Augmented, accelerated, autonomized: How Vanguard is embedding AI across the product lifecycle (Kelly Anne Pipe and Nicole Scribner) episode artwork

EPISODE · Jun 15, 2026 · 39 MIN

Augmented, accelerated, autonomized: How Vanguard is embedding AI across the product lifecycle (Kelly Anne Pipe and Nicole Scribner)

from Engineering Enablement by DX · host DX

Kelly Anne Pipe is Head of Developer Experience at Vanguard, and Nicole Scribner is a Director in the firm's Chief Technology Office focused on engineering enablement and advancement.In this session from DX Annual, Kelly Anne and Nicole share how Vanguard is expanding its AI strategy beyond software engineering to the entire product development lifecycle. While the company initially focused on tools like GitHub Copilot for engineers, they found that faster coding alone did not significantly improve delivery speed. Product managers, designers, QA teams, and organizational processes were still operating at a different pace.To address this challenge, Vanguard developed a product team maturity model built around three stages: Augmented, Accelerated, and Autonomized. The framework spans six dimensions, from AI-powered delivery and AI-ready codebases to team autonomy, operations, and responsible AI.Kelly Anne and Nicole explain how Vanguard is applying the model across more than 800 product teams, the behaviors they believe will enable faster delivery, and the lessons they have learned about measurement, organizational change, dependencies, and scaling AI across the product development lifecycle.In this episode, we cover:(00:00) Intro(02:16) The state of AI one year ago at Vanguard(02:54) The engineering bubble(05:05) Building an AI maturity model for 800 product teams(08:24) Dimension 1: AI-powered product delivery(10:00) Dimension 2: AI-ready codebase(12:20) Dimension 3: Autonomous agent utilization (13:00) Dimension 4: AI-augmented operations(14:00) Dimension 5: Team autonomy and enablement(16:11) Dimension 6: Responsible AI(18:15) The people problem: role evolution (20:00) The measurement problem (22:55) Lessons learned from rolling out the maturity model (26:46) What’s ahead (30:10) Q&A #1: Getting your codebase ready for AI(32:22) Q&A #2: Audit trails and responsible AI(34:16) Q&A #3: Vanguard's maturity model progress(36:15) Q&A #4: Measuring cycle time across 800 teamsReferenced:• Vanguard• Jennifer St Pierre - Dell Technologies | LinkedIn• Mercari

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Augmented, accelerated, autonomized: How Vanguard is embedding AI across the product lifecycle (Kelly Anne Pipe and Nicole Scribner)

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