Chris Pedregal
speaker
154 appearances
1 recordings
1 series
first heard Feb 2025
last heard Feb 2025
Chris Pedregal’s voice in public audio — every appearance, attributed to the second.
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Appearances
I'm speaking about granola right now because that's what we're building. Maybe it'll be us, maybe it was someone else, but I guarantee you a tool will be used by everyone basically in this context. As to what the norms are going to be, I personally hate the idea of a hidden pendant that is listening to everything. I know in Silicon Valley, that's one of the visions for the future.
And I personally don't like that vision. I think in a work context, the phone is great. because you basically put it down on the table and it is an easy social contract with the people in that meeting of what's happening. That's how we do work at Granola. Basically every meeting at Granola, it's very clear if there's a phone out and whose phone is taking notes.
And I think the social contract really matters. It's up to the individual to manage this as it's up to the individual to manage everything in the work environment. I think if you put the phone out and you're upfront about it, everyone benefits. And I think that change will happen, I think, much faster than you expect. Whereas I think in social circles, it will be very different.
The two defining characteristics that are different about this space in this moment are one, the speed at which the technology is getting better is nuts. And two, where Grinola is built on top of LLM, so it's an app layer product, we get so much benefit from writing these incredible technological advancements that are happening at the LLM layer. So we spend a lot of our time
really thinking about what makes a great user experience end to end. And if we weren't building on top of this foundational technical layer like LLM, we'd need a massive team to be able to do what we're doing today. So we really do benefit from that. That said, A lot of what makes Granola great is sweating the details of all these technical edge cases, stuff you'd never think of.
It's like you're in the middle of a meeting and you take off your AirPods and it's on a Zoom call that has multiple channels. And all of a sudden, Granola needs to do something very specific to make that feel seamless that you never would have thought of until you built it and you realize it felt crappy if you didn't do that.
We use as many AI tools as possible for as many things as possible inside of Granola. But some of the tools, at least on the development side, aren't quite there yet. We're so close to take that end to end. So we still have to do a lot of work there. Again, I hate doing time horizon guesses here because it's basically impossible to know.
If you fast forward us three years, I think the way we would work and what we would be able to outsource to AI would be completely different.
That's right. Our CTO, Voss, he has a goal, basically minimizing the number of lines of code every engineer writes at Granola every day is a goal of his. It's an active goal. We just did this offsite and the theme was, so the theme was basically use AI everywhere for things you wouldn't expect to. Just push ourselves outside of our comfort zone. And there's this great example.
We were, I was trying to barbecue some shrimp for the team. We bought some shrimp. This was in Spain. I've never barbecued shrimp before. I'm typing into chat GPT, like, okay, how do you barbecue shrimp? And Voss was like, no, give it the right context. So he's like, take a photo of the barbecue and take a photo of the shrimp. And he was totally right.
So I was like, yeah, yeah, yeah, give it the context. So I did this. Turned out the shrimp was already cooked. We didn't realize it because it was in Spanish. So we didn't have to cook it at all. We just needed to heat it up. Which never, ever would have figured out if I had just typed it in.
An interesting point there is there's just a completely different intuition you need to have around how you use these tools and you build with AI. Perhaps in a similar way where the web came along and people pre-web wouldn't automatically default to using Google. They'd go elsewhere versus people who had grown up, were young enough when that happened. would always default to using Google.
I think there's going to be a very, very, very similar divide here, which is basically the AI natives will just understand what context they need to give AI and how to work with AI. And actually, when in doubt, you should probably give it more context and see what it's going to say, as opposed to like, assume you know, right? And I'm 38.
I'm very happy the team is constantly pulling me like I'm literally at the forefront and thinking about this all the time. And I don't use AI as much as I should be using it. If that's the case for me, think about the general population.
Gathering the context, just getting all the data is not that hard. It's only a matter of time before you can plug in all your email into Anthropic or ChatGPT and all your nodes and all your company documents and all your tweets. And it'll have all that. I think there's a different question, which is which of that context is really relevant for the thing I'm about to do right now.
And that may be a technical problem. That may be a UI problem. I don't know. So that's on the context side. I do think a huge blocker for unlocking the power of collaborating with AI is what's the UI, what's the interface for collaborating with UI?
I really think we're in the terminal era with old school computers where you type in a command and then the computer would literally spit back a command. The way we work with ChatGPT, I don't think chat's going away, but I think it will feel archaic in how little control you really have as a user. I was looking this up. I was trying to find an analogy for this.
The first cars that came out, they didn't have steering wheels. They had basically a stick that you could turn like left to right. And it was fine if you were trying to go really slow. The moment you went fast, the stick was unusable. You'd move it too much and you'd crash off the road and it was a big security problem.
And then finally someone came up with a steering wheel and a steering wheel is a UI that gives you so much fine grain control when you're trying to turn. And I think we still have to invent what the steering wheel is for when you're working with AI and collaborating with AI. Right now we have some very coarse controls and it's turn taking right now.
It's like I write something, then the AI does something, then I react back to it. And I think it's going to be a lot more fluid and a lot more collaborative. Once we figure that out.
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