Two words that make most engineers shudder: code refactoring. Now raise the stakes — refactoring decades of legacy systems inside a large enterprise.

A tech debt-heavy project of this scale needs a leader who has driven complex digital transformations, like Gayatri Narayan (formerly PepsiCo, Microsoft, Amazon). Now, as President of Technology at Builders FirstSource, Gayatri Narayan is achieving a 3–4x increase in engineering velocity since joining less than a year ago.

Gayatri joins host Yousuf Khan to unpack the strategy behind those results, including how to deploy AI across the SDLC, how to rigorously evaluate ROI on AI investments, and how to lead change across complex enterprise tech stacks.

Key Moments:
01:30 – Why Construction Technology Is Ready for Transformation
04:05 – AI Strategy: Elevating UX and Customer Experience
08:20 – Evaluating AI Investments: ROI, NPV, and Operating Costs
12:45 – Achieving 3–4x Engineering Velocity
16:05 – Humans in the Loop: Craft, Code Review, and AI Amplification
18:35 – Where the Industry Gets AI Adoption Wrong
20:30 – Leadership Advice: Start with the Customer

About Gayatri:
Gayatri Narayan is a general management executive with more than 15 years of experience leading product, engineering, data science, and operations across global enterprises, with full P&L responsibility and a track record of driving profitable growth through digital transformation.

She currently serves as President of Technology at Builders FirstSource, where she leads enterprise technology strategy, modernizes legacy systems, and embeds AI into the software development lifecycle to accelerate innovation across the residential construction value chain.

Previously, she served as Senior Vice President of Digital Products and Services at PepsiCo and held multiple general management roles at Microsoft, including leading Product and Engineering for Intelligent Communications across Teams and Skype as well as Enterprise PaaS and SaaS businesses; she also held leadership roles at Amazon spanning Marketplace Transportation and Logistics and several major retail categories.

Guest Highlights:
“We’ve seen a three to four times increase in engineering velocity — especially in refactoring legacy systems where historically there was very little knowledge of how the system actually worked.”

“With generative AI, companies that have existed for 20 or 30 years don’t have to get bogged down by legacy stacks. They can embrace emerging technologies without spending 18 to 24 months just refactoring.”

“It really comes down to efficiency of time. The developer’s surface area of impact expands dramatically — it’s not just about writing code anymore, it’s about delivering business value faster.”

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