The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
00:32:14 · Mike Cannon-Brookes
[00:32:14] S0: Look. I think it's just incredibly positive. I suspect for those who want to use those models to achieve things, whether you're coding, doing architecture, improving business processes, whatever it is that you are doing, creating art, I think we should see that as a very positive thing. We are going to get higher value technology. We are gonna get better products and services for every consumer. It is going to be a creativity driven economy. One of the the phrases that I've I've liked the most recently, and I I give Didier, the the founder of Culture Amp, the the credit because it's his his phrase, I believe, or at least he's the first person who told me. We're moving from a world of information asymmetry to imagination asymmetry, which is such a great way of thinking about it. Right? It's no longer I know something that someone else doesn't, or I have a particular business knowledge. Those knowledges are becoming less about the asymmetric value than can I think about how to apply AI and these technologies to problems in unique ways? That's the creativity that we're all kinda having to see in business now, which is if you're a first principle thinker about business, it's awesome. Right? It's the most dynamic and exciting period that we've ever lived through in technology, maybe ever will. I get why it's scary. I also think it's it's imagination. You're applying new things in fundamentally new ways.
00:33:29 · Harry Stebbings, Mike Cannon-Brookes
[00:33:29] S1: If we live in this imagination asymmetry and you were to review the last twelve months, where do you think you have not shown enough imagination where you needed two more? [00:33:40] S0: That's a good question. I think the biggest problem I have is time, which is maybe what all of us have as our problem. I don't mean that in some big philosophical, like, life and death way. [00:33:50] S1: I'm a venture capitalist, my friend. I sit on the sides and throw shackles in when someone calls me. Time Yeah. [00:33:56] S0: You seem to work fairly hard and fairly long days on a lot of different things. Right? [00:34:00] S1: So Dude, dude, that's because I'm a podcaster. Terrible decision as well.
00:34:03 · Mike Cannon-Brookes
[00:34:03] S0: You have you have 50 instinct tasks running simultaneously. I haven't even had a chance to to install instinct yet. Heard about it. That what it is conceptually? So I think trying to carve out enough time to think is what I'm really trying to do at the moment. That deep long thinking. There's something about the time slicing of the world. You know, people talk about the move from, you know, movies to TV shows to YouTube to TikToks. Right? It's like, you know, books to to magazine articles to to newspapers to, like, tweets or whatever. Like, everything's getting shattered so much more. And in the agentic world, you can kind of get into this, like, push the agent, do the thing, push the agent, do the thing, push the agent. And sitting back and long thinking and still absorbing these changes and trying to look at them. We're living through a period of history, I think, where there's a lot of change on a day to day basis. But trying to see the year to year changes is much harder, and it requires sort of a a deep thinking, you know, that that I'm trying to create the space to do. I haven't had... It's been a hectically busy year. I haven't had a lot of time to do that, but I'm really, over the last two or three months, have been actively trying to do that. Even if it's only a couple hours a week, it's very easy to be busy. And I think in AI, even easier to be busy. Right? All of your agents and things running, your claws and instincts and muses and whatever are gonna keep attacking your attention. How do you create time for space for real thinking is is, I think, going to be something I need to get better at.
00:35:29 · Harry Stebbings, Mike Cannon-Brookes
[00:35:29] S1: Mike, just to give you context, my instinct is an automation to buy Laura Piana shoes for my girlfriend. This is not some incredibly intelligent, sophisticated workflow just to give you some boundary. Maybe in Silicon Valley, they're doing some things, man. Mine is just, like, buying Brunello cucinelli. [00:35:45] S0: I think you'd be surprised. I think a lot of the agentic, consumer use cases, right, people have talked about how much of it is basically, like, shopping and travel. [00:35:53] S1: Dude, if you're an aggregator or you're an advertising engine, I... Good luck. A question for you. You know, we see a lot of data marketplaces, whether it's your Macaws or your Surgeons paying for a huge amount of data from small companies, medium sized companies. You talked about the context graph earlier. Data feeds that context graph. How do you think about the cost of data, the cost of acquiring data, and what this market looks like as we evolve?
00:36:21 · Mike Cannon-Brookes
[00:36:21] S0: Look. I think it's a little bit different. The corporate decisions and knowledge that underlie the teamwork graph are about us trying to help a company that has made decisions, projects, documents, data often. For example, how many times are PowerPoint slides the place where people put actual facts and figures? A lot. Like, data is stored in databases. I'm like, yeah. There's a lot of data stored in PowerPoints, and it didn't actually ever make it to a database. How do we take all of that organizational knowledge, history, decision making, wrap it into a social graph of the people in the organization, and add code, the technological services created by a company, and mix all that together so we can give you great answers and learnings and decisions. And there's lot of inference we can apply on top on behalf of the company as well as being a continual self learning. Right? The Teamwork Graph's job is to infer ahead of your agent before your agent is asked a question to infer the best possible answer to that. Think about it like Google's index of the web. It doesn't go and crawl all of those websites to answer your question. It does that in advance. It has a lot of really smart indexing and inference technology to create an index so that it can answer questions very cheaply and at scale. That's our job, but tailored for every single company that has a wholly different set of information. That's very unique to each individual company. I don't think they're going to sell that information. I'm not sure it's particularly useful. I know we saw Makar or Google, I forget who actually end up winning buying the Sabb. It was
00:37:52 · Harry Stebbings
[00:37:52] S1: Spirit.