The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
00:48:26 · Luke Harries, Harry Stebbings
[00:48:26] S1: Yes. [00:48:27] S0: Which is they crush it on Twitter for very specific clips. When you look at any of their view rates, very little. When you look at their retention on engagement rates, fuck all. But they have brilliant, and this is not a criticism, crush channel market fit. They have brilliant for Twitter for certain types of videos, but they also do volume. Yeah. It's a spray game. Clubhouse. [00:48:52] S1: We will see. I think they're still evolving what their actual product is, but they found this, as you said, like channel fit. And to jump back to the counter positioning, they've done the really... The funky thing of they're like, okay. They've counter positions against All In, where All In was like no ads. They're like, we're gonna be all ads. And they're like, TechCrunch is going more the vibe or maybe not TechCrunch, but traditional media is going more the vibe of being, like, anti tech. They're like, no. We're going to be completely pro tech. Others are going like, oh, we're only polished, button up, the clean cuts. They're like, no. We're going to be, like, streaming live content, the raw stuff. So... [00:49:25] S0: And, also, they're, like, smartly dressed. [00:49:27] S1: Smart... Yeah. Yeah.
00:49:27 · Luke Harries, Harry Stebbings
[00:49:27] S1: Smart... Yeah. Yeah. [00:49:28] S0: No tech broodies and stuff. They're like shirts and they look really formal. I think they've been really smart. So I didn't mean that as a takedown, but I I think it's interesting. Dude, we were breaking down the teams earlier. You have a weird element, which is, and you said this to me before, you don't have PMs. Yes. Why? Explain this to me. This is like the holy grail of product teams, don't it? [00:49:50] S1: And for context, Harry asked me this in front of an audience of about nineteen seconds. [00:49:54] S0: Only PMs. Yeah. Yeah. You guys raised your hand, and it was like, oh god. So
00:50:01 · Luke Harries
[00:50:01] S1: the reason we don't have PMs is our overall thesis is that engineers are building the product, and they should be responsible for the product. And with AI now, we're seeing much more like different traditional roles merging. And so engineers are going towards product engineers or engineers towards growth engineers. And what's fantastic is when you have product engineers and the engineers who are actually building the product, they own the road map, they can go from idea, and chances are their ideas are better and more right because they're the ones speaking to users and understand the context. So they can have better ideas. They then ship the product. They then get the results and analyze them, and they do that entire loop without needing anyone else's permission or anyone to slow them down. So that's why I think the ideal setup is engineers own the product, and they're responsible for it. Now we then, instead of having PMs or a separate marketing function, which is kind of like three separate functions, engineering product marketing, instead, we merge a lot of product with a lot of marketing and call that growth. And most of the team actually is ex PMs who are now doing growth, and so they're responsible for all the marketing as well. And so now each different product has an engineering lead, which is responsible for how great is the product overall, and they partner with the growth lead, which is responsible for particularly the awareness, the acquisition, and then they collab on the activation and retention pieces. How do you
00:51:28 · Harry Stebbings
[00:51:28] S0: prevent the growth role, which is a lot former PMs, just slipping into a PM role again and trying to actively manage product and kind of over engineer with the engineers?
00:51:39 · Luke Harries, Harry Stebbings
[00:51:39] S1: We keep the growth teams pretty small. And so, frankly, there's just not enough time to be meddling in the different engineers' work. You're not gonna be doing wireframes or going to be doing, like, large numbers of user interviews because you're too busy running the launches or running the channels for that particular product. So that's one. It's like we keep it pretty busy and lean. And the other one is if you hire great engineers, they just don't need it. And so the best engineers we hire, we put everyone through a product challenge, which is where we give them an imaginary product, and we ask them, step one, work out what features you should build. Like, imagine I'm a customer. Imagine you're doing research. They will actually go through on Google and find competitors and use that to shape the features. So step one is work out what features to build. Step two, they're then gonna turn that into the actual wireframes, and they'll be sketching out in Figma of, like, okay. This is what I think the product should look like. And then step three is you have system architectures. So they're like, okay. This is the different back end, the API design. And if you hire an engineer who, one, you know is really strong at coding because you've screened for that before, and two, you've then tested them through this full product loop. Like, you have confidence that they're able to take those products and those features from idea to launch. [00:52:50] S0: Do you think we will see PMs reduce as a role in future tech companies with AI becoming more and more prominent?
00:52:50 · Harry Stebbings, Luke Harries
[00:52:50] S0: Do you think we will see PMs reduce as a role in future tech companies with AI becoming more and more prominent? [00:52:56] S1: Yeah. I think PMs move to either growth. So you combine the PM role with marketing, and depending on your size and how strong your engineers are, you do more or less at the PM. Or many PMs will actually move towards product engineering, which is they're somewhat technical already. They can actually upscale themselves using tools like Cursor or Lovable and actually go and ship full end to end products. [00:53:19] S0: Can I ask you today, when you think about ElevenLabs code, how much of it do you think is AI generated? [00:53:24] S1: So I still write code probably 20% of the time. The only code I write is through Cursor, where I'm describing in the chat what I want done and then it executes on my behalf. And I'm probably more the extreme because I'm often doing, like, growth features which are adding on top of the core of the product. In terms of core engineering, I would say probably 60, 70% of code now is AI written. So it's still like the majority. Where we don't do any AI written or AI generated code is our research engineering, where it's just like research engineering and research, where it's a very different style of work. And, also, these code bases are so sensitive. When you think about the initial ElevenLabs launch and how quickly we got to a billion dollars of revenue, That's pretty much Peter's models being world class, and so that we just don't want to go through any sort of LLM.