Engineering Enablement by DX

Mapping the new SDLC at BNY: Codifying AI into every step of the delivery lifecycle (Jason Valentino)

Engineering Enablement by DX

Show Notes

Jason Valentino is Head of Software Engineering Strategy at BNY, where he oversees developer tooling, DevEx, platform workflows, and software delivery governance across more than 8,000 engineers. In this session from DX Annual, Jason shares how BNY moved beyond AI coding assistants to rethink the entire software delivery lifecycle. He explains how his team identified bottlenecks across the SDLC, prioritized automation opportunities, and applied AI to planning, peer review, testing, change management, and compliance workflows. Jason also discusses what it takes to scale AI inside a highly regulated enterprise, including rewriting policies, partnering closely with risk and audit teams, and building a culture that encourages experimentation and rapid sharing of ideas.

Where to find Jason Valentino: • LinkedIn: https://www.linkedin.com/in/jasonvalentino

In this episode, we cover: (00:00) Intro (01:20) Early results from AI coding tools at BNY (04:08) The 3X stress test: What breaks if engineering throughput triples? (06:56) Three ways to apply AI across the SDLC: IDE and CLI tools (08:07) Using autonomous AI agents for repetitive engineering tasks (09:16) Embedding AI directly into SDLC workflows (12:27) Why leaders should encourage experimentation and “start saying yes” (15:00) Q&A: How platform and productivity teams are evolving to support AI (16:33) Q&A: Rewriting policies and controls for AI-assisted software delivery (17:52) Q&A: How AI is affecting software quality and test ownership (19:00) Q&A: What Jason is most proud of: Practical examples of AI across the SDLC (20:30) Q&A: How BNY handles duplicated work across AI initiatives (22:30) Q&A: How BNY uses AI to support regulatory and compliance work (23:30) Q&A: Automating code reviews and change tickets (25:55) Q&A: How increased AI-driven throughput is affecting on-call and reliability (27:11) Q&A: How BNY works with risk and audit partners to move quickly with AI (29:01) Q&A: How BNY scales successful AI use cases across the organization (30:42) Q&A: What Jason is most proud of after BNY’s busiest year with AI

Referenced: • AI-assisted engineering: Q4 impact report • Measuring AI code assistants and agents • Measuring developer productivity with the DX Core 4 • Windsurf • Claude Code by Anthropic | AI Coding Agent, Terminal, IDE • Codex | AI Coding Agent

More from Engineering Enablement by DX

Oct 16, 2026

As AI agents become more capable, context quality is increasingly the limiting factor in their performance. In this episode of Engineering Enablement, DX researcher Brian Houck by his CAFE(S) is joined by co-authors Max Kanat-Alexander (Capital One), Eirini Kalliamvakou (DX), and Margaret-Anne Storey (University of Victoria) to discuss CAFE(S), a new framework for improving context quality. The panelists introduce the five dimensions of CAFE(S): Clarity, Actionability, Fidelity, Efficiency, and Security. They walk through common context failures, how poor context accrues technical and cognitive debt, what it costs in developer productivity and operating spend, how AI is changing the skills engineers need, and why context review could become as important as code review.

Oct 2, 2026

Meta researcher Moritz Beller joins Brian Houck to discuss how Meta measures developer productivity. Moritz explains diff authoring time and how Meta uses it to evaluate tools and guide engineering decisions. They explore how AI is changing engineers’ work and revealing gaps in traditional metrics. They also revisit Moritz’s “Mind the Gap” study and discuss the promise and risks of AI agents for testing.

Sep 11, 2026

In this episode of Engineering Enablement, Robert Lucero, Chief Architect at Okta, joins host Brian Houck to discuss how agentic AI is changing identity and access management. They explore how organizations should define agent identities, why authentication and authorization remain foundational, and how sandboxing, fine-grained permissions, and just-in-time access can enable agents to operate autonomously without creating unacceptable risk. Robert shares what Okta has learned from driving AI adoption among security-minded engineers, what makes a repository ready for AI agents, and why strong testing, CI, and review processes matter even more as AI generates more code. They also discuss AI’s role in software validation, the need for human judgment, and whether AI will ultimately give the advantage to security teams or attackers.

Aug 26, 2026

Max Kanat-Alexander is an Executive Distinguished Engineer at Capital One, where he helps lead developer experience and AI-assisted software development. In this episode of Engineering Enablement, Max joins Brian Houck to discuss how AI is changing software development and why strong engineering fundamentals matter more than ever. They explore how engineering skills are evolving, why AI can amplify weaknesses in the development lifecycle, and how teams should rethink code review, quality, and testing. Max also shares how leaders can assess whether their organizations are ready for more advanced AI workflows and why developing the next generation of senior engineers remains one of the biggest open questions in software engineering.

Aug 14, 2026

AI adoption among software developers is approaching 100%, AI-authored code now makes up more than half of merged code, and developers report saving more time with AI every quarter. But those gains aren’t translating evenly into better outcomes. In this episode of Engineering Enablement, host Brian Houck, Distinguished Scientist at DX, sits down with Justin Reock, Deputy CTO at DX, to unpack findings from DX’s latest AI Impact Report. They explore where AI is improving engineering velocity and developer experience, where concerns are emerging around PR size, change confidence, and failure rates, and why rising AI spend has yet to produce a comparable increase in innovation. They also discuss how AI is changing the meaning of code maintainability and where developers’ AI-driven time savings may actually be going.

See all episodes →