a16z Podcast• Nov 4, 2025• 31:29Interview

ElevenLabs CEO: Why Voice is the Next AI Interface

From a16z Podcast

Mati Staniszewski•CEO & Co-founder, ElevenLabs

Executive Summary

ElevenLabs has rapidly expanded from a core voice synthesis product to a comprehensive audio AI platform, now including voice agent orchestration and a fully licensed music generation model.
The company's high shipping velocity is driven by a unique organizational structure of ~20 small, independent product teams, a "no titles" policy, and a six-month mandate for new products to prove their value.
A key strategy involves deep collaboration with creative industries, evidenced by paying out $10 million to creators via its Voice Marketplace and securing complex licensing deals with music labels like Merlin and Cobalt.
As the company scales to 350 people, it is actively navigating the transition from a passion-driven startup to a structured organization, focusing on aligning sales incentives with long-term strategy.

12 quotes

Concerns Raised

Aligning sales incentives with company strategy during rapid scaling.
Managing potential inefficiencies like duplicative work arising from a decentralized team structure.
Navigating lengthy and complex negotiations with established industries like music labels.

Opportunities Identified

Becoming the foundational platform for enterprise voice agents and conversational AI.
Expanding the creator economy through the Voice Marketplace and licensed music generation.
Dominating the market for high-quality, multilingual audio content creation, including dubbing and narration.

Key Themes

Rapid Product Expansion and Innovation

ElevenLabs has aggressively moved beyond its foundational text-to-speech technology to offer a full suite of audio AI tools, including voice agent orchestration, speech-to-text, and licensed music generation. This expansion is fueled by a culture of rapid, continuous shipping.

This strategy demonstrates the company's ambition to become a dominant platform for all audio AI, moving up the stack from a component to an end-to-end solution provider, significantly increasing its total addressable market.

Decentralized Organizational Structure for Speed

The company is structured into approximately 20 small, autonomous product teams of 5-10 people. This is complemented by a "no titles" policy to maintain a flat hierarchy and a six-month "prove it or kill it" window for new products to find market fit.

This agile, decentralized model is central to ElevenLabs' ability to innovate quickly across multiple product lines. It serves as a case study for scaling innovation in the fast-paced AI industry, despite potential trade-offs like duplicative work.

Proactive Collaboration with Creative Industries

Rather than pursuing a purely disruptive path, ElevenLabs actively partners with creative professionals and industries. This is exemplified by its Voice Marketplace, which has paid $10M to creators, and its 18-month effort to secure licensing deals with music labels for its music model.

This collaborative approach helps mitigate the negative "AI is bad" narrative, builds industry trust, and ensures a sustainable business model by creating licensed, commercially-viable products, which is crucial for navigating the complex IP landscape of generative AI.

Navigating Scaling Challenges

As ElevenLabs grew to 350 employees, it encountered classic scaling challenges, particularly in its go-to-market function. A key learning was the critical need to carefully align sales team incentives (commissions, quotas) with long-term company strategy to prevent misaligned behaviors.

This highlights the crucial operational and cultural shifts required as a successful AI startup matures. The explicit policy of not selling to competing foundational models, even at the cost of a deal, shows a maturing strategic focus over short-term revenue.

Balancing Foundational Research and Product Needs

The company manages the tension between long-term research breakthroughs and immediate product demands with a "three-month rule." If a research-level solution is more than three months away, the product team is empowered to build a more immediate, practical solution to meet user needs.

This pragmatic framework prevents product development from being stalled by uncertain research timelines. It ensures the company consistently ships valuable features to users while continuing to invest in foundational model improvements.

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Topics

AI Voice Synthesis Text-to-Speech (TTS)Generative AI Organizational Structure Product Management Go-to-Market Strategy Scaling Startups Creator Economy Music Generation IP Licensing AI Ethics Remote-First Culture Team Culture Enterprise AI Conversational AI Agents

Processed Apr 6, 2026 yt-dlp + mlx-whisper + Gemini