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The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch 1h 3m 2 speakers 6 chapters transcribed 1 month ago
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Arun Mathew 0:00
sometimes getting overly fixated on the financial metrics in this environment can leave you just like with an unsatisfying taste in your mouth. Growth can obscure and blind you to a lot of underlying ills in the business. I think you can actually be successful in this market investing in consensus. Investing is an art and a science. The science is understanding how to properly value a company and the art is understanding when to break the rules. Focus on hitting singles and doubles and let the home runs take care of themselves.
Harry Stebbings 0:26
This is 20 of you see with me, Harry Stebbings. Now stay, I'm thrilled to welcome a dear friend to the show, Myles Clements. Myles helps lead Excel's growth investing practice, where he's backed some of the best in the business, including Atlassian, Linear, Cursor, and many more incredible companies. Now, Mars is an old friend, and so this was a very, how do I put it, no holds barred discussion. I think he put up with a lot of very pressing and prying questions, and I don't think you've ever heard an Excel partner be quite as open and honest as this, which was just fantastic. Mars really was very special to have on. But before we dive into the show today, over 80% of Fortune 100 companies are running their businesses with Airtable.
Harry Stebbings 1:09
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. 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. Unlock the true scale of your workflows at www.airtable.com forward slash 20 VC, Airtable, the infrastructure of innovation.
Harry Stebbings 1:56
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? 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. MetaView's built a suite of AI agents that behave like recruiting co-workers. They proactively find candidates, they take interview notes automatically, and they help you surface the best candidates in process.
Harry Stebbings 2:41
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. Frontier labs keep facing the same limitation. Models perform well on benchmarks, but they fall short once they enter real coding tasks, real tools, and real workflows. That disconnect between synthetic evaluation and actual system behavior is now a core blocker for agentic models.
Harry Stebbings 3:28
That's why NVIDIA, Anthropic, Salesforce, Gemini, and other leading lab partners partner with Turing. Turing is the research accelerator focused on post-training reliability. They build realistic RL environments, next-generation data quality systems built from real-world operational traces, and coding datasets that stress models under 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.

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