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The Trillion-Dollar Industries AI Is Disrupting: Voice, Law & the End of the Billable Hour

All-In with Chamath, Jason, Sacks & Friedberg51m 33s

Two AI company founders—Mati from 11Labs (voice AI) and Max from Legora (legal AI)—discuss their explosive growth, competitive threats from frontier model providers, strategies for maintaining quality and culture during hypergrowth, and how AI is fundamentally transforming trillion-dollar industries by automating manual work and disrupting legacy business models.

Summary

The conversation features two rapidly growing AI companies disrupting major industries. Mati from 11Labs describes scaling from zero to $600 million in ARR in 50 months, with 600 employees. 11Labs has built text-to-speech technology that sounds human and powers voice agents across customer service, sales, and operations. Mati emphasizes maintaining culture during hypergrowth through small, tightly-knit teams of 5-10 people with embedded engineers everywhere, even in non-technical departments. The company has eliminated product managers, relying instead on engineers who understand customer needs and design. 11Labs partners with frontier models (OpenAI, Anthropic) but invests heavily in proprietary research to outcompete them on voice-specific tasks. The company addresses impersonation and voice rights concerns through content moderation, detection systems, and partnerships with celebrities like James Earl Jones (Darth Vader voice licensing to Disney/Epic Games) and Matthew McConaughey. Mati highlights moving from reactive to proactive customer service, where voice agents have context and can help before customers ask. He notes that people share more openly with AI than humans due to reduced emotional barriers, and interaction patterns with AI differ significantly from human conversation—people are snappier, more direct, and less concerned about wasting time.

Max from Legora discusses transforming the legal industry by moving from the billable hour model to software-driven work. Legal services represent a $1 trillion market with only 4% software adoption versus 96% services, indicating massive opportunity. Legora went from $1 million to $100-150 million ARR with consistent 50% quarter-over-quarter growth for seven quarters, becoming one of the fastest-growing enterprise SaaS companies with direct sales. Max explains that law firms charge high rates for junior associates to cross-subsidize partner work, creating perverse incentives to drag out projects. AI changes this economics by automating document review and research. Legora has completed four acquisitions in-house using their tools, with the fastest deal closing in 12 days from LOI. The company employs forward-deployed legal engineers who help firms transition from pre-AI to post-AI business models. Max addresses competitive threats from Claude and broader AI providers, arguing they're actually pipeline generators—customers experiment, hit capability ceilings, then adopt Legora. He emphasizes building narrow, domain-specific models rather than general legal intelligence, and highlights trust and compliance as core differentiators when handling sensitive case law and national security contracts. The conversation touches on data leakage concerns, regulatory complexity across jurisdictions, and how AI agents can now perform end-to-end case strategy by combining witness statements and precedent.

About this episode

<p>(0:00) ElevenLabs' $600M ARR Ramp, 600 Employees & Life Without PMs</p> <p>(15:34) Celebrity Voice Deals, Deepfake Impersonation & Racing OpenAI and Anthropic</p> <p>(31:42) Legora's Hypergrowth, Disrupting Law Firms & the Billable Hour</p> <p>(42:31) LexisNexis Decline, Legal Data Moats & Legora's Narrow AI Models</p> <p>Thanks to our partners for making this possible!</p> <p>Airwallex is a leading global payments and financial platform for modern businesses, offering trusted solutions to manage everything from business accounts, payments, treasury, and spend management to embedded finance. <a href="https://airwallex.com/allin">https://airwallex.com/allin</a></p> <p>Oracle powers AI at every scale—from frontier labs to enterprise production. Your data. Leading models. No lock-in. One platform, architected for AI. Built for business. Visit <a href="https://www.oracle.com/artificial-intelligence/ai-experience/?source=:ex:sn:::::AllIn&amp;SC=:ex:sn:::::AllIn&amp;pcode="> https://www.oracle.com/artificial-intelligence/ai-experience/?source=:ex:sn:::::AllIn&amp;SC=:ex:sn:::::AllIn&amp;pcode=</a></p> <p>Follow Mati:</p> <p><a href="https://x.com/mati">https://x.com/mati</a></p> <p>Follow Max:</p> <p><a href="https://x.com/MaxJunestrand">https://x.com/MaxJunestrand</a></p> <p>Follow the besties:</p> <p><a href="https://x.com/chamath">https://x.com/chamath</a></p> <p><a href="https://x.com/Jason">https://x.com/Jason</a></p> <p><a href="https://x.com/DavidSacks">https://x.com/DavidSacks</a></p> <p><a href="https://x.com/friedberg">https://x.com/friedberg</a></p> <p>Follow on X:</p> <p><a href="https://x.com/theallinpod">https://x.com/theallinpod</a></p> <p>Follow on Instagram:</p> <p><a href="https://www.instagram.com/theallinpod">https://www.instagram.com/theallinpod</a></p> <p>Follow on TikTok:</p> <p><a href="https://www.tiktok.com/@allin">https://www.tiktok.com/@allin</a></p> <p>Follow on LinkedIn:</p> <p><a href="https://www.linkedin.com/company/allinpod">https://www.linkedin.com/company/allinpod</a></p> <p>Intro Music Credit:</p> <p><a href="https://rb.gy/tppkzl">https://rb.gy/tppkzl</a></p> <p><a href="https://x.com/yung_spielburg">https://x.com/yung_spielburg</a></p>

Key Insights

  • 11Labs grew from first product release to $600 million ARR in 50 months, with accelerating adoption timelines: 20 months to $100M, 10 months to $200M, 5 months to $300M, then reaching $600M, indicating compound acceleration rather than linear growth.
  • Mati eliminated product managers entirely and embedded engineers in every department (including legal, talent, and revenue teams), arguing that with AI tools, non-technical functions can now handle their own product design without traditional PM gatekeeping.
  • People share significantly more personal information with AI voice agents than with humans due to reduced emotional barriers and shame, particularly in sensitive domains like financial services, making AI-human interaction fundamentally different from human-human interaction.
  • 11Labs remains competitive against frontier model providers not through scale but through specialized architecture choices and proprietary labeled audio data (built by 1,000+ internal contractors), demonstrating that research innovation matters more than model size in narrow domains.
  • The legal services industry represents a $1 trillion market with only 4% software penetration versus 96% manual services, while legacy players like LexisNexis make only a few billion annually despite data monopolies, indicating massive value capture opportunity for AI-native competitors.
  • Legora achieves consistent 50% quarter-over-quarter growth partly because AI agents now perform end-to-end case strategy combining witness statements, precedent, and regulatory data, moving from augmentation to autonomous work that reduces lawyer involvement and time.
  • Legacy law firms struggle to compete with AI startups not because incumbents lack data, but because they cannot move fast enough, cannot attract technical talent, and face internal political friction that prevents rapid business model transformation from hourly billing to fixed fees or success-based pricing.
  • Max argues that building general legal intelligence models is wasteful, and instead Legora builds narrow specialized models (like a contract data extraction model) that can be heavily optimized for cost and latency, suggesting domain-specific fine-tuning outperforms general large models in regulated professional services.

Topics

Voice AI and text-to-speech technology disrupting customer service and communicationsLegal AI automating document review and research to disrupt the billable hour modelHypergrowth management and maintaining engineering culture during 50% quarter-over-quarter expansionCompetitive dynamics with frontier model providers (OpenAI, Anthropic) and partnership strategyData privacy, voice rights, and impersonation concerns in AI systemsFrom augmentation to autonomous AI agents performing end-to-end workLegacy industry disruption and moat erosion for incumbents like LexisNexis and WestlawBuilding proprietary datasets and narrow domain-specific models versus general intelligence

Transcript

You're on a bit of a heater, huh? It's the best time to be building. And revenue has surged, but you face really intense competition. Let's go right at that to start. If you were building a global financial system from first principles today, you wouldn't build it on 50-year-old legacy rails. You'd build Airwallex, oneex one ai native platform for global accounts cards and payments is designed to make the entire world feel like a local market others are bolting ai onto broken infrastructure but air wallex was built for the intelligent era from day one stop paying the legacy tax and start building the future at airwallex.com all in airwallex built for the future 350 million in what…

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