WEBVTT NOTE Sentence-level transcript of https://www.youtube.com/watch?v=EEt3ZSG4a1s NOTE One cue per sentence. Cue ids are the line anchors on /transcripts/EEt3ZSG4a1s.html. A cue ends where the next begins, or 2 s after its last word. s1 00:00:01.309 --> 00:00:03.309 [music] s2 00:00:12.639 --> 00:00:15.720 Please join me in welcoming the chief executive officer s3 00:00:15.720 --> 00:00:15.759 [music] s4 00:00:15.759 --> 00:00:19.920 at Hyper Agent, Howy Lou. s5 00:00:20.305 --> 00:00:22.305 [music] s6 00:00:31.840 --> 00:00:32.480 All right. s7 00:00:32.480 --> 00:00:33.360 Hello. s8 00:00:33.360 --> 00:00:36.480 Um, who's excited about the end of this event? s9 00:00:36.480 --> 00:00:38.399 This this has been an amazing few days. s10 00:00:38.399 --> 00:00:39.280 Amazing talks. s11 00:00:39.280 --> 00:00:41.040 Amazing uh Gary talk right there. s12 00:00:41.040 --> 00:00:43.680 And by the way, I've never been introduced with so much base. s13 00:00:43.680 --> 00:00:46.079 I am very very pumped in this moment. s14 00:00:46.079 --> 00:00:49.680 Um, so I consider myself a product thinker at heart. s15 00:00:49.680 --> 00:01:05.920 meaning you know as much as I like to spend time on the technical side of building and you know I I love to think about architecture and algorithms and so on you know really I'm a product form factor thinker at heart and you know what I want to end today off with is a brief and kind of s16 00:01:05.920 --> 00:01:25.280 highle overview of how I see the world going with agents as it relates to product form factors so I'm calling this hiring employable agents and it's really a reflection on as these models have gotten better and better and we've heard from some really really great speakers about you know the latest uh frontier models whether GLM 5.2 to s17 00:01:25.280 --> 00:01:41.280 uh or others and how to coax the most um performance out of them and really this is not about the technical deep dive but how do we think about these from a product building standpoint so who am I the founder and CEO of air tableable and also know hyper agent which is a product within air tableable and s18 00:01:41.280 --> 00:01:59.439 as many of you already know air tableable is basically a almost laughably horizontal platform uh when we in fact set out to build the company almost 12 years ago we got you know basically this negative feedback from virtually every investor we talked to early on which was you know you can't possibly go out with a horizontal platform s19 00:01:59.439 --> 00:02:07.759 approach and try to build something that is everything for everyone like any type of app that people want to build you know you can't solve all of those use cases s20 00:02:07.759 --> 00:02:17.440 and you know I think we ended up doing a pretty good job of solving for many of them at least and solving for a large builder community and we're basically applying a very very similar philosophy s21 00:02:17.440 --> 00:02:29.040 to agents now and I'm going to break down how we're doing it so um when I zoom out and think about the progression of models and therefore the product form factors they enable. s22 00:02:29.040 --> 00:02:31.200 I really see it as this spectrum, right? s23 00:02:31.200 --> 00:02:40.239 So, we went from basically completions, which is, you know, you give a model, one of these LLMs, a, you know, string of tokens and it just, you know, continues s24 00:02:40.239 --> 00:02:43.040 emitting more tokens until it gets to a stop token. s25 00:02:43.040 --> 00:02:45.599 And more or less it would just kind of complete your thought, right? s26 00:02:45.599 --> 00:02:47.840 Or complete um the pattern. s27 00:02:47.840 --> 00:02:56.560 And you know, until instruct GBT happened and enabled a chat form factor, it was like arguably powerful but more narrowly applicable. s28 00:02:56.560 --> 00:03:06.400 Once we got to a higher level of model intelligence and then also the kind of innovation of instruct GBT and kind of tuning these models to actually have more of a conversational back and forth behavior s29 00:03:06.400 --> 00:03:08.959 with users, then we enabled the chatbot, right? s30 00:03:08.959 --> 00:03:12.159 And of course we all know chatbt was an awesome breakout product. s31 00:03:12.159 --> 00:03:16.560 We're now all very very intimately familiar with that form factor of AI. s32 00:03:16.560 --> 00:03:18.959 The next level I call an agent, right? s33 00:03:18.959 --> 00:03:21.280 And you know I think agent has been very overloaded. s34 00:03:21.280 --> 00:03:30.080 Um, we've probably talked about that a ton over the past few days, but my definition of agent really is the same as the anthropic definition, which is distinct from workflows. s35 00:03:30.080 --> 00:03:34.799 And an agent is really a model that recurses upon itself, right? s36 00:03:34.799 --> 00:03:40.959 And has, you know, the the open-ended set of tools that it could call, of reasoning steps it can make, of decisions it can make. s37 00:03:40.959 --> 00:03:47.040 So, it's not prescripted to a linear workflow, but it can kind of make an open-ended set of choices. s38 00:03:47.040 --> 00:03:56.959 Um, still you know I like to think of agents as being a little bit distinct from the next level of agents which I'm using the term claw here because openclaw obviously has has popularized s39 00:03:56.959 --> 00:04:05.439 uh this concept but you know there's a market shift that I see from agents that were still mostly reactive um you know to user input. s40 00:04:05.439 --> 00:04:07.680 So you would have an agent go and perform a task. s41 00:04:07.680 --> 00:04:12.400 It might spend 20 minutes maybe up to an hour to perform the task and then it completes. s42 00:04:12.400 --> 00:04:22.160 claws um as I call them are really you know about agents that go and perform work for much longer right they can even have a mechanism like the heartbeat mechanism within openclaw s43 00:04:22.160 --> 00:04:40.000 um and now in other products like hyper agent that enable them to wake up on their own and almost like um exhibit this always on behavior I mean underneath the hood what's happening is you know each wake up basically results in many different turns so the agent loops upon itself it's performing tool calls each tool call response s44 00:04:40.000 --> 00:04:51.360 then invokes the the LLM again until it reaches a stopping point, but then that stopping point gets reinvoked or or kind of restarted with a heartbeat mechanism where you can wake up the agent again and again, right? s45 00:04:51.360 --> 00:05:01.600 And so this idea of this always on agent that's actually constantly moving towards its goal and kind of figure out creatively how to unblock itself where maybe prior agents would get stuck. s46 00:05:01.600 --> 00:05:06.720 I think that's a really really important kind of next form factor uh leap that we're seeing. s47 00:05:06.720 --> 00:05:14.320 And then finally, as you think about models that are now capable of, you know, really, really intelligent orchestration of complex tasks, right? s48 00:05:14.320 --> 00:05:23.840 Um, so I've personally been using the workflows capability in uh cloud code quite a bit, uh, where it can fan out a lot of work to a massively parallel set of, uh, of agents. s49 00:05:23.840 --> 00:05:37.360 Um but this concept of you know this agent that can go and orchestrate with other agents right an agentto agent interaction um to perform even more advanced tasks uh right longer running jobs is I think the next leap yet s50 00:05:37.360 --> 00:05:49.520 all of this is enabled because the models are getting smarter and smarter to the point where they can achieve coherence even on longer and more open-ended scoped problems right u if you recall back to the days of um s51 00:05:49.520 --> 00:06:02.639 uh baby AGI and autogbt those were really kind of fun cool science experiments, but ultimately, you know, as much as they were really interesting to watch and, you know, see them work for hours and hours on a problem, they would all inevitably, s52 00:06:02.639 --> 00:06:06.160 you know, kind of end up drifting off to something not super useful, right? s53 00:06:06.160 --> 00:06:09.280 It would go off into a rabbit hole and kind of get stuck. s54 00:06:09.280 --> 00:06:20.160 And I think now the models are actually smart enough to enable not only longer running jobs but actually enable us to start applying these kind of organizational principles to break down problems s55 00:06:20.160 --> 00:06:24.639 into differently scoped tasks that different agents can hand off to each other. s56 00:06:24.639 --> 00:06:33.199 All of which is about managing each agent's task uh or context window and ability to coordinate work with each other. s57 00:06:33.199 --> 00:06:34.720 So all this is kind of abstract. s58 00:06:34.720 --> 00:06:44.479 I want to make it very very tangible and show you how we've applied some of that design thinking of building a horizontal product and distilling a lot of the complexity of agents s59 00:06:44.479 --> 00:06:51.039 like we did for building a database or a database powered app with air table for agents in hyper agent. s60 00:06:51.039 --> 00:06:56.160 So this is a um a very realistic use case based on some of our actual customer usage. s61 00:06:56.160 --> 00:07:04.560 One of the interesting things we found from launching Hyper Agent is, you know, the the uh prototypical users for Hyper Agent are not who you would think they are, right? s62 00:07:04.560 --> 00:07:18.000 I mean, we definitely get our fair share of like the super AI forward, you know, kind of pure software companies, like AI companies themselves, but we also get really interesting other companies that are, you know, sometimes like traditionally offline businesses. s63 00:07:18.000 --> 00:07:27.919 And in this case, we're depicting a very realistic scenario, which is um a customer uh that is in a landscaping business and actually uses agents to run virtually endtoend s64 00:07:27.919 --> 00:07:39.120 every part of their business, which is finding clients to propose landscaping projects to like physically going and like redoing their garden or their backyard and end to end managing everything from the prospecting s65 00:07:39.120 --> 00:07:42.720 to building a quote and a pitch to managing the work itself. s66 00:07:42.720 --> 00:07:56.160 And I think this is a huge huge um interesting um insight that you know I've just kind of stumbled on from working on hyper agent which is ingenuity of agent builders is not contained to just AI companies or software companies. s67 00:07:56.160 --> 00:07:58.960 Um and I was really inspired by Gary's talk just a second ago. s68 00:07:58.960 --> 00:08:11.039 I think that the uh the motive behind that applies to every industry, every sector and there are really really creative people many of whom are in this room who can go out and disrupt your own industry whatever it be. s69 00:08:11.039 --> 00:08:13.280 You know, it doesn't have to be a pure software business. s70 00:08:13.280 --> 00:08:23.039 Um, but I think all it takes is the ability to imagine what work could look like when you do go and become fully not just an AI native company, but I like to use the term, you know, a fully s71 00:08:23.039 --> 00:08:32.800 fleet of agents native company where you're actually going above and beyond and not just thinking about small kind of narrow steps to automate with AI, but actually how to employ s72 00:08:32.800 --> 00:08:43.519 a whole fleet of agents that have governed behavior and have the right context and the right tools to be able to do really useful and very end-to-end autonomous work. s73 00:08:43.519 --> 00:08:45.279 So let's walk through what this looks like. s74 00:08:45.279 --> 00:08:51.839 Um this is a realistic example of you know in this business this uh this landscaper wants to go and pitch clients right? s75 00:08:51.839 --> 00:08:56.160 So you know they get all these inbound uh submissions of clients who are interested. s76 00:08:56.160 --> 00:08:59.839 Somebody submits this inquiry saying hey here's my current backyard. s77 00:08:59.839 --> 00:09:01.279 You know it's a little messy. s78 00:09:01.279 --> 00:09:06.160 Here's my info like can you give me a quote and show me a proposal of what you could do? s79 00:09:06.160 --> 00:09:12.080 This basically gets routed into a um in into one agent that is the triager agent, right? s80 00:09:12.080 --> 00:09:21.440 And so this agent is basically taking in this intake and saying, "Hey, like what is the um the scope of the project, you know, like is this something we want to take on s81 00:09:21.440 --> 00:09:23.200 and is this a quality lead? s82 00:09:23.200 --> 00:09:24.240 Is this a legit person?" s83 00:09:24.240 --> 00:09:36.640 And so it does some research, but ultimately it hands off then the work to another agent, a surveyor agent to actually go and then look at the um the physical landscape of this person's backyard s84 00:09:36.640 --> 00:09:41.600 and come up with a proposal of what a rellandscape version of that could look like. s85 00:09:41.600 --> 00:09:49.680 So here um the surveyor agent is going and looking at the original imagery uh or even video that the um submitter gave them. s86 00:09:49.680 --> 00:09:55.519 Um, hyper agent uh in our case uh works with a fully um capable sandbox VM. s87 00:09:55.519 --> 00:10:00.320 So every agent in fact every thread with an agent is able to fully write code. s88 00:10:00.320 --> 00:10:01.519 It can manipulate files. s89 00:10:01.519 --> 00:10:15.440 It can actually use things like ffmpeg to like you know clip out individual screenshots from a video file and then analyze those um and actually go through and like find all the relevant information to create a fairly high quality s90 00:10:15.440 --> 00:10:20.880 um and hightouch uh proposal that would have been unfathomable for a small business like this before. s91 00:10:20.880 --> 00:10:21.120 Right? s92 00:10:21.120 --> 00:10:31.600 If you think about like a really high-end interior designer or maybe like a very high-end landscaper, maybe they could do a very bespoke proposal like this for like a $5 million plus s93 00:10:31.600 --> 00:10:34.320 uh client, you know, if they're working for a big hotel or something. s94 00:10:34.320 --> 00:10:44.079 But it would have been unheard of to do something this hightouch and actually mock up real imagery and a real client pitch deck for, you know, just a small backyard landscaping proposal. s95 00:10:44.079 --> 00:10:54.959 But this person has done it because they've they've figured out how to use agents in an extremely capable and autonomous way to do the job that otherwise would have been undoable by humans. s96 00:10:54.959 --> 00:11:09.920 And so what happens next is you know the surveyor agent it it went and created this proposal and pitch and now the intervention has to go back to the human like there is a step where humans still need to unblock the agents right Sarah Guo put out a great post uh a few weeks ago about you know s97 00:11:09.920 --> 00:11:22.320 just describing like where the value is going to acrue in this AI landscape as things evolve and models get smarter and I firmly agree with her take which was you know the ultimate blocker to still be able to deploy useful agents s98 00:11:22.320 --> 00:11:32.160 there's still a human element to that you know as As much as models are getting smarter, the ability for agents to get unblocked by humans that still own policies and decisions s99 00:11:32.160 --> 00:11:41.600 and really importantly just kind of gate, you know, really critical um high impact actions like in this case actually making a pitch to a customer that has a binding quote s100 00:11:41.600 --> 00:11:53.760 um or perhaps like agreeing to do the work that becomes something that the human then intervenes at just like a great manager who's getting upwards uh reports or you know upwards work updates from their team to then unblock. s101 00:11:53.760 --> 00:12:05.600 So here we have Sage who has come back to uh the real human uh owner of this business and saying hey here's a lead I already surveyed the the project here's a beautiful pitch deck and a proposal s102 00:12:05.600 --> 00:12:22.560 and have come up with a realistic quote based on all the factors I've already surveyed in this uh particular project to give to uh to you to now approve sending to the client and see if they accept it right and you can see like even the u the proposal itself is this really beautiful kind of interactive s103 00:12:22.560 --> 00:12:33.920 uh web page that again would have been unfathomable for a business like this to be able to send to every single client even for small tasks uh or jobs like a $10,000 landscaping proposal, right? s104 00:12:33.920 --> 00:12:45.360 Um you know, better yet, as you interact with these agents, you know, as as Gary talked about with GBrain and and just kind of like creating this very um sticky context layer that learns with every interaction. s105 00:12:45.360 --> 00:12:46.240 I completely agree. s106 00:12:46.240 --> 00:12:55.040 I think that is a you know kind of a universal principle and kind of a form factor for useful agents going forward is agents should not be static. s107 00:12:55.040 --> 00:13:02.000 They should not just be you know either static LLM calls or static even agents that just have a prompt and you know some static skills. s108 00:13:02.000 --> 00:13:13.120 They really need to learn with every interaction right and you can't wait for the next you know kind of fine-tuning run of your own models where you have you know a bunch of collected data or rubrics to to retrain the model. s109 00:13:13.120 --> 00:13:15.040 It should learn in real time, right? s110 00:13:15.040 --> 00:13:24.720 It should accumulate the memories and skill updates and just take user feedback and actually learn from real world performance to constantly adjust and get better just like humans do. s111 00:13:24.720 --> 00:13:39.279 And so in this case you can see you know within Slack or you know in our case within uh either Slack or email or other um invocation methods you can basically go back and forth with the agent just like a real human and say hey like you know remember to take this into account next time you kind s112 00:13:39.279 --> 00:13:48.720 of you know here's something differently uh formatted or a different way to think about the proposal or you missed kind of um this additional cost lever in this particular project. s113 00:13:48.720 --> 00:13:50.720 So, you know, remember that for next time. s114 00:13:50.720 --> 00:13:56.800 And I think it's critical that in this next generation of agents, agents need to remember these things, right? s115 00:13:56.800 --> 00:14:11.120 Um they should feel fluid and and um evolving just like humans are in order for them to fully realize the potential that the latest frontier model capabilities enable them to to actually go and do in terms of autonomy. s116 00:14:13.360 --> 00:14:25.360 Um, and then finally, I think what ends up happening at the end of all of this is with all of these agents that are each individually capable and even interacting with each other, I think the job of the human becomes increasingly about unblocking s117 00:14:25.360 --> 00:14:27.839 agents to be able to do work effectively. s118 00:14:27.839 --> 00:14:38.959 And so, you know, I I compare this to the development workflows that uh have evolved from, you know, originally before any um, you know, kind of AI enabled coding, obviously, we just sat in front of a computer. s119 00:14:38.959 --> 00:14:40.720 We as humans are pretty single threaded, right? s120 00:14:40.720 --> 00:14:56.160 You'd start at one code file, you think about a problem, you'd kind of bang out some code, maybe take a break, come back to it to then we had um augmented coding with the first generation of GitHub copilot and similar tools where I mean I think of that as really just a completions form factor on coding. s121 00:14:56.160 --> 00:15:04.959 You type some code, it can autocomplete a few extra lines to then we had things like cursor composer 1.0 0 like the original uh experience not the the composer model s122 00:15:04.959 --> 00:15:17.920 um but the chat experience where you could talk to this agent it would do more complex changes and that was even more leverage right but we're now moving to this point where you know the best frontier agentic developers I know and many of you are sitting in this room s123 00:15:17.920 --> 00:15:32.399 are are really just kind of overseeing a fleet of agents right like in fact going to sleep without setting off your agents to perform useful work overnight feels like you're you're taking this huge loss like your your team is not working because you're not unblocking Um, and so the UX s124 00:15:32.399 --> 00:15:40.160 of how you oversee these agents, whether it's in development workflows or general purpose work like this landscaping example needs to shift as well. s125 00:15:40.160 --> 00:15:52.000 And so the way we've thought about that is you need to see this kind of orchestration control plane where you can see at a glance what all of your agents are working on, what they're blocked on, who's handing off work to each other. s126 00:15:52.000 --> 00:16:03.120 And your job becomes almost like, you know, zooming out to see the entire Sim City landscape and orchestrating across everything going on at a macro level between your different agents s127 00:16:03.120 --> 00:16:09.120 rather than going and having to play micro and zoom into each individual project or each individual task. s128 00:16:09.120 --> 00:16:18.320 Um and so I think this is a really really exciting moment as we have shifted from you know not just completions and kind of the slight augmentation of existing human s129 00:16:18.320 --> 00:16:25.920 uh work but really a radical now leap into humans as orchestrators of agents that also can orchestrate themselves. s130 00:16:25.920 --> 00:16:40.000 and finding the right way for us to interact with those agents as they become more and more capable is going to become not just the opportunity to boil the ocean but in my opinion table stakes for survival for every company in every industry s131 00:16:40.000 --> 00:16:53.199 this is going to be the way to get ahead and thrive in your industry and if you don't you know as Jensen put it you know it's not going to be AI taking your job it's going to be you know somebody using AI who takes your job or takes your business so really really excited both for the s132 00:16:53.199 --> 00:17:01.680 opportunity and for everyone in this room to be part of this um transformation and this really kind of bold leap into the next form factor of AI. s133 00:17:01.680 --> 00:17:04.640 Um all that being said, we'd love to see you try Hyper Agent. s134 00:17:04.640 --> 00:17:08.319 So hyperagent.com/aiie and you get $1,000 of inference credit. s135 00:17:08.319 --> 00:17:17.520 Um you know that can be spent on all of our different model offerings including uh you know the latest uh Opus 4.8 Fable 5. You can use it on GLM 5.2 s136 00:17:17.520 --> 00:17:25.120 uh on GBD 5.5 etc. and we'd love to see what you do with uh with agents on Hyper Agent or elsewhere. s137 00:17:25.120 --> 00:17:28.160 Thank you all for being here. s138 00:17:57.679 --> 00:18:00.160 How are we again? s139 00:18:00.400 --> 00:18:01.600 Thank you for joining us. s140 00:18:01.600 --> 00:18:02.400 Thank you. s141 00:18:02.400 --> 00:18:16.720 Um so for the close of our events uh a few months ago I saw that hyper agent was launching this startup competition and at AIE we've always wanted to feature some kind of battlefield s142 00:18:16.720 --> 00:18:29.120 for like a competition and a contest for people uh and we didn't really have any sort of mechanism by which to judge or to fund it or anything like that and hyper agent came along and they had this uh 500 founders s143 00:18:29.120 --> 00:18:31.200 right what was the inspiration for that s144 00:18:31.200 --> 00:18:45.760 you know I think um as I think about the multiple layers of disruption stacking you know we we're going as I said from you know just humans doing the same work they were augmented a little bit by AI to now humans overseeing fleets of agents doing work that wasn't before possible like this landscaper s145 00:18:45.760 --> 00:18:55.360 running his business in a fundamentally different way to now this entirely new economy of agent native companies being built and so you know really the founding 500 is about betting on the most frontier s146 00:18:55.360 --> 00:19:06.160 part of that economy as possible right it's the most agentically leveraged companies that are not only outd disrupting their space but kind of defining an entirely new playbook for how companies in this new era will be run. s147 00:19:06.160 --> 00:19:12.480 And I think the leverage we're already seeing from some of these uh these companies that are running in this way like Gary said like it's profound. s148 00:19:12.480 --> 00:19:17.200 I mean it's far more than even being like an early software leveraged or internet leveraged company. s149 00:19:17.200 --> 00:19:29.760 So really really you know kind of big believer that this subset of the economy is going to have explosive growth far higher than any other sector and it's going to cut across not just you know the tech industry, software industry but every industry. s150 00:19:29.760 --> 00:19:30.240 Yeah. s151 00:19:30.240 --> 00:19:38.720 uh in my London keynote I always often talk about how uh work agents are eating the rest of work and being accessible to nontechnical teams. s152 00:19:38.720 --> 00:19:46.160 In fact, my team is right there back now because AIE runs on air table uh and they're so excited to meet you and so excited to to work with hyper agents. s153 00:19:46.160 --> 00:19:50.160 Um so from 500 founders we you guys pre-selected 20. s154 00:19:50.160 --> 00:19:52.559 They competed today in the startup battlefield. s155 00:19:52.559 --> 00:19:55.280 Uh three have emerged as finalists. s156 00:19:55.280 --> 00:19:56.880 Let's introduce them. s157 00:19:56.880 --> 00:20:00.320 Um, so I don't know if I'm supposed to to click this. s158 00:20:00.320 --> 00:20:03.760 Uh, but uh first of all, I'm just going to go and introduce uh our dear judges. s159 00:20:03.760 --> 00:20:08.000 I think uh we're going to have Howie, Theo, and Joshua. s160 00:20:08.000 --> 00:20:11.440 Um, thank you from Pan. s161 00:20:11.440 --> 00:20:16.720 Um, and uh we I think we'll we'll we'll sort of have them judging there. s162 00:20:16.720 --> 00:20:20.720 Uh, but also we're going to uh go into the format and the background as well. s163 00:20:20.720 --> 00:20:30.640 Uh so basically what we're going to do uh we um the Hyper Asian team has kindly put up $100,000 in prizes and basically what this is is a competition s164 00:20:30.640 --> 00:20:33.840 for whoever is going to be the most impressive uh winners. s165 00:20:33.840 --> 00:20:39.760 So uh 50k to the winners um 30k to runner up to 20k to second runner up. s166 00:20:39.760 --> 00:20:47.919 Uh we're going to have a hype video that is uh thankfully um created by hyperframes and hijen. s167 00:20:47.919 --> 00:20:54.400 uh we have founder pitches and Q&A with the judges and then we'll also get to the next uh uh pitch as well. s168 00:20:54.400 --> 00:20:57.440 So just three quick pitches back toback. s169 00:20:57.440 --> 00:21:07.840 Um and basically we decided that we really wanted some kind of judging in terms of like what is impressive and usage of this technology and like why it matters. s170 00:21:07.840 --> 00:21:14.799 Um it's not an investment pitch so much as like you know it's not like a VC pitch so much as like well why should you care? s171 00:21:14.799 --> 00:21:22.080 Why is this an interesting use of technology and and why um you know why are you like an interesting founder that people should know? s172 00:21:22.080 --> 00:21:26.480 Um and so I'm very excited to announce like the winning teams. s173 00:21:26.480 --> 00:21:33.520 Uh so I think first of all we're going to introduce um come on Spiro come on stage. s174 00:21:33.520 --> 00:21:33.840 All right. s175 00:21:33.840 --> 00:21:36.080 Thank you. s176 00:21:36.259 --> 00:21:38.259 [applause] s177 00:21:38.559 --> 00:21:41.919 Um I think you guys are going to take over and present. s178 00:21:41.919 --> 00:21:43.360 Yeah. s179 00:21:43.360 --> 00:21:45.360 All right. s180 00:21:45.360 --> 00:21:48.960 Do you have your clickers or you got you got your you're gonna kick it off? s181 00:21:48.960 --> 00:21:50.320 Okay. s182 00:21:50.320 --> 00:21:54.320 Hey everyone, I'm Spirro Anakos, one of the founders of Kamad. s183 00:21:54.320 --> 00:21:58.159 This is Dom and I'm Nick Nakos. s184 00:21:58.159 --> 00:22:00.159 We are the founders of Kamad. s185 00:22:00.159 --> 00:22:04.000 Kamad has agentified physical commodity trade. s186 00:22:04.000 --> 00:22:12.159 From the rice you eat to the gold chain you're wearing to the chip in your smartphone to the gas you're putting in your car to every single copper pipe s187 00:22:12.159 --> 00:22:14.000 running through our data centers. s188 00:22:14.000 --> 00:22:17.200 Physical commodities power the world. s189 00:22:17.200 --> 00:22:20.240 But the global trade system is broken. s190 00:22:20.240 --> 00:22:21.760 Trillions move annually. s191 00:22:21.760 --> 00:22:30.080 Yet hundreds of billions are lost annually due to fraud, fragmentation, and the sheer complexity of coordinating global trade. s192 00:22:30.080 --> 00:22:36.159 Kamad has taken that complexity and transformed it into an agentic execution layer. s193 00:22:36.159 --> 00:22:46.240 Our proprietary CFC state machine governs specialized agents that verify, execute, and settle trades entirely. s194 00:22:46.240 --> 00:22:49.600 And then, you know, people ask, why is this so complicated? s195 00:22:49.600 --> 00:22:57.200 And if you think about it, it's like, well, it's every country in the world, every resource, all of their different currencies, and all of their different banking laws. s196 00:22:57.200 --> 00:23:00.559 So, of course, it's inevitably going to be a disaster, right? s197 00:23:00.559 --> 00:23:05.200 But with AI, it's finally solvable. s198 00:23:05.200 --> 00:23:06.880 So, we're very excited to have you here. s199 00:23:06.880 --> 00:23:18.559 We also have our our first customer in the crowd out of the UAE U trading company based in Dubai and he moves several hundreds of millions of volume in in trade every single year and uh he's proved the product. s200 00:23:18.559 --> 00:23:21.360 So, we're excited to be here today and thank you for the opportunity. s201 00:23:21.360 --> 00:23:23.026 Talk to the judge. s202 00:23:23.026 --> 00:23:25.026 [applause] s203 00:23:25.200 --> 00:23:28.799 17 trillion dollars in physical commodities move every year. s204 00:23:28.799 --> 00:23:30.240 The world runs on them. s205 00:23:30.240 --> 00:23:33.440 Yet it still moves on paper, email, and a handshake. s206 00:23:33.440 --> 00:23:35.919 No one knows who is real or if the documents are. s207 00:23:35.919 --> 00:23:38.080 The result, billions lost. s208 00:23:38.080 --> 00:23:40.640 Commod plugs into the stack you already run. s209 00:23:40.640 --> 00:23:44.320 Gmail, Slack, Stripe, Salesforce, WhatsApp, and more. s210 00:23:44.320 --> 00:23:45.440 A deal begins. s211 00:23:45.440 --> 00:23:47.039 Agents screen both sides. s212 00:23:47.039 --> 00:23:50.080 KYC identity sanctions in seconds. s213 00:23:50.080 --> 00:23:52.400 Forensics catch document fraud instantly. s214 00:23:52.400 --> 00:23:54.080 A private deal room spins up. s215 00:23:54.080 --> 00:23:57.200 Shipping and logistics partners link in with live pricing. s216 00:23:57.200 --> 00:23:59.919 Then an agent swarm structures the deal in parallel. s217 00:23:59.919 --> 00:24:05.120 Compliance, legal, currency, banking, shipping, settlement, weeks of work in minutes. s218 00:24:05.120 --> 00:24:08.320 The swarm obeys one protocol, the CFC. s219 00:24:08.320 --> 00:24:10.080 Our patent filed state machine. s220 00:24:10.080 --> 00:24:13.200 Agents advance only by clearing every deny condition. s221 00:24:13.200 --> 00:24:15.360 It cannot move until the evidence is real. s222 00:24:15.360 --> 00:24:16.480 Settlement eligible. s223 00:24:16.480 --> 00:24:18.080 It never touches the funds. s224 00:24:18.080 --> 00:24:19.200 It emits the signal. s225 00:24:19.200 --> 00:24:22.720 Your bank moves the money 30 days closed in minutes. s226 00:24:22.720 --> 00:24:27.200 Commodities can't see the video on the confidence monitor. s227 00:24:29.181 --> 00:24:31.181 [applause] s228 00:24:36.799 --> 00:24:37.696 What happens now? s229 00:24:37.696 --> 00:24:37.760 [laughter] s230 00:24:37.760 --> 00:24:39.440 I don't know. s231 00:24:39.440 --> 00:24:40.559 Is it on me? s232 00:24:40.559 --> 00:24:40.880 Yes. s233 00:24:40.880 --> 00:24:43.600 Um I I I realized that we didn't get you a mic. s234 00:24:43.600 --> 00:24:46.320 So uh are you're still miked up at the end of miked up? s235 00:24:46.320 --> 00:24:47.039 Oh, you're all miked up. s236 00:24:47.039 --> 00:24:47.520 Okay, great. s237 00:24:47.520 --> 00:24:50.080 Um, so I think we have a little bit of a Q&A session. s238 00:24:50.080 --> 00:24:52.080 Yeah. s239 00:24:53.360 --> 00:24:55.440 So, are we supposed to ask questions or what? s240 00:24:55.440 --> 00:24:57.120 Exactly. s241 00:24:57.120 --> 00:25:00.159 My team agreed to this, not me. s242 00:25:01.279 --> 00:25:03.520 Wait, why are you guys playing this? s243 00:25:03.520 --> 00:25:05.360 Joshua, you want to go? s244 00:25:05.360 --> 00:25:07.039 Uh, sure. s245 00:25:07.039 --> 00:25:11.919 I I'm very interested in the um the second project, common.io. s246 00:25:11.919 --> 00:25:15.032 And you know, certainly we need a share space for agent to s247 00:25:15.032 --> 00:25:15.120 [music] s248 00:25:15.120 --> 00:25:16.640 collaborate together. s249 00:25:16.640 --> 00:25:22.237 Just curious, have you thought about having that format to be HTML versus a markdown file or how s250 00:25:22.237 --> 00:25:22.240 [music] s251 00:25:22.240 --> 00:25:24.799 you've been thinking about it? s252 00:25:24.799 --> 00:25:26.559 Sorry. s253 00:25:26.559 --> 00:25:26.880 All right. s254 00:25:26.880 --> 00:25:27.919 Sure. s255 00:25:27.919 --> 00:25:28.159 Yeah. s256 00:25:28.159 --> 00:25:28.480 Don't s257 00:25:28.480 --> 00:25:28.720 Yeah. s258 00:25:28.720 --> 00:25:30.752 I was just saying that you know um s259 00:25:30.752 --> 00:25:31.039 [music] s260 00:25:31.039 --> 00:25:34.400 um the second project common.io is about s261 00:25:34.400 --> 00:25:35.039 That's the next one. s262 00:25:35.039 --> 00:25:35.200 Yeah. s263 00:25:35.200 --> 00:25:35.760 Oh, the next one. s264 00:25:35.760 --> 00:25:37.200 We're talking about the first one. s265 00:25:37.200 --> 00:25:40.320 Uh so I'll ask a question. s266 00:25:40.320 --> 00:25:51.200 This is one of those types of products that's really hard to build because it requires so much domain specific knowledge as well as like the building out of all of these pieces to collect the information needed for the product. s267 00:25:51.200 --> 00:25:58.960 A lot of the concern I have with modern startups is the thing that they're building is eventually going to be a feature of a sufficiently intelligent model. s268 00:25:58.960 --> 00:26:09.679 Do you see a future where the models get capable enough and the tools they're given by Anthropic and OpenAI could compete with you guys if they were to get smart enough and build in the right directions? s269 00:26:11.200 --> 00:26:15.360 So in commodities trade, it's very specific as to what data is being pulled. s270 00:26:15.360 --> 00:26:19.679 And what we've done with our orchestration layer is set the gates for each agent. s271 00:26:19.679 --> 00:26:23.600 So they're pulling from real databases and have that context themselves. s272 00:26:23.600 --> 00:26:33.120 Whereas you're talking about gold, oil, grain, whatever it may be, there's certain procedures that only industry experts really know and have the documents and the information to pull that in. s273 00:26:33.120 --> 00:26:37.360 Which is why we've partnered with Connor and a few other partners to bring in all that data. s274 00:26:37.360 --> 00:26:43.279 uh and I have domain experience as well to know what's real, what's not and to train the agents based upon that. s275 00:26:43.279 --> 00:26:45.600 So to your question, could that happen? s276 00:26:45.600 --> 00:26:57.120 They can learn more for sure on the open internet, but this is a private industry with a lot of sensitive information and they have to learn upon and train upon certain data in order to progress and become experts in that domain. s277 00:26:57.120 --> 00:27:00.640 So it sounds like relatively bespoke in the sense that like every company's a bit different. s278 00:27:00.640 --> 00:27:02.799 You need to get everything for them. s279 00:27:02.799 --> 00:27:11.120 How many customers would it take for this to become a billion dollar company or to hit like I don't know 100 mil ARR like how many customers you think it would take to get there? s280 00:27:12.240 --> 00:27:15.360 It's about 100 uh 100 customers total s281 00:27:15.360 --> 00:27:17.360 huge. s282 00:27:17.360 --> 00:27:22.799 It's also important to mention as well like the tickets in this industry are massive on on deal sizes. s283 00:27:22.799 --> 00:27:25.600 It's not like a stripe for example processing microtransactions. s284 00:27:25.600 --> 00:27:30.880 One transaction might be you know $200 million or north of that. s285 00:27:30.880 --> 00:27:36.400 and one partner such as a refinery, many of them transact nine to 12 billion dollars a month. s286 00:27:36.400 --> 00:27:44.720 So getting in at that level, charging per deal on that changes the whole landscape of what we're able to earn and what we're able to be valued at. s287 00:27:44.880 --> 00:27:46.720 I just want to add one more piece as well. s288 00:27:46.720 --> 00:27:48.480 Our solution is end to end. s289 00:27:48.480 --> 00:27:55.360 So you know the solution serves the entire supply chain, but the wedge ultimately into the industry is the traders and the banks. s290 00:27:55.360 --> 00:28:00.240 Banks pulled out of physical commodities trading years ago after the fraud became so rampant. s291 00:28:00.240 --> 00:28:08.159 So this unlocks a tremendous amount of liquidity as well by the audit trails and the immutability that we give uh into the commodity and the trade itself. s292 00:28:08.159 --> 00:28:10.559 So there's a lot to love about this business. s293 00:28:10.559 --> 00:28:17.679 I think like in many ways it's like check checks all the boxes on like the classic like here is the ideal vertical agent business to build. s294 00:28:17.679 --> 00:28:24.880 Like if you look at the the YC kind of like RFS for vertical agents like this is like the perfect application in the right the right kind of sector. s295 00:28:24.880 --> 00:28:32.320 like there's lots of money up for grabs and there's a lot of like domain specific stuff that you have to do that creates I think a good defensible moat. s296 00:28:32.320 --> 00:28:48.159 Um I think my perspective is more like you know what do you do to keep up with the changing competitive landscape and just you know as models progress how do you need to evolve your product to stay competitive right so it's less about is this a relevant and great business today and more about what changes over the s297 00:28:48.159 --> 00:29:00.000 next two three years or even like next year that impacts you in a way that you know it doesn't necessarily mean like enthropic opening eye eats your lunch but what do you need to do to stay you know kind of at the frontier and be a better product. s298 00:29:00.000 --> 00:29:06.480 Yeah, I think like the only thing that's actually defensible is being the most creative in your category regardless of which product you're creating, right? s299 00:29:06.480 --> 00:29:09.279 Like truly nothing's defensible other than being the most creative. s300 00:29:09.279 --> 00:29:14.159 Like anybody these days has a product, but we actually do like the anthropic eat your lunch model. s301 00:29:14.159 --> 00:29:18.799 Like we like the ship extinction model where we ship and then 10 companies go extinct the next day. s302 00:29:18.799 --> 00:29:24.720 So um yeah, it's aggressive shipping and product superiority, but then ultimately we're going to win on distribution. s303 00:29:24.720 --> 00:29:29.600 What are you most excited about on your upcoming road map if you can share? s304 00:29:30.080 --> 00:29:32.399 becoming the bank. s305 00:29:32.399 --> 00:29:33.679 Yeah, s306 00:29:33.679 --> 00:29:35.919 it's exciting. s307 00:29:36.159 --> 00:29:36.960 Thank you so much. s308 00:29:36.960 --> 00:29:38.000 Awesome. s309 00:29:38.000 --> 00:29:38.559 Give better off. s310 00:29:38.559 --> 00:29:39.520 Come on. s311 00:29:39.520 --> 00:29:41.760 Uh we're going to invite the next team on now. s312 00:29:41.760 --> 00:29:43.840 Uh if you want to come back here. s313 00:29:43.840 --> 00:29:44.559 Thank you. s314 00:29:44.559 --> 00:29:46.480 Appreciate it. s315 00:29:46.480 --> 00:29:47.200 Thanks. s316 00:29:47.200 --> 00:29:54.080 Um and up next we have Max Windbomb and the team from Common.io. s317 00:29:54.320 --> 00:29:56.640 Come on, Max. s318 00:29:56.640 --> 00:29:57.919 Oh, you're going to play the video. s319 00:29:57.919 --> 00:29:59.919 All right. s320 00:30:00.399 --> 00:30:03.279 All right, we'll play the video. s321 00:30:04.399 --> 00:30:06.799 That was the music. s322 00:30:06.799 --> 00:30:11.039 Oh, sorry. s323 00:30:22.799 --> 00:30:22.799 Heat. s324 00:30:22.799 --> 00:30:24.799 Heat. s325 00:31:00.876 --> 00:31:02.876 [music] s326 00:31:03.200 --> 00:31:04.799 All right, welcome in. s327 00:31:04.799 --> 00:31:06.080 Come on, guys. s328 00:31:06.080 --> 00:31:08.559 Oh, thank you. s329 00:31:09.039 --> 00:31:14.720 Um, if you could uh so we have a little bit of a technical snafu where the judges couldn't see the video. s330 00:31:14.720 --> 00:31:15.200 Okay. s331 00:31:15.200 --> 00:31:18.320 Uh, we have to describe a little bit just to just to prompt things off s332 00:31:18.320 --> 00:31:18.799 before s333 00:31:18.799 --> 00:31:20.960 you if you sort of before you get into the whole pitch. s334 00:31:20.960 --> 00:31:21.600 Yeah. s335 00:31:21.600 --> 00:31:22.080 Okay. s336 00:31:22.080 --> 00:31:24.000 Pretend like we're a non multimodal model. s337 00:31:24.000 --> 00:31:27.200 We just we only accept text. s338 00:31:27.360 --> 00:31:35.760 So, uh, yeah, text comment.io is a uh it's um multiplayer markdown editor. s339 00:31:35.760 --> 00:31:40.640 It's uh focused on making the best documents um for the modern work which is uh people and agents. s340 00:31:40.640 --> 00:31:47.200 But what you would have seen on the video is a familiar document editor interface, but people and agents are popping in. s341 00:31:47.200 --> 00:31:48.640 They're notifying each other. s342 00:31:48.640 --> 00:31:50.399 Everyone can call anyone in. s343 00:31:50.399 --> 00:31:54.000 Um and that's that's basically the gist. s344 00:31:54.000 --> 00:31:55.120 Awesome. s345 00:31:55.120 --> 00:31:55.679 All right. s346 00:31:55.679 --> 00:32:08.640 So, um, it's Friday afternoon, ready to go home, packing up your laptop, and all of a sudden you're hearing dings around the office, servers down, big outage. s347 00:32:08.640 --> 00:32:13.120 So, you put down your bag, you head into the conference room, and you're pulling out your laptop. s348 00:32:13.120 --> 00:32:15.200 There's one question on your mind. s349 00:32:15.200 --> 00:32:18.080 What is going on, Claude? s350 00:32:18.080 --> 00:32:20.080 And you're entering that in. s351 00:32:20.080 --> 00:32:21.840 You're waiting a few minutes. s352 00:32:21.840 --> 00:32:22.720 Give me some ideas. s353 00:32:22.720 --> 00:32:24.720 It's culminating or whatever. s354 00:32:24.720 --> 00:32:34.880 And then it gives you some ideas and the first thing you do is you tell everyone else in the room the ideas so they can put it into their clouds and then someone else has a different idea and then they let you know and then you put it into your cloud s355 00:32:34.880 --> 00:32:37.360 and then you real how did we get here? s356 00:32:37.360 --> 00:32:39.279 How is this the job? s357 00:32:39.279 --> 00:32:41.600 There has to be a better way and there is. s358 00:32:41.600 --> 00:32:48.720 It's agents and the who are doing the work and people who own the problem sharing context in real time. s359 00:32:48.720 --> 00:32:50.080 But how? s360 00:32:50.080 --> 00:32:53.919 Think of the productivity software that you all use the collaboration software. s361 00:32:53.919 --> 00:32:58.480 Can you just like drop your coding agents into them and have them working with each other? s362 00:32:58.480 --> 00:33:03.120 No, you can't because they were built for people, not for agents. s363 00:33:03.120 --> 00:33:05.600 And that's why we're making Comet. s364 00:33:05.600 --> 00:33:08.559 It is the multiplayer markdown editor. s365 00:33:08.559 --> 00:33:15.200 It is we're laser focused on making it the best document platform for modern work for people and for agents. s366 00:33:15.200 --> 00:33:15.840 It's open. s367 00:33:15.840 --> 00:33:16.559 It's pluggable. s368 00:33:16.559 --> 00:33:17.919 That's key for enterprises. s369 00:33:17.919 --> 00:33:20.880 It's key for it's key for developers. s370 00:33:20.880 --> 00:33:24.720 and it's wrapped in a user experience that is super familiar. s371 00:33:24.720 --> 00:33:29.360 I started my career in productivity bringing collaboration features into Microsoft Word. s372 00:33:29.360 --> 00:33:37.919 Max and I worked together um at Texio, the first AI native writing software six years before chat. s373 00:33:37.919 --> 00:33:42.080 We were deploying companywide rollouts of AI writing software to the Fortune 500. s374 00:33:42.080 --> 00:33:44.720 We've been doing this a long time. s375 00:33:44.720 --> 00:33:48.240 The market for comment is expanding with agents. s376 00:33:48.240 --> 00:33:59.279 As more and more people use agents, more people are going to need the ability for agents to share context in a product that is built for agents but designed for people working together s377 00:33:59.279 --> 00:34:03.039 even in the highest stake circumstances. s378 00:34:03.120 --> 00:34:04.559 Awesome. s379 00:34:04.559 --> 00:34:10.560 I love the shape of this business because it's like the inverse of what we just heard from the um the commod guys, right? s380 00:34:10.560 --> 00:34:12.240 Like they went super vertically deep. s381 00:34:12.240 --> 00:34:26.079 they're trying to extract a lot of value out of a very deep um you know domain and you guys are going super broad and arguably maybe a little thinner but by intention right and I don't say that as a as a detriment at all like I think you know one way to think about the landscape here is s382 00:34:26.079 --> 00:34:36.560 like the agent economy is going to be so large there's just so much money flowing through agents like literally the token spend right and if you can be a product that like even a one to you know 2% s383 00:34:36.560 --> 00:34:45.119 uh amount of those tokens touches like you could be a very valuable even if like the per uh per or per usage um you know kind of uh metric s384 00:34:45.119 --> 00:34:56.320 uh you know kind of margin extraction or revenue is is relatively low you can be a very cheap very fast very um broad product and still gain a lot of scale right so I think it's a really really interesting shape of product s385 00:34:56.320 --> 00:35:07.440 um what have you found is like the most surprising learnings from like a product design or product affordances standpoint to make this product better for agents than like the human design equivalents right like why not just have agents s386 00:35:07.440 --> 00:35:14.720 collaborate on a Google doc right or even try to use like GitHub as the uh uh you know kind of repo not just for code but for markdown. s387 00:35:14.720 --> 00:35:20.400 All writing software today is horrible for agents to use. s388 00:35:20.400 --> 00:35:24.000 Software like Google Docs has a really terrible format. s389 00:35:24.000 --> 00:35:25.680 It has an MCP. s390 00:35:25.680 --> 00:35:27.760 You can send a document there. s391 00:35:27.760 --> 00:35:33.920 You can have your agent read a document from there, but you can't have them collaborate in real time. s392 00:35:33.920 --> 00:35:38.720 And that's critical for all kinds of real work that needs to happen. s393 00:35:38.720 --> 00:35:43.760 And as more agents join the workforce, they need to be in there with your documents. s394 00:35:43.760 --> 00:35:55.200 And as we've talked to our users, people who love working in documents, who rely on documents for their day-to-day, need to bring their agents because they're starting to use agents, too. s395 00:35:55.200 --> 00:35:58.240 It's not just developers anymore. s396 00:35:58.240 --> 00:35:58.720 Okay. s397 00:35:58.720 --> 00:35:59.200 I think s398 00:35:59.200 --> 00:36:00.079 I'll mention it. s399 00:36:00.079 --> 00:36:01.920 Oh, final closing words. s400 00:36:01.920 --> 00:36:15.520 I was just going to say the other thing I'll mention is that I've been super surprised about um talking to people at this conference when we've talked to them is how many people have said I've rolled my own like visual markdown editor that other people can look at so people can look and s401 00:36:15.520 --> 00:36:25.760 then you're like ah but I gave up I just rendered an HTML document instead like it's a hard problem and you need dedicated like focus on making it great and that's kind of what we're doing. s402 00:36:25.760 --> 00:36:25.920 [snorts] s403 00:36:25.920 --> 00:36:26.720 Awesome. s404 00:36:26.720 --> 00:36:28.720 All right, nice job guys. s405 00:36:28.720 --> 00:36:30.345 Thank you so much. s406 00:36:30.345 --> 00:36:31.200 [applause] s407 00:36:31.200 --> 00:36:34.800 Uh next for and last team to compete. s408 00:36:34.800 --> 00:36:38.079 We're going to play the video by Foundry. s409 00:36:52.480 --> 00:36:55.235 Content creators don't have time to build a business, s410 00:36:55.235 --> 00:36:55.359 [music] s411 00:36:55.359 --> 00:36:57.520 so they have to hire an agency. s412 00:36:57.520 --> 00:37:00.560 It's expensive, slow, and risky. s413 00:37:00.560 --> 00:37:01.130 Built by s414 00:37:01.130 --> 00:37:01.200 [music] s415 00:37:01.200 --> 00:37:07.599 Foundry replaces the agency and lets creators launch their own products faster and cheaper. s416 00:37:07.599 --> 00:37:10.800 Our AI agents build the business end to end. s417 00:37:10.800 --> 00:37:12.480 The creator launches it. s418 00:37:12.480 --> 00:37:14.240 We keep growing the revenue. s419 00:37:14.240 --> 00:37:16.850 Type in any creator's handle and our s420 00:37:16.850 --> 00:37:16.960 [music] s421 00:37:16.960 --> 00:37:26.000 agents become their biggest fans, watching their videos, reading their comments, and finding a painkiller their audience would actually pay for. s422 00:37:26.000 --> 00:37:32.160 We've done this creators of every size and over half a million people use products our agents built. s423 00:37:32.160 --> 00:37:35.440 The cost of building software is approaching zero. s424 00:37:35.440 --> 00:37:40.240 What's left is trust and taste and no one has more of it than creators. s425 00:37:40.240 --> 00:37:45.920 We're building the agentic product team that is going to turn every creator into a founder. s426 00:37:45.920 --> 00:37:46.880 Woo! s427 00:37:46.880 --> 00:37:49.920 Foundry team, come on up. s428 00:37:51.359 --> 00:37:51.839 Thank you. s429 00:37:51.839 --> 00:37:52.640 Thanks, Max. s430 00:37:52.640 --> 00:37:54.000 Hello, AIE. s431 00:37:54.000 --> 00:37:55.599 I am Weston Belgettes. s432 00:37:55.599 --> 00:37:58.320 I'm the founder and CEO of Built by Foundry. s433 00:37:58.320 --> 00:38:03.520 We're going to turn every content creator into a founder of their very own company. s434 00:38:03.520 --> 00:38:05.599 And I have great news today. s435 00:38:05.599 --> 00:38:09.440 I think we found the formula for a winning business. s436 00:38:09.440 --> 00:38:15.839 You take your unique expertise and turn it into a product and you solve cold start with your built-in distribution. s437 00:38:15.839 --> 00:38:17.920 Theo, you you did this with T3 Chat. s438 00:38:17.920 --> 00:38:19.119 Yeah, it sucked. s439 00:38:19.119 --> 00:38:19.731 It doesn't work. s440 00:38:19.731 --> 00:38:20.240 [laughter] s441 00:38:20.240 --> 00:38:27.520 It works great for our our our users, but uh Gary did it with with G uh GStack and GBrain. s442 00:38:27.520 --> 00:38:41.200 And uh what what we find is that if we help uh creators to take a step back and solve a real pain point that their users have, so we're not just making another Patreon for that, paywalling this content. s443 00:38:41.200 --> 00:38:43.599 We're helping them solve a real pain point behind that. s444 00:38:43.599 --> 00:38:50.240 And that's what our agents are experts in is finding the pain point within the users's problems. s445 00:38:50.240 --> 00:39:00.720 And our companies have uh built over uh many different niches and uh different sizes of shape and shapes of creators. s446 00:39:00.720 --> 00:39:06.000 And really what we're building is we want to give the power back to the content creator. s447 00:39:06.000 --> 00:39:19.280 They're stuck in these I worked at Tik Tok for two years and and I met with hundreds of creators who are stuck just doing brand deals or affiliate links or selling $20 PDFs in their link in bio and they are one step away from building s448 00:39:19.280 --> 00:39:20.480 their own business. s449 00:39:20.480 --> 00:39:23.680 They just need someone to help them and that's what our agents do. s450 00:39:23.680 --> 00:39:35.839 At Built by Foundry, we deploy teams of agents to build recurring revenue businesses for content creators so that they can focus on posting and posting and posting and we can keep growing their revenue. s451 00:39:35.839 --> 00:39:37.200 I have a lot of thoughts on this one. s452 00:39:37.200 --> 00:39:37.760 Okay. s453 00:39:37.760 --> 00:39:47.839 So, the problem I find as a creator, even with the brands I work with, is that there is a saturation point where it stops being useful to talk about a given product with my audience. s454 00:39:47.839 --> 00:39:58.400 Like with me, for Versel, for example, there was quickly a point where everybody in my audience either was a Verscel user and doesn't want me to show it to them anymore or they won't be a Verscell user and they don't want me to talk about it anymore. s455 00:39:58.400 --> 00:40:05.440 It is very easy to hit the saturation point and the best solution is to have a much broader set of things to show your audience. s456 00:40:05.440 --> 00:40:06.960 One of the best things I ever did for myself. s457 00:40:06.960 --> 00:40:14.960 The single moment that has had the most positive impact on myself, my career, my businesses, and my income has been going from having four sponsors to 80. s458 00:40:14.960 --> 00:40:18.560 Because now there's a wider variety of things to bring my audience. s459 00:40:18.560 --> 00:40:24.960 And even if 80% of them aren't relevant to them, the 20% that is is now conversion I'm getting that I wouldn't have otherwise. s460 00:40:24.960 --> 00:40:29.839 The variety of what I bring to my audience is where I find the most value by far. s461 00:40:29.839 --> 00:40:33.359 And every creator I've worked with ultimately has come to a similar conclusion. s462 00:40:33.359 --> 00:40:36.560 That said, you're touching on really important pieces here. s463 00:40:36.560 --> 00:40:39.119 Creators do have more taste than most founders. s464 00:40:39.119 --> 00:40:41.599 Creators do have better distribution than most companies. s465 00:40:41.599 --> 00:40:44.079 Creators know their audience better than most businesses. s466 00:40:44.079 --> 00:40:52.800 And you've built a machine that identifies that, but it doesn't provide the solution to that other problem, which is you have to bring variety to your audience. s467 00:40:52.800 --> 00:41:04.640 Where I could see this working really well is as a tool that businesses use when they identify a creator is overlapping with the archetype of customer they're looking for to help that business build better things for Theo. s468 00:41:04.640 --> 00:41:08.000 And I've told this to so many businesses that want to work with me. s469 00:41:08.000 --> 00:41:13.040 Watch my streams, watch my videos, find the problems I have, and then show me how your product solves them. s470 00:41:13.040 --> 00:41:16.560 That's a way better pitch than going to try and start your own company as a YouTuber. s471 00:41:16.560 --> 00:41:20.800 As the YouTuber who has started the second most companies, as far as I'm aware, it doesn't work. s472 00:41:20.800 --> 00:41:23.280 It just burns you out and it burns your audience out too. s473 00:41:23.280 --> 00:41:32.000 The best thing you can do is work with companies to teach them what your audience wants and for them to come to you with money to show it to those audience or those audience members. s474 00:41:32.000 --> 00:41:38.640 I understand and I will say your niche as a tech creator is one that is very challenging because there's a lot of options. s475 00:41:38.640 --> 00:41:44.000 Um and what we have found is that for all of our creators, I'll just few examples. s476 00:41:44.000 --> 00:41:56.720 Um, one one creator's name is Brandon and he does homesteading content and he always loses track of uh the best settings on his freeze dryer, which sounds ridiculous to us, but to his 2 million followers, that's a real pain point. s477 00:41:56.720 --> 00:42:04.640 And now they pay him a recurring revenue monthly or monthly or yearly subscription to solve that specific painoint. s478 00:42:04.640 --> 00:42:07.119 So, I think unfortunately Theo, you've picked a bad niche. s479 00:42:07.119 --> 00:42:13.520 I'm sorry, but um if you want to pivot to homesteading or gardening, m maybe uh we could we could work together. s480 00:42:13.520 --> 00:42:23.440 But I I'd say primarily whatever the user's niche is, apart from tech and maybe com comedians, we've been able to take a step back. s481 00:42:23.440 --> 00:42:34.240 Our agents find a painoint that they're willing to pay for and zero creators across our entire company history have ever left our our company because they always are profitable. s482 00:42:34.319 --> 00:42:35.839 You're very convincing. s483 00:42:35.839 --> 00:42:36.560 [laughter] s484 00:42:36.560 --> 00:42:36.960 Okay. s485 00:42:36.960 --> 00:42:37.359 Excellent. s486 00:42:37.359 --> 00:42:39.839 Then give it up. s487 00:42:40.319 --> 00:42:40.640 Yeah. s488 00:42:40.640 --> 00:42:41.734 Thank you. s489 00:42:41.734 --> 00:42:42.640 [applause] s490 00:42:42.640 --> 00:42:45.839 Um, so we're going to have a little bit of a deliberation moment. s491 00:42:45.839 --> 00:42:48.400 Uh, the judge is going to go backstage for a couple minutes. s492 00:42:48.400 --> 00:42:51.040 In the meantime, sorry. s493 00:42:51.040 --> 00:42:51.359 Okay. s494 00:42:51.359 --> 00:42:55.839 In the meantime, we've, uh, prepared this little video recapping the World's Fair. s495 00:42:55.839 --> 00:42:58.560 So, take your time, judges. s496 00:43:00.729 --> 00:43:02.729 [music] s497 00:43:29.119 --> 00:43:30.859 This is our biggest AI engineer. s498 00:43:30.859 --> 00:43:31.119 [music] s499 00:43:31.119 --> 00:43:33.680 event ever. s500 00:43:40.160 --> 00:43:41.340 We're constantly adding s501 00:43:41.340 --> 00:43:41.440 [music] s502 00:43:41.440 --> 00:43:44.880 new techniques for you to draw. s503 00:43:55.095 --> 00:43:57.095 [music] s504 00:44:36.360 --> 00:44:38.360 [music] s505 00:45:08.560 --> 00:45:10.319 Thank you so much. s506 00:45:10.319 --> 00:45:11.200 All right. s507 00:45:11.200 --> 00:45:15.119 Um, I think we're inviting everyone back on stage. s508 00:45:15.119 --> 00:45:18.880 Give it up for the start of Battlefield. s509 00:45:18.880 --> 00:45:22.800 Um, congrats, guys. s510 00:45:22.800 --> 00:45:23.520 Yes. s511 00:45:23.520 --> 00:45:24.000 Okay. s512 00:45:24.000 --> 00:45:27.440 So, uh, we have some prizes that we're going to hand out. s513 00:45:27.440 --> 00:45:30.960 I think, um, the folks back there are doing some checks. s514 00:45:30.960 --> 00:45:37.760 Um, in second runnerup face, we have Kimode. s515 00:45:38.586 --> 00:45:40.160 [applause] s516 00:45:40.160 --> 00:45:42.079 Uh, Theo, I think you're presenting. s517 00:45:42.079 --> 00:45:45.440 Uh, yes. s518 00:45:45.440 --> 00:45:50.160 Okay, we'll take some pictures as well for the team. s519 00:45:53.760 --> 00:45:54.640 All right. s520 00:45:54.640 --> 00:45:58.960 U, next, and I guess this also reveals the order. s521 00:45:58.960 --> 00:46:02.720 Uh, we have Foundry as runner up. s522 00:46:02.720 --> 00:46:02.821 Great s523 00:46:02.821 --> 00:46:02.960 [cheering] s524 00:46:02.960 --> 00:46:04.160 pitch, Max. s525 00:46:04.160 --> 00:46:05.441 Great pitch. s526 00:46:05.441 --> 00:46:07.441 [applause] s527 00:46:09.599 --> 00:46:10.480 All right, congrats. s528 00:46:10.480 --> 00:46:11.359 Awesome. s529 00:46:11.359 --> 00:46:14.079 All right, no secrets now for the grand prize. s530 00:46:14.079 --> 00:46:15.520 Comment.io. s531 00:46:15.520 --> 00:46:16.000 Welcome. s532 00:46:16.000 --> 00:46:17.280 Great video as well. s533 00:46:17.280 --> 00:46:18.079 Congratulations. s534 00:46:18.079 --> 00:46:20.319 Well deserved. s535 00:46:24.319 --> 00:46:26.640 Do you want to also do the group photo? s536 00:46:26.640 --> 00:46:27.760 I think we're doing s537 00:46:27.760 --> 00:46:28.720 all of us. s538 00:46:28.720 --> 00:46:30.720 Um, s539 00:46:31.839 --> 00:46:32.480 yes. s540 00:46:32.480 --> 00:46:32.880 Okay. s541 00:46:32.880 --> 00:46:33.200 All right. s542 00:46:33.200 --> 00:46:34.640 What it mean just them? s543 00:46:34.640 --> 00:46:35.520 They're the founders. s544 00:46:35.520 --> 00:46:37.520 We're just here to com everyone. s545 00:46:37.520 --> 00:46:38.000 Oh, fine. s546 00:46:38.000 --> 00:46:40.480 We'll sneak it in. s547 00:46:40.640 --> 00:46:41.359 Get them. s548 00:46:41.359 --> 00:46:42.240 Come on in. s549 00:46:42.240 --> 00:46:43.040 Yes. s550 00:46:43.040 --> 00:46:45.119 All right. s551 00:46:46.800 --> 00:46:48.319 Thank you so much. s552 00:46:48.319 --> 00:46:50.480 You all had some building with hyper agent and s553 00:46:50.480 --> 00:46:51.280 Yeah, of course. s554 00:46:51.280 --> 00:46:53.119 Yeah. s555 00:46:53.119 --> 00:46:53.257 Um, s556 00:46:53.257 --> 00:46:53.599 [music] s557 00:46:53.599 --> 00:46:55.760 any last words that you wanted to comment on? s558 00:46:55.760 --> 00:46:57.920 I think you guys uh brief a little bit. s559 00:46:57.920 --> 00:46:58.160 Yeah. s560 00:46:58.160 --> 00:46:58.400 Yeah. s561 00:46:58.400 --> 00:47:02.079 I just want to thank uh sorry about the thank everyone here at AIE. s562 00:47:02.079 --> 00:47:12.000 We got amazing feedback um through the whole um time and uh Hyper Agent um for inviting us to this and Hyper fans for helping us with the video and uh s563 00:47:12.000 --> 00:47:13.680 overall like s564 00:47:13.680 --> 00:47:14.872 so much. s565 00:47:14.872 --> 00:47:15.760 [snorts] s566 00:47:15.760 --> 00:47:16.400 Check us out. s567 00:47:16.400 --> 00:47:18.560 It's free. s568 00:47:18.640 --> 00:47:34.880 comment.io I know.