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

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