Every one of ElevenLabs' original core research and engineering employees is still at the company, reflecting exceptional culture retention.
Snapshot · All-In with Chamath, Jason, Sacks & Friedberg
Every one of ElevenLabs' original core research and engineering employees is still at the company, reflecting exceptional culture retention.
Where this was said
At 3:30 · chapter starts 0:00
Jason describes the shift he's personally felt — from dreading voice IVR systems to now almost feeling guilty taking a human agent's time. Casser validates this, saying ElevenLabs is seeing it in its enterprise customer base: the combination of reliability, model orchestration, contextual knowledge, and integrations has finally crossed a quality threshold [1] — Mati Casser "With AI, people are much more open to share what actually happened, give the information, and suddenly this emotional block of in front of …" 14:40 . He describes a future where voice agents proactively reach out before a customer even knows they need help — shifting from reactive support to anticipatory service. The most surprising data point: in financial services, customers are dramatically more honest with AI voice agents than with human ones. When a Revolut or Klarna customer is being reminded about a missed payment, the shame of admitting the truth to a human is absent with AI, producing better information and faster resolution.
ElevenLabs went from zero to $600M ARR in under 4 years, with each milestone taking half the time of the previous: 20 months to $100M, 10 to $200M, 5 to $300M. This is what AI-native compounding looks like at full speed.
ElevenLabs took 20 months to reach $100M ARR, then 10 months to $200M, then 5 months to $300M, showing rapid acceleration.
ElevenLabs reached $600M in annual recurring revenue with 600 employees and has operated with no product managers since founding.
ElevenLabs embeds an engineer into every department — including legal, talent, and sales — to build automations and serve as a security check on AI-generated code.
ElevenLabs has never had a product manager. Instead, engineers are embedded in every team — legal, talent, sales — to build automations and audit AI-generated code. The bet: engineer-polyglots beat PM-mediated teams every time.
Jason Calacanis has started using a foot pedal with WhisperFlow to give 1–2 minute stream-of-consciousness prompts to AI. The insight: LLMs handle long, unstructured spoken input better than typed prompts, and the friction of typing was limiting prompt quality.
Sam's initial MVP was coded in approximately one week using ChatGPT voice mode and copy-pasting code, with no prior technical experience.
Sam argues Discord is 10x better than email for building relationships with younger users who rarely check their inbox.
Sam's monthly operating costs include Cursor ($200), AI image generation ($100), AI video generation ($200), hosting ($100), email marketing ($80), and AI compute ($300–$500).
Sam recommends copying days of Discord chat history into ChatGPT and prompting it to list recurring pain points as a fast, free market research technique.
Bhanu and his team built approximately 50 free tools to attract search traffic, each linked back to SiteGPT.
With AI coding tools like Cursor, Bhanu can now create a new free marketing tool in less than 5 minutes by referencing existing tools.
Bhanu filters Ahrefs keyword results to show only those with a keyword difficulty below 10, making them realistic ranking targets for any decent website.
Bhanu sets a minimum search volume of 1,000 monthly searches when selecting keywords to target with free tools.
PropGPT averaged 20 downloads per day right after launching on the App Store through influencer marketing.
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