Scaling AI Rocketships: ElevenLabs’ Mati Staniszewski & Lovable’s Anton Osika

1. Key Themes

The Experience Advantage: Why Starting at 21 Would Have Failed

Both founders emphasized that their 7-8 years of pre-startup experience was crucial to their success. Mati noted he "didn't even know the world of entrepreneurship existed" when studying mathematics, and only learned customer-focused product development at Palantir. Anton similarly needed time to understand how to hire senior engineers and build ambitious products. As Mati stated: "I don't think I would be able to understand the first early dynamics of starting something in the same way. The other thing, I think we would have probably worked on a very different idea." [00:02:28]

The Small Team Architecture: Staying Nimble at Scale

11 Labs operates as "effectively a lot of small teams, third teams of five to ten people" despite having over 300 employees [00:15:11]. This structure enables rapid response to changes. Mati explained: "The moment something comes out either internally from our research team or from other teams, you know that this is like you have 24 hours to start integrating that into your product. That's like the most important time to really be ahead." [00:24:36]

The Death of Annual Planning: Six-Month Horizons in AI

Both CEOs have abandoned traditional annual planning cycles. Anton runs with a six-month product roadmap that's "pretty flexible" within that timeframe [00:23:06]. 11 Labs does quarterly planning for teams, but notably, "here we don't give any timelines, we do research initiatives beyond the plan" for their foundational research work [00:24:11]. The underlying technology changes too rapidly for longer planning cycles.

2. Contrarian Perspectives

Building for the 99%, Not Productivity for the 0.5%

Anton made a deliberate choice to avoid the crowded developer tools space: "0.5% of the world can even code, and much fewer can build a great product like Mati's co-founder, right? So I decided let's build something for the 99% and not this productivity boost for developers, and that's going to be a completely new type of interface." [00:07:32] This goes against the conventional wisdom that you should build tools for developers first.

Europe as Hard Mode—But With Hidden Advantages

While acknowledging Europe as "hard mode" for distribution and access to experienced executives, both founders argued the disadvantages are overrated. Anton explained: "I think it has been very helpful for us to be like the go to number one talent destination in Stockholm. There is much more available talent that doesn't jump around. They aren't entitled and spoiled. And they're yearning for a possibility to literally change the world." [00:36:51] They're betting against the Silicon Valley-or-bust narrative.

The AI Platform Threat Is Overblown

Despite OpenAI and Anthropic having massive distribution advantages, neither founder expressed significant paranoia. Anton noted: "What we're building is this full platform where you're serving like most of the product needs for an entire product and engineering organization. And that takes a lot of iterations...unless they're like building that out completely in the dark and then launching it, I don't think it's going to be a threat." [00:26:19] They believe focus and product iteration beats distribution.

3. Companies Identified

Palantir

• Description: Data analytics and deployment company
• Why mentioned: Formative experience for Mati, teaching him customer-focused product development
• Quote: "I joined them where it turned out you can actually be deployed at the customer, learn about the problems, try to understand those problems and bring them back and build the product, which was like the first glimpse into how to build something from scratch." [00:02:44] - Mati Staniszewski

Sona (acquired by Workday)

• Description: AI company recently acquired for $1 billion
• Why mentioned: Anton was early employee and helped recruit talent that grew the company
• Quote: "One was the founder, Sona, so Joel, who recently sold the Sona to Workday for a billion dollars...My contribution was bringing in some of those smart people that went on to grow it to what it became." [00:06:17] - Anton Osika

HubSpot

• Description: Marketing and CRM platform (Brian Halligan's company)
• Why mentioned: Referenced as case study for scaling, delegation, and managing platform competition
• Quote: Discussed throughout by Brian as examples of lessons learned

4. People Identified

Michael (11 Labs Co-founder)

• Description: Mati's co-founder and high school friend, leads research
• Why mentioned: Example of long-term co-founder relationship and complementary working styles
• Quote: "I think it still would have the pleasure of working with Michael Funder, I know him in his high school...the smartest person I know and is kind of leading the research work in his case he needs to go extremely deep for very long time." [00:02:02] - Mati Staniszewski

Steve Jobs

• Description: Apple founder
• Why mentioned: Primary influence on both CEOs' leadership philosophy
• Quote: "What I like about him is he really understands that like a team working better and better and better over time and like really obsessing and caring about what you're doing is." [00:41:17] - Anton Osika

Jamie Dimon & Satya Nadella

• Description: CEOs of JPMorgan and Microsoft respectively
• Why mentioned: Leadership role models for Mati
• Quote: "I like Jamie Dimon and how his clarity and his like across so many things that he runs...Satya, I think the way he kind of turned it out. And he is like a very caring person around, around how he runs the company." [00:44:05] - Mati Staniszewski

5. Operating Insights

The P0/P1/P2 Email System

Mati implemented a sophisticated email triage system combining human and AI classification: "My really understanding and how nice helping and the script is helping to auto classify a lot of emails to effectively p0 p1 p2...same day reply on the p0 p1 can wait for the week p2. Not important." [00:30:23] The system uses contact lists to auto-classify certain people as P0, ensuring rapid response to key relationships.

Geographic Batching for Context Efficiency

Rather than frequent international trips, Mati stays in each continent for extended periods: "I'm trying to never be switching the continent in a in the same month. So like I would 10 a month, I'm trying to stay in one place...I usually try to be in a US for close to a month." [00:32:46] This reduces context-switching costs and enables deeper customer engagement.

The Backward Reference as Hiring Filter

When hiring for unfamiliar roles like sales, Mati emphasized: "The back references really helps across that beyond the spending time with the team which which I think is crucial." [00:30:27] This is especially important when hiring salespeople who are naturally good at selling themselves.

6. Overlooked Insights

The Cultural Imprint of Your First Sales Leader

Mati revealed a non-obvious dynamic about sales hiring: "For sales specifically is that you are hiring of course a great individual for creating the sales playbook, helping you sell into the enterprises. But then ultimately the person you hire, they will set the culture for the sales team too. Like a lot of the people they will hire will be so similar in the approach to that work, which which I didn't appreciate until the other after the fact." [00:40:37] This means the first sales hire has outsized influence beyond just their individual contribution—they're defining the DNA of your entire go-to-market organization.

The Equity Education Problem in Europe

A subtle but significant barrier to European startup growth emerged: "In Europe, you kind of need to convince the employees. Sometimes you need to convince the families that this is the right thing. In Poland, we need to frequently explain that equity is worth something. Almost forced employees to take the equity." [00:39:43] This isn't just about compensation design—it's a generational education problem that requires doing tender offers to create proof points before the next cohort believes. This creates a flywheel disadvantage versus US talent markets that most people overlook.