The Age of the Agent: Flo Crivello
00:00:00.000 | I'm going to talk about the future that awaits us, and not the super distant future either,
00:00:21.300 | like I'm talking about 5, 10 years, certainly within our lifetimes.
00:00:26.180 | The future that awaits us once agents have fully realized their potential.
00:00:32.440 | If I had to describe it in one sentence, I'd say that it's a world where a 25-year-old
00:00:39.200 | can have the same or more business impact as the Coca-Cola company.
00:00:44.300 | It sounds insane when you say it this way, but there's actually a precedent to it.
00:00:48.800 | It's happened before with media.
00:00:52.180 | Consider what Oprah had to do to build her media empire, right?
00:00:56.440 | She had to go and pitch a bunch of CNN executives in some stuffy room and raise money, hire a crew,
00:01:03.520 | find cameraman.
00:01:07.240 | And obviously, the internet and apps like YouTube have brought that friction down to zero.
00:01:13.520 | And it's brought that friction down so much that it actually sounds like a joke.
00:01:17.780 | Consider the top YouTuber, Mr. Beast, he's got a much greater reach than Oprah.
00:01:25.940 | He actually has more of a reach than the Super Bowl.
00:01:28.780 | And it's just him and his laptop is how he got started.
00:01:33.780 | So it happened before, even weirder, Ryan's World.
00:01:38.040 | He started when he was three years old, making videos on YouTube of him unboxing and reviewing toys.
00:01:45.120 | Today, he's 12 years old and he's worth $100 million.
00:01:50.220 | My point is that once you bring the friction down to zero, and once you remove the gatekeepers, you don't just get the same kind of content, except cheaper.
00:02:05.480 | The nature of the content changes when you remove the gatekeepers.
00:02:12.480 | Right, look at Oprah, look at the Super Bowl, that makes sense.
00:02:14.980 | It's like a talk show, it's like a sports game.
00:02:18.520 | Ryan's World and Mr. Beast is just weird.
00:02:21.820 | And so my point is that we're about to see the exact same transformation happen to the world of business at large.
00:02:29.240 | We're going to take the friction down to zero.
00:02:32.040 | And as a result, we are going to see much weirder, more creative ideas come to life.
00:02:41.580 | You know, Lindy is my second startup.
00:02:43.140 | Before it, I had another one called Teamflow.
00:02:45.720 | And I remember when I started it, I had a perhaps naive understanding of what starting a business entailed.
00:02:50.420 | I thought it was all about building a cool product and bringing it to market.
00:02:55.240 | And then I found out that's actually the fun part, right?
00:02:57.520 | Before you get there, people -- I see the founders laughing in the audience.
00:03:01.720 | Before you get there, you've got to meet with lawyers and incorporate, and meet with bankers and open a bank account,
00:03:06.920 | and meet with VCs and raise money, and meet with recruiters and hire a team, and it goes on and on.
00:03:10.680 | And I mean, you guys know, once you have a business, it's not much easier.
00:03:13.740 | It just keeps going.
00:03:17.720 | So when that wave of generated AI came about, all these amazing products that we're seeing that generate copywriting for you,
00:03:24.240 | generate images, I was like, that's awesome.
00:03:26.240 | But it doesn't solve my problem of it's just too darn painful to start a business.
00:03:31.240 | And also, the GDP isn't made of copywriters or illustrators.
00:03:36.300 | It's made of work and actions.
00:03:38.280 | So that's when I got interested in agentic AI, AI that can actually automate the menial parts of your life.
00:03:47.300 | There's this amazing movie, Office Space, by the same guy who made Silicon Valley, I highly recommend.
00:03:55.360 | And there's this awful, depressing character in there, named Milton.
00:04:00.400 | He spends his life in some basement doing God knows what, they call it filing TPS reports.
00:04:07.340 | And in the end, Milton does the most productive thing of his career, which is that he burns the building to the ground.
00:04:19.580 | That's what we're going to do, figuratively.
00:04:26.820 | The cops are coming.
00:04:29.180 | You know, I think this is a symbol that no one is happy with this status quo.
00:04:34.940 | People are always worried about, oh, robots are stealing people's jobs.
00:04:37.540 | I think it's people who have been stealing robots' jobs.
00:04:41.620 | Do you want to be Milton?
00:04:47.980 | And it's a huge problem when you look at the data.
00:04:51.720 | The average manager in the U.S. spends 15 hours every week on this kind of administrative task.
00:04:57.940 | That's $459 billion every year just in the U.S.
00:05:03.120 | That's more than the GDP of Norway.
00:05:08.060 | So that's where we start.
00:05:10.860 | We build an AI employee.
00:05:13.700 | The first thing it does very well is it acts as your personal assistant.
00:05:22.340 | We've called it Lindy.
00:05:25.660 | The good news is, as we've dug into that problem space, we found out there are three big time wasters.
00:05:31.440 | And you know the ones.
00:05:32.440 | No surprise there.
00:05:33.440 | This is where you spend your life at work and you hate it.
00:05:35.660 | So calendar, your email, your meetings.
00:05:38.160 | So the product we built, those are actual screenshots of the product.
00:05:41.900 | You can ask it to schedule your meetings for you.
00:05:45.000 | This example here is actually pretty cool because it demonstrates another ability of Lindy, which is she continuously learns from her interactions with you.
00:05:56.900 | So here I was like, help me find half an hour every week with Eric, and she called it Flo Eric, because previously I had asked her to find certain minutes with Eric tomorrow.
00:06:07.540 | And she did that, but she named the meeting meeting with Flo, and all my meetings are meeting with Flo, so it's not very helpful.
00:06:14.460 | And I was like, no, I gave her a little bit of feedback.
00:06:17.060 | I called it Flo Eric, and she did so, she renamed the meeting, and she saved the preference for future instances.
00:06:30.220 | And generally, I can give any arbitrary preference of any complexity that I want to Lindy, and she'll remember them and honor them.
00:06:42.820 | I can CC Lindy to my emails, so that she helps me schedule them.
00:06:50.480 | And when you use Lindy, she can pre-draft your replies for you in your inbox, in your voice, for each individual recipient.
00:07:00.860 | Because you don't talk the same way to your partner as you do to your investors, hopefully.
00:07:08.480 | So every morning I wake up, I open my Gmail, and I just have all the drafts ready for me to review.
00:07:15.140 | Lindy prepares me for my meetings, so I've asked her, "Hey, five minutes before every meeting, send me the Zoom link, the LinkedIn of the people I'm meeting with, and the summary of my last few emails with them."
00:07:28.140 | She just does that.
00:07:33.140 | Now, the really crazy thing is that we ourselves didn't actually build any of these features.
00:07:39.800 | What we did is we built a universal framework, allowing an AI to pursue any arbitrary goal using any arbitrary tool.
00:07:49.800 | And some very complex and sophisticated behaviors come out of that, as we'll see later.
00:07:57.800 | My pet peeve, every time people go on stage and they talk about their AI products, they always talk about the good part.
00:08:03.460 | It always works.
00:08:04.460 | It's very cherry-picked.
00:08:05.460 | And so I'm going to break that pattern a little bit today, and I'm going to talk about a time when it didn't work.
00:08:11.460 | A few weeks ago, I asked Lindy to help me work on my vocabulary, and every morning to send me a new interesting world.
00:08:19.460 | And so she does that, every morning I wake up, I have a new world in my inbox, that's great, I start to use them.
00:08:25.120 | Until one morning, I received this world, "pure liquidity," a captivating term denoting the act of meandering through a conversation with no fixed direction.
00:08:34.120 | And I paused for a minute on that one, I was like, "Pure liquidity."
00:08:37.120 | So I was like, "I didn't have heard of this one before, I just Googled it," and sure enough, it doesn't exist.
00:08:42.120 | So then I went back and re-Googled every wheel that she sent me, and none of them existed.
00:08:53.620 | So if I've used any wheel that doesn't exist today, that's why, she's been poisoning my brain.
00:09:02.780 | But when it works, it works great.
00:09:09.280 | And what it means for you when it works is that your computing experience of the future isn't one when you're in the basement, filing TPS reports all day.
00:09:22.780 | It's not one where you're working on your computer.
00:09:27.260 | It's one where you're having a conversation with your computer.
00:09:32.740 | So in flow state, you just focus on what you uniquely do best, and all the menial, awful parts of your work that you hate arrange themselves automatically for you.
00:09:46.240 | Now, I don't know about you guys. I think this is all awesome. I cannot wait for this to fully come to fruition.
00:09:52.240 | But it doesn't yet get you to the stage that I was talking about where a 25-year-old has more business impact than the Coca-Cola company.
00:10:01.740 | In order to get there, you have to go one step further.
00:10:05.740 | And instead of having just one Lindy work for you as your assistant, you can have an entire society of Lindys working together on your business to pursue your goals.
00:10:19.240 | If you want to realize how powerful that can be, consider the fact that every single item around you in the room right now was made by a group of people.
00:10:33.240 | Even the simplest of items, not one person can do it.
00:10:37.240 | In fact, there's this guy who ran this project called the toaster project.
00:10:41.240 | He wanted to see, can a single human make a very simple item like a toaster?
00:10:47.240 | He spent six months on it. It cost him $2,000, probably more like 50K if you include the value of his time.
00:10:54.740 | And this is what he ended up with in the end.
00:10:56.740 | Oh, he could have gone to Amazon and bought a perfectly fine toaster for 25 bucks.
00:11:03.740 | I think this contrast is a good illustration of the difference in abilities between one person, six months, 50K, pretty bad looking toaster.
00:11:16.740 | And a group of people, 25 bucks, perfectly fine toaster.
00:11:21.240 | I think the same thing happens to LLMs.
00:11:24.240 | You go to GPT-4, you ask it to do something like, hey, build an entire iOS app for me, soup to nuts.
00:11:30.240 | Design it, publish it to the app store, do everything.
00:11:34.240 | It can't, and then people conclude, oh, GPT-4 can't do it.
00:11:37.240 | Right? You got to wait for GPT-5, GPT-6, GPT-7.
00:11:40.240 | I think it's the same thing as if you went to some guy and you asked him, make a rocket for me, and you can't.
00:11:47.740 | And then you're like, oh, humans can't make rockets.
00:11:49.740 | And obviously they can, just got to let them work together.
00:11:53.740 | So that's exactly what we built, is a framework for multiple agents to work together in pursuit of your goals.
00:12:03.240 | This is what it looks like.
00:12:06.240 | The most awesome example that I know of is that we have created a society of Lindy's for Lindy to build herself.
00:12:16.740 | We need to build a lot of integrations for Lindy to work well with Slack, Twilio, Google Sheets, and so on and so forth.
00:12:26.740 | Instead, we are building this society of Lindy's.
00:12:30.240 | At the top level, there's this tool creation Lindy that takes an instruction like, hey, build a Slack integration.
00:12:36.240 | Talks to this Lindy that goes online and finds the open API spec and the online web documentation.
00:12:43.240 | Talks to this Lindy, that's a manager Lindy, just splits up the task across many engineers.
00:12:49.240 | The engineers work on the task.
00:12:50.740 | There's a specific engineer for the authentication code because there's a few gotchas here.
00:12:55.240 | And then they pass the work to a QA engineer in Lindy that does the work.
00:13:01.740 | And if it doesn't work, sends it back to the software engineer.
00:13:03.740 | If it works, submits a PR.
00:13:08.740 | This, for the record, is 70% or 80% of the way there.
00:13:11.740 | But I think it points to the future.
00:13:17.740 | So this is how you get to that future where a 25-year-old in his San Francisco studio can have more of a business impact than the Coca-Cola company.
00:13:33.240 | I think this is going to be the greatest equalizer of human history.
00:13:38.240 | Today, the best CMO in the world probably works for Apple or Nike or Coca-Cola.
00:13:44.740 | Not too long from now, the best CMO in the world is going to be an AI CMO.
00:13:48.740 | The same goes for the best designer in the world, the best engineer in the world.
00:13:54.240 | They're all going to be AI designers, AI engineers.
00:13:57.240 | They're going to work for you.
00:14:01.240 | We're all going to have the same lever of infinite strength to make change happen in the world.
00:14:10.240 | And the only question is going to be, can you use that lever?
00:14:12.740 | That's the only skill that's going to matter in the future.
00:14:17.740 | Imagine if you weren't constrained anymore by time, by money, by your team, by your network.
00:14:27.740 | Imagine if you could build anything, and it was just you, your laptop, and your Lindy's.
00:14:38.740 | Thank you.
00:14:40.240 | Thank you.
00:14:42.240 | Thank you.
00:14:43.240 | Thank you.
00:14:44.240 | Thank you.
00:14:45.240 | Thank you.
00:14:46.240 | Thank you.