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What actually changes inside a product and engineering org when a company commits to becoming AI-native—not as a side project, but as the new operating system?

In this episode of Supra Insider, Marc and Ben sit down with Gaurav Hardikar, VP of Product at HomeLight, to unpack the company’s ambitious transformation: an executive team hackathon, ten AI initiatives across tech debt and product debt, and a completely new way of scoping, shipping, and collaborating across product, engineering, and design.

Gaurav walks through how HomeLight reshaped their workflows to move dramatically faster, built an AI-powered scoping assistant that consolidates inputs across functions, and created a shared “source of truth” that removes one of the biggest product bottlenecks—misalignment.

He also introduces a brand-new role inside the org: the AI Product Builder—what it is, why PMs can’t do all of it, and the skills that separate great builders from average ones as AI-native development becomes standard.

Whether you’re a product leader trying to accelerate your roadmap, an engineer rethinking how AI changes execution, or a PM who wants to understand what skills will still matter in an AI-native world, this episode gives a practical, inside-the-org look at what real transformation requires.

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Interviewing at Uber, Figma, Stripe, or DoorDash?

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In this episode, we covered the following topics:

* (01:52) How HomeLight’s AI efforts started: chat, voice, and agent coaching tools

* (07:32) The moment leadership realized the org needed to rethink how it works

* (12:31) Three process initiatives: the design system, scoped workflows, and automated analytics

* (17:53) The #1 pain point in traditional scoping: misalignment

* (26:23) Where VPs should insert themselves in the workflow (and where they shouldn’t)

* (36:10) Why specs die but scope lives on—defining what’s in, out, and why

* (38:10) The dangers of overbuilding before you prototype

* (41:19) Introducing the new AI Product Builder role at HomeLight and the traits that make someone great at it

* (49:48) How zero-to-one projects graduate—or get collapsed into something simpler

* (53:27) The “last mile” problem: QA, edge cases, and Slack interface constraints

* (58:37) Leadership’s role in creating psychological safety for experimentation

* (1:06:32) Final lessons and what HomeLight wants to learn from other AI-native orgs

* And more!

Links:

* Gaurav Hardikar Newsletter: https://www.insidergrowthhq.com/

* Gaurav Hardikar: https://www.linkedin.com/in/ghardikar/

* Marc: https://www.linkedin.com/in/marcbaselga/

* Ben: https://www.linkedin.com/in/benerez/

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