, you said a few agents, but actually I happen to know it's a little bit more than a few. what what what's roughly the the the you know the panopticon or the or the pantheon of of kind of uh agents and what is the kind of circle the the number of you know and it's hard to be exactly ontological on this but the number of agents that are that are running yeah so i i i finally have a

2:07Parth Patil:interesting framework for this which is there are there's there's like different levels to the agents. There's agents that, um, that you spin up when you need them arbitrarily, when you want to scale up your effort on a task. Right. I think of those as like the drones, like sub agents, drones, kind of like the ephemeral swarm that you can scale up and scale down on an as needed basis. And then I think there's the other side, which is more interesting. Um, which is kind of like the, the, the open claw, the Hermes, because these, these agents that act that like you work with over the course of several months on a particular problem, they tend to accumulate experience, memories, and skills.

2:46Parth Patil:And what I've noticed is when an agent accumulates an interesting set of skills and memories, you are inclined to give it a name. And it goes from like, it's elevated from the rest of these ephemeral drones that you spin up to someone on your team. And in terms of the number of agents that I have actually named that I go back to for different problems, unique problem spaces or like they have different purposes. Some of them support our team. I have one that just, you know, tracks my personal life. Those I have eight of them. And I think there might be like a Dunbar number here of like how many you can actually manage that you actually want to interact with.

3:26Parth Patil:But even they can spin up drones under them to scale up their effort on different tasks, which is fascinating. Let's say if you count the drones, it's on the order of maybe like 10 ,000 maybe, but like... A few. Yeah, it just gets, you know, you get it. But if you count the ones that like are recurring characters, recurring cast members, I would say eight or nine, yeah. And then, you know, on the 50-hour, you know, kind of tasks, what kind of tasks are those? Yeah, so the first test I gave that clued me into this, like the new ceiling was I asked for Codex to build an Android app and an iOS app at the same time for a concert music discovery experience.

4:14Parth Patil:Basically, I had an app in mind and I've never, never built a mobile app. I've done analytics, but I've never built a mobile app. And it installed the developer kits for both iOS and Android and then started building the app and testing it in simulation because I was basically I said what the success criteria was like send me the working build and send me screen recordings as you build features that demonstrate that the features work so it builds the app it builds a feature it pretends it's a user clicks through the app to make sure that the feature works and the whole thing is a screen recording it sends me so for me it's like I also get the app so I can play with it but like the bottleneck is now reviewing time Right.

4:55Parth Patil:So watching a video of a feature working is actually a lot easier for me to review than reading every line of code in a problem space that I don't have experience. But the idea that you can turn I mean, it would usually take multiple people several months to get something like that done. But the idea that you can just turn a prompt and an idea into the first working artifact in the span of like two, three days is is amazing. It's a new level of prototyping, definitely. And what's the most unusual thing you've, or couple unusual things that you've done with, you know, kind of your agent teams? I'd say the most, one of the more practical, unusual things that I like to do is, so we talk a lot about, like, today we're working with language models.

5:42Parth Patil:And the, you get in what you get, you get out what you put in. So if you're an expert on a topic, you can usually articulate what you want with a pretty good sense of detail. And so your prompts are very precise. You know what you want. And then you get a very high quality output. But when you're trying to get agents to work in a domain where you don't have experience, you might not even know how to ask the right question, how to ask the agent to do the right thing. And so what I have to do, what I do now is I have some agents, the entire job is to just do automated research to construct a knowledge graph of a vocabulary around a space.

6:17Parth Patil:And then when I, when I actually prompt for something, my prompt gets intercepted by the agent upscaled because it's run through this knowledge graph of expertise found from the internet. And then that prompt goes in. So I'm able to, you know, when I prompt a video model, I don't have cinematography skills. But if I describe the kind of effect that I'm going for, the model will upscale my prompt using an accumulated knowledge base of tactics that it's constantly researching. So even researching what are the best ways to use coding agents, having an agent that just researches that is very helpful instead of me relying on my own individual learning curve.

7:00Yep. So given, you know, obviously how fast all this is moving, you know, kind of who's, you know, not only keeping up but leading and what happens if you give them more fuel?

7:14Parth Patil:This is the most interesting thing. I feel there's only so much that I can explore by myself. And I already, you know, that's all I do all day long. And it's hard to keep up with trends in AI. There's so much happening across the spectrum in the field. And so the people, what I found is that the people that are kind of obsessive, that are very passionate about a problem space, these are the ones that are uncovering what the ceiling of AI is, what it's capable of. A lot of the best tools that I use today are a result of talking to my friends that are very deep in these fields. And so we're going to meet some of them, actually, and learn from them.

7:49Let's go into it. So tell people what the Token Grantee Program is.

7:54Parth Patil:So I've had this idea for a while, ever since I started playing with language models. But essentially, we created a program, this token grantee program, where we take a certain number of high potential individuals and we give them$1 ,000 a week in AI tokens. And this is a recurring grant, not a one-time thing. And we don't restrict what tools they can use. And that's by design, because the best model on any given day changes from week to week, right? So we don't want to be prescriptive in terms of what models we want people to use. We actually want people to figure out what the best models are for any given job and then to just use that.

8:33Parth Patil:And so that's why we're very like$1 ,000 a week in tokens, use them on whatever tools you want. And then on top of that, I give them access to a couple agents of my own, which have been accumulating skills that are using a lot of the same models. And so you get this remote agent support. You get that from like Hermes agents, open-claw agents that I've been working with. And then you also get a collaboration with me, right? So I've been deep in these models as well. So being able to bounce ideas off of someone that's also kind of going psycho using all the best frontier models, it becomes helpful for both of us.

9:07Parth Patil:I mean, I get a friend that I get to work with and unpack the future. And then they also get more and more resources. So what does this mean in terms of, you know, kind of, you know, how you balance patience and impatience? What does it mean for creativity? You know, what are the, you know, the kind of the restructuring of what is possible? And now, you know, kind of what's available in terms of what that possibility is? Yeah. Yeah. So creativity has always demanded patience. And I think for the first time, there's certain vectors of the way we work that we can actually choose to trade electricity for time.

9:54Parth Patil:We can choose to, like the fact that you can have an idea for a mobile app and within two, three days, you have a working Android and iOS version. I mean, you can imagine going to the app store within a week without having any engineers is pretty incredible, like if that's like basically the path that we're on. So the idea that we're closing the gap on the time between having an idea and getting it out into the world, I think that's the patience gap. And we're hoping to figure out the mechanisms by which we can close that distance as down as possible. The notion of redrawing the boundaries of possibility of – because part of what we do even in innovation is we constrain our imaginations to a kind of a range of what we think is possible.

10:38And when the possibility landscape gets redrawn, you have to retrain your imagination. You have to retrain what is kind of – what is possible on it. And kind of this balance of patience and impatience because you want impatience for driving where you're going. you want patients to know that actually sometimes a long slog actually, in fact, gets you there. And, you know, this is part of, you know, like, you know, going back to super agency and impromptu kind of like AI being amplification intelligence is it now makes what is possible for people to do very, very different. And also, of course, you know, now scaling is not just split scaling a company, but scaling individuals, scaling imagination, you know, and all the rest.

11:29So let's talk a little bit about your roster of grantees. Run us through them. Sure.

11:36Parth Patil:We have Will Weinbach, who is a New York social media lead who thinks in terms of distribution, content, and social. He thinks about narratives and turning experiments into stories that can travel. And he's also one of the most prolific user of agents that I've ever met. We have Ben Hansford, an award-winning director and creative technologist who teaches film at USC, and he blends deep machine learning work with commercial creative for major brands. We have Joey Salvatore, an editor-turned-VFX artist-turned-AI creator who builds out loud, growing an audience and learning and teaching in public through his content distribution and culture.

12:14Parth Patil:We have Dozia Nazia, a security-minded builder out of Arlington, Virginia, with a CS masters and a deep technical base, the kind of person that turns spare compute into applied experiments instead of passive exploration. We have Katie Zhang, a systems-minded builder in San Francisco, whose arc runs from finance and crypto payments to AI-powered accounting and robotics product ops. And she's even taken a stab at building AI agents for game design. And we have Matthew Tiemann, a DC-based AI engineer with a winding path through robotics, logistics, finance, and data analysis, now building agents at Foundry Logic to strengthen American and energy infrastructure.

12:55It's a fascinating and diverse group. I think part of the selection was people who not only have raw, unique, and interesting mindsets and talents, but also are exploring in different directions. It's kind of AI pioneers. So how about, you know, how did you think about this kind of the selection of this group? And then let's move in from that to kind of thinking about this as a potential new shape for entrepreneurship.

13:31Parth Patil:Yeah. I think, you know, obviously we're seeing in AI right now the first major commercial application is in programming and coding automation. And there's reasons for that. It's a verifiable domain. It's very easy to see whether code runs or whether it works or not. But I think what's more interesting is the second and third order affects the other domains that are less objective, things like the creative spaces. And when I think about AI, I think there's a massive amount of creative leverage that's being created as a result of the automation in the subjective, As a result of the automation in objective domains, we have a huge opportunity in creative domains where it's not obvious what right or wrong is, what good or bad looks like.

14:16Parth Patil:That requires more judgment, better understanding of people. And so when I think about who these people are, I think about people that are, yes, some of them are very strong technically. But more importantly, they have this creative, they don't view themselves as purely technical. They have this creative ambition. they work outside of their lane in their hobbies and interests. And then that passion is taking them to new realizations in domains where AI is not nearly as good. And so I think like figuring out what we should be doing when AI is getting good at automating and doing math and coding, a lot of that is actually like, what about the things AI is like really struggling at that requires human judgment?

14:56Parth Patil:And so that's kind of why we went with a much more broader mix than purely engineers. Yeah. Part of the thing, people naturally think, oh, it's coding, it's use of agents, it must be AI. But actually, in fact, many folks who basically have zero engineering background, zero coding background, actually, in fact, are hugely amplified because now there's a higher premium on creativity, ability to synthesize, being able to ask the right questions, being able to see what problems are kind of interesting to solve, being willing to try something different to make it happen. Like all of this kind of this stuff echoes in to some of the key skills around entrepreneurship.

15:46And so it's kind of this notion of not being afraid of the tech, of being engaged in it. I mean, it's one of the things where, you know, whether it's from, you know new college grads or existing employees like no no actually in fact dive into it and explore it to you know amplify yourself and again that's part of the reason why the closest parallel to entrepreneurs that I've kind of talked about over the decades is pioneers it's it's being willing to explore a new space and that requires a certain risk tolerance a certain boldness but now the depth of the shape of technical skills is very different and include being very light so it's it's much more important to be asking the right questions and be creative the right way which is of course part of the reason why you know you and i you know those few years back started working together not the least between you're you're one of the co-authors of read AI.

16:47So what do we think if we, you know, kind of pull the camera back, you know, you know, if this works, what does it unlock? And we know that access like this is going to broaden. What happens as it broadens? Yeah. You know, I think just three years ago when we met,

17:13Parth Patil:You met me at the tail end of my deep exploration. But at the time, it was not mainstream. Your first deep exploration. Yeah, my first deep exploration of language models. But seeing what GBD-4 was capable of back then and what I could do with it just eight months in, I realized pretty early on, it was kind of isolating at the time. And I realized what I lacked around me was a bunch of other people that were also in the same headspace at the time. and over those over those the last few years what I've been doing is working with a lot of the people that we're about to meet I started meeting them back then and I started introducing them to these technologies some of them had jobs some of them were working on other things but I basically clued them in back then and the interesting thing is like when you when you when you drop like gpd4 into a network and then you come back eight eight months later and you see how people are using it how it changes their worldview how it changes their career arc their view of everything That, I think, is the beginning of this idea of super agency that you write about.

18:13Parth Patil:Because it's not single player, right? I exist in a network. I exist in a community. And once I learn something, I can teach a few other people. And then we start working together. And then we can start collectively learning the next game, the next problem space. And I think that's where we are now. We're in this next phase of this community exploration of many domains at the same time. And AI is getting better faster than you could ever imagine. So no one person can explore it alone. And so now we're at the community level. And then I think it'll be interesting when it starts getting to a society level, right, where each person is now picking, like, is now amplifying 10 people around them, their families, the problem spaces that they work in.

18:52Parth Patil:And it starts getting into different metros, into different countries. I think that's very exciting to me. Being able to show up somewhere on the other side of the world and have an interesting conversation about the frontier capabilities and then what it means for everyday folk. So I'm looking forward to the diffusion of the technology now more broadly. And where are the areas in terms of human expression? And what is this going to mean? Because, for example, you and I have, along with a couple other key members of our team, worked on creating AI music, Christmas album, Valentine's album, You know, got some other ones coming up, you know, a pie song, Celebrating Pie, April Fool's.

19:40That's one, you know, images, you know, kind of, you know, creating a variety of images, but also, you know, kind of like one-off books. Where is the kind of the range of kind of human expression in this? Because I actually think one of the things that people really undercount, part of the reason I did impromptu first, is how much this amplifies the ability to express humanity, to do human connection. Where do you kind of see the range of kind of creativity and human connection going? Yeah.

20:14Parth Patil:So if we're looking at generative media, and whether that's generative text, generative images, audio, video, in its current form, and then where it's going next, there's also generative worlds coming online from Dr. Fei Fei and similar teams. I feel that now any idea can be transformed into almost any medium for a pretty low price I think the quality is still getting there in some of these domains but it is rapidly accelerating I mean just two years ago we were I was showing you prototypes of movie trailers with you and me in them and it was a it was like we didn't have any dialogue and the max the longest shot that we could get that was reliable was maybe four seconds but now with cdance 2 it's clear that we're going to start getting into long form video storytelling that is that is generative and so it's not just like an expansion of vfx but that everyone has a vfx team everyone has a studio in their pocket is kind of where we're going and that changes the number of people that can that can create content the number of people that are telling stories and the range of stories that end up being told so I'm very excited about that I think ultimately I'm personally most passionate about I think within three years we're going to have a thriving ecosystem of vibe-coded games and if anyone can make a game we would have an explosion of games and I look forward to that world.

21:44Well as a deep gamer that is not a surprise have you seen any glimmers yet of you know technology starts with kind of the replication in the new technological medium of old, right? So it's like when, you know, the first kind of online, like, hey, we're going to have marketplaces for transactions, it was like translating newspaper classifieds into, like, searchable classifieds, right? And etc, etc, etc, as ways of doing this. And so in these, these media, you know, you tend music, we've got video, we've got games, we've got images, we've got words. Have you seen anything yet that is, and I've seen a little bit of art stuff that is super interesting, but have you seen anything that kind of is adding to the human expressiveness communication style?

22:43You know, a trivial one might be emojis, you know, kind of where those started getting added into the way that people would communicate emotionally, you know, kind of in quick form and is now part of a, you know, thing, you know, or acronyms from much earlier internet, you know, ROFL, you know, et cetera, et cetera. Have you seen anything like that yet in kind of the various, you know, AI expressiveness?

23:09Parth Patil:Yes. I think we see it in images already, and we're also starting to see in video, but I think AI images, image models, GPT Image 2, which came out, I think, since the last time we talked, GPT Image 2 feels like, I would say, an AGI for images. If I were to say, like, what would that look like? It's an image model that is both really good at rendering, you know, whatever you ask for, but also creating meaningful new infographics and stuff like that. But it's also, like, deeply culturally aware, and it's also capable of modifying images. So I think there is something there which is the there's a new vehicle of creating memes and if a meme is this this idea this viral idea that gets remixed and broadcast and remixed and broadcast by many people we now have the ultimate meme creator which is this like image model that within a couple seconds you can edit the image into this new concept bring in the cultural reference so i think there's an there's new meat there's new vehicles for memes to emerge and i think same thing is true in video.

24:12Parth Patil:And that's really exciting because the number of meme, if the number of meme, if creating something becomes very easy, then more people can do it. More people can participate. And creating memes used to be a kind of a rare skill and kind of a slog. Like you have to actually be good. You have to understand the culture and then you have to go and have the skills to edit the meme together to make it and make something worth it. Something that actually that travels. And I think that more people will be able to create interesting memes and more interesting new meme formats are coming out, video meme formats.

24:44Parth Patil:That's, yeah, I think that's something to watch. We see the early forms of this. Yeah. Yep. And it's kind of just beginning. And then in terms of, you know, one of the things that, you know, people kind of both wonder and worry about is kind of AI as the new companion. It's a little bit like inflection with personal intelligence and, you know, kind of other things. You started this very early, including, like, you know, helping your mom plan trips to Rome and all the rest. What is, like, kind of a principle about, like, how to dive in and use this and, well, for the wonder, and any principles in terms of avoiding or being careful?

25:39Parth Patil:yeah I think the best way to start getting into these systems getting into agents and in a meaningful exploration is to apply it to something that you're very passionate about something that you have experience in that you're very passionate about because then no one has to tell you to do it it's not like oh you got to use AI for your job it's more like actually here's what I want to do I want to learn this new art style like my mom likes doing water she likes exploring art But then she realized that GPT Image 2 becomes a really good co-pilot for pre-visualization for watercolor painting. Because GPT 2 knows how to imagine the thing that you would need before you went to start painting that would give you a better shot of not making a mistake on the final output.

26:21But that kind of connection, it's like, I know my mom cares about art.