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Past the Pilot: What It Takes for AI to Survive Contact with 1,100 Engineers

Posted Oct 29, 2026 | Views 0
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Sagnik Nandy
CTO @ Docusign

Sagnik Nandy is the Chief Technology Officer and Executive Vice President of Engineering at Docusign responsible for engineering, cloud operations, and technology strategy that enables customers globally to run their organizations on Docusign.

Most recently, Sagnik served as the President and Chief Development Officer for Workforce Identity at Okta where led engineering development and operations, product management, and design and user research. Earlier, he joined Okta as their CTO, overseeing the engineering and business technology arms of the company.

Prior to Okta, Sagnik served as the Vice President of Engineering at Google where he oversaw several critical components of Google’s core advertising business, the backbone of the company’s growth and revenue. During his 15 years at Google, Sagnik also helped build Google’s Measurement and Analytics offerings and took several products from inception to becoming market leaders.

Sagnik has a bachelor’s degree from the BITS, Pilani (Birla Institute of Technology and Science Pilani) and a Ph.D. in computer science and engineering from UC San Diego.

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SUMMARY

Most engineering orgs have solved for AI tool adoption already. What separates the ones getting real leverage from it is shared infrastructure, workflow automation, and guardrails that survive past the champions who first pushed for it.

At Docusign, that started with a peer-led model. Engineers across teams took on responsibility for embedding AI into daily workflows, documenting what actually worked, and surfacing the friction points that tooling alone couldn't fix. That foundation now spans across all 1,100+ of the company’s engineers.

Sagnik Nandy will walk through what came next, how Docusign's engineering org moved from individual AI adoption to a connected set of internal platforms spanning the SDLC – from coding to observability to agent orchestration – and the design decisions that made those platforms reusable for engineers and product teams rather than one-off tools.

He'll cover what worked, what didn't, and how the team distinguishes AI that's actually improving outcomes and developer productivity from AI that's just increasing usage.

Attendees will leave with a practical framework for designing AI platforms that scale past the pilot stage, and an open door to keep the conversation going with Docusign's engineering team after the session.

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CONTENT & TRANSCRIPT


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