Engineering teams have upgraded their tools. Have they upgraded how they work?

Eira May

On this episode of Leaders of Code, Eric Anderson, director of engineering at Intuit, joins Stack Overflow engineering director Ben Matthews to talk about what happens to software teams when AI makes code generation seemingly free.

Eira May

Because someone still has to own the consequences of what gets built and whether it can function at scale.

Eira May

Jon Hyman, co-founder and CTO of Braze, shares how he's led the company's engineering organization over nearly 15 years of growth — and how they transformed into an AI-first team in just a few months.

Eira May

The most valuable AI tools in your enterprise stack do more than generate answers. They help developers determine which answers to trust.

Eira May

Adoption and trust are moving in diametrically opposed directions, and that gap has real implications for organizations deciding how to spend money on software.

Eira May

Dana Lawson, CTO of Netlify, shares her insights on leading a lean, globally distributed engineering team that powers 5% of the internet.

Eira May

The difference between AI that impresses people in demos and AI that drives production value is context.

Eira May

For most of the web's history, content platforms operated on a simple binary: open or blocked. Then generative AI changed everything.

Eira May

Inside the pay-per-crawl model colaunched by Stack Overflow and Cloudflare.

Developer trust is synonymous with a willingness to deploy AI-generated code to production systems with minimal human review, as well as assurance that AI tools aren’t introducing unacceptable risks and technical debt that will burden you down the line.

Eira May

Not only is there a future for software development, but we’re on the cusp of enormous demand for code developed by humans.

Eira May

Successful implementation and scaling of enterprise AI projects is fundamentally a people and operating model challenge, not just a technology problem.

Eira May

Learn how IBM deployed and integrated AI tools in the ultimate enterprise environment.

What we learned from the first year of Leaders of Code.

Eira May

How Stack Internal provided the foundation for a culture of continuous learning and open collaboration.

Eira May

Lessons learned building a global API platform, navigating hyper-growth, and API-powered AI agents.

Here, we’ve distilled the survey findings, laid out action items for leadership, and dug into recommendations around agentic AI for the enterprise. Spoiler alert: It all comes back to data quality.

Eira May

Discover how leveraging an intelligent, community-driven knowledge layer is the key to grounding probabilistic tools, preventing AI hallucination, and validating high-quality code.

This episode draws on insights from the 2025 Stack Overflow Developer Survey to equip leaders with ways to navigate the current AI landscape and capture value beyond the hype.

While AI coding assistants are helping developers become more productive, the true value of AI lies in its ability to automate the non-coding tasks that have historically been bottlenecks, allowing leaders to create more agile teams and focus on higher-level strategic problems.

Phoebe Sajor

This episode provides insights and strategies to successfully navigate AI adoption in engineering teams. Learn how to build developer confidence and create environments that drive real results beyond the hype.

Whether you're leading an engineering team today or preparing for an AI-integrated future, this conversation provides practical insights into where AI can have the greatest impact on your software delivery process.

The most effective learning doesn’t happen in a classroom. It happens during work.

Eira May