Why AI hasn't replaced human expertise—and what that means for your SaaS stack
The most valuable AI tools in your enterprise stack do more than generate answers. They help developers determine which answers to trust.

Articles on business, SaaS, and the software that powers organizations.
The most valuable AI tools in your enterprise stack do more than generate answers. They help developers determine which answers to trust.

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

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

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

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

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.

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

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

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

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

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

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.

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.

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.

In this episode of Leaders of Code, Stack Overflow CEO Prashanth Chandrasekar and Christina Dacauaziliqua, Senior Learning Specialist at Morgan Stanley, talk about the importance of experiential learning in fast-paced environments. They emphasize the value of creating intentional learning environments where innovative tools meet collaborative communities to support growth for both individuals and organizations.

Innovation is at the heart of any successful, growing company, and often that culture begins with an engaged, interconnected organization.

In this episode of Leaders of Code, Jody Bailey, Stack Overflow’s CTPO, Anirudh Kaul, Senior Director of Software Engineering, and Paul Petersen, Cloud Platform Engineering Manager, discuss the U.S. Bank’s journey from traditional banking practices to embracing new technologies.

Striking the balance between speed and strategy is a major challenge for business and tech leaders. That’s where aligned autonomy comes in.
