20VC: From Only OpenAI to Die-Hard Anthropic: The Downfall of OpenAI in Enterprise | Harvey vs Legora: Legal AI is a Winner Take All | $7M ARR in a Single Day and Raising $200M Across 3 Rounds with No Deck with Max Junestrand, CEO @ Legora
episode
The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
1h 3m
3 speakers
8 chapters
transcribed
Transcript
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Transcript generated automatically by AI and may contain errors.
What is the main topic discussed in this episode?
It doesn't really matter who was first. It matters who's best. It's totally a winner takes all. Number one will grab 90% and number two to number 10 will share the remaining 10%.
Why does everyone think of Harvey when they hear about legal AI?
Gotta run like hell. You gotta win. There's no number two.
Why is OpenAI considered toast and what led to the switch to Anthropic?
There is only being number one. There's only winning. Everything else is losing. In a single day in 2025, in December, we added 7 million of ARR.
Which foundation models are expected to win in the next 24 months?
One day in 24 hours. And that was more than what we did in 2023 and 2024 combined.
This is 20VC with me, Harry Stebbings, and what a show we have in store for you today. Last week, we had Harvey on the show. That broke pretty much all records. This week, we have their biggest competitor, Legora on the show. And joining me is Max Dunstrand, co-founder and CEO at Legora, the legal AI company that has scaled to 70 million in ARR, 750 of the world's biggest law firms as customers, and over 300 employees in just two years. They've raised over $200 million from some of the best, including Benchmark, General Catalyst, Redpoint, and Iconic, to name a few. But before we dive into the show today, over 80% of Fortune 100 companies are running their businesses with Airtable. And Airtable combines AI with the scale of an award-winning, infinitely flexible no-code system, a platform where you can see all of your data in one place and use it to make really big picture decisions.
What lessons can be learned from scaling a company from Europe to the US?
Think of it like mission control for your company. Airtable goes beyond organization and automating repetitive tasks. It lets you use your data to inform strategy, monitor progress, and take action. Every cell is capable of performing hundreds of AI-powered tasks like web research or localization. and using those results to inform and update hundreds or thousands of other sales and workflows in real time.
Do Americans really work as hard as they claim?
Unlock the true scale of your workflows at www.airtable.com forward slash 20 VC, Airtable, the infrastructure of innovation. And just like Airtable organizes your workflow data, MetaView organizes your conversation insights. This episode is brought to you by MetaView. Who says hiring has to be fair?
Why are seat models not dead in SaaS?
Every founder, VC, and exec I speak with knows this. Your ability to hire is the biggest constraint on your company's growth. But recruiting is slow, it's subjective, and only getting more competitive. And that's why teams like Eleven Labs, Brex, Replit, Deal, and 5,000 other organizations use MetaView, the AI company giving high-performance teams a real unfair advantage in hiring.
How can competition ignite passion within a team?
MetaView's built a suite of AI agents that behave like recruiting coworkers. They proactively find candidates, they take interview notes automatically, and they help you surface the best candidates in process. For the first time, AI handles the recruiting toil and gives you a single source of truth. That means hours saved per hire and a team focused on what matters most, winning the right candidates as fast as possible. Don't let your competitors out hire you. MetaView customers close roles 30% faster. Try MetaView today and get a free month of sourcing at metaview.ai forward slash 20VC. After MetaView captures what was said, Turing helps you build with the people who can deliver after it. and other leading labs partner with Turing.
Turing is the research accelerator focused on post-training reliability. They build realistic reinforcement learning environments, next-generation data quality systems built from real-world operational traces, and coding datasets that stress models under the conditions where failures matter. State changes, workflow branching, brittle tool calls, and the coding errors that break RL agents but never appear in benchmark reports. In reality, a model may demonstrate correct reasoning in your evaluation setup, yet still select the wrong parameter or mishandle a code update in a realistic interface. Turing makes that failure visible and gives teams the signal they need to fix it. For labs advancing agentic systems, Turing provides the structure required
to understand why these failures occur. To find out how, visit Turing.com forward slash 20VC.
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Chapters
8 chapters
1
What is the main topic discussed in this episode?
0:00–0:13
2
Why does everyone think of Harvey when they hear about legal AI?
0:13–0:17
3
Why is OpenAI considered toast and what led to the switch to Anthropic?
0:17–0:26
4
Which foundation models are expected to win in the next 24 months?
0:26–1:25
5
What lessons can be learned from scaling a company from Europe to the US?
1:25–1:51
6
Do Americans really work as hard as they claim?
1:51–2:10
7
Why are seat models not dead in SaaS?
2:10–2:34
8
How can competition ignite passion within a team?
2:34–1:03:21
Speakers
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