Building an Enterprise AI Startup from Day Zero

Lexi Reese has scaled companies at every stage — from building Google’s programmatic advertising business, to helping Gusto grow revenue from $10M to $300M.

Now she’s co-founder and CEO of Lanai, an enterprise AI startup tackling a problem most companies don’t even realize they have: they can’t actually see how AI is being used inside their organizations, or whether it’s driving real outcomes.

In this episode, we unpack what it really looks like to build a company from scratch in the AI era.

Lexi walks through how she ran more than 200 customer interviews before committing to a product direction, why product-market fit isn’t real until someone is willing to pay, and how she’s building a 14-person team — plus AI “teammates” — without losing focus or trust.

We also talk about fundraising in a tougher 2025 market, why early founders need to resist the urge to build comprehensive solutions too soon, and how organizational design is already changing as AI flattens hierarchies and reshapes work.

If you’re thinking about starting a company — or you’re in the messy middle of finding product-market fit — this conversation offers a practical roadmap for what actually matters.

RUNTIME 51:45

 

EPISODE BREAKDOWN

(2:01) What Lanai does

(5:05) Lexi’s customer discovery process — “definitely 200 interviews”

(12:03) Why customer delight should be a founder’s obsession metric

(15:36) What “AI productivity” actually means

(19:12) Lexi’s framework for managing small, early-stage teams

(26:23) Her take on seed-stage fundraising in late 2025

(31:54) How to integrate customer feedback into product strategy

(38:00) The most meaningful proof a first-time founder can show an investor

(40:53) Why “trust has a code” when it comes to teamwork

(44:08) How Lexi stays obsessed with customers in every meeting

(48:15) The final question

LINKS

• Lexi Reese
• Lanai
• Steve Herrod
• Juxtapose
• General Catalyst
• Splunk
• Datadog
• Why You Will Marry the Wrong Person, Alain de Botton

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Thanks for listening!

 – Walter.