Scaling enterprise AI: lessons in governance and operating models from IBM
Successful implementation and scaling of enterprise AI projects is fundamentally a people and operating model challenge, not just a technology problem.

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

We're running a survey to understand how people are using AI to learn and whether that's helping, hurting, and replacing tools.

What specific kind of bugs is AI more likely to generate? Do some categories of bugs show up more often? How severe are they? How is this impacting production environments?

Ryan welcomes Anthony Vinci, former senior intelligence officer and author of The Fourth Intelligence Revolution, to explore AI’s evolving role in intelligence in places like translation and image analysis, the challenges of evolving modern tech into government infrastructure, and the importance of democratized intelligence so citizens can keep themselves and loved ones safe.

Ryan sits down with Michael Parker, VP of Engineering at TurinTech to discuss the newest kind of tech debt—AI-generated tech debt. They dive into the uneven productivity results of AI tools, how tech teams are evolving their roles and work in response to these massive technological shifts, and what the nervous developer can do to maintain joy in their work.

Learn how to protect MCP servers from unauthorized access and how authentication of MCP clients to MCP servers works.

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

Here's the lowdown on all the tech from 2025 that you, dear Zoomer, should know about.

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

Ryan welcomes back the mighty Scott Hanselman, VP of Developer Community at Microsoft, for a crossover episode about all things vibe coding.

Pete Johnson, Field CTO, Artificial Intelligence at MongoDB, joins the podcast to say that looking at AI’s impact as a job killer is a flawed metric.

Ryan hosts Akamai data scientist Robert Lester on the show to discuss how the growth of AI bots affects internet traffic, the ways these AI bots differ from the original search engine optimization ones, and why you might not want to mitigate AI bots on your websites.

Ryan sits down with Tom Totenberg, head of release automation at LaunchDarkly, to discuss the perils of taking too many shortcuts in software development, how business pressures and AI code tools have contributed to dangerous corner cutting, and the importance of balancing speed with sustainability to maintain system integrity.

Evaluating question quality and determining the appropriate feedback required some classic ML techniques in addition to our GenAI solution.

MIT and Stanford professor Alex “Sandy” Pentland joins the show to explore the power of communities for shared knowledge and how AI could hurt or help the growth of these communities.

For promising Gen Z students, a career as a software developer seemed like the golden ticket to career stability and success. But in the age of AI, the career promise for Gen Z software developers is gone.

Money is pouring into the AI industry. Will software survive the disruption it causes?

How we feel about AI-generated content, what AI detectors tell us, and why human creativity matters. Also, what is art?

Ryan welcomes Anil Dash, writer and former Stack Overflow board member, back to the show to discuss how AI is not a magical technology, but rather the normal next step in computing’s evolution. They explore the importance of democratizing access to technology, the unique challenges that LLMs’ non-determinism poses, and how developers can keep Stack Overflow’s ethos of community alive in a world of AI.

Ryan sits down with Corey Quinn, Chief Cloud Economist at Duckbill, at AWS re:Invent to get Corey’s patented snarky take on all the happenings from the conference.

Four days, 60,000 developers, and AI-generated perfume. The re:Invent that was.

AI yells at voice agents so you don't have to.

Ryan is joined by Kayvon Beykpour, CEO and founder of Macroscope, to dive into AI-powered code review’s potential for managing large codebases, the need for humans-in-the-loop for PR reviews so AI tools can efficiently and effectively debug, and how AI can increase visibility through summarization at the abstract syntax tree level and high signal-to-noise ratio code reviews.

There's a distinct shift in how enterprises are talking about their AI solutions. Speed and flashiness are giving way to steadier, slower, more focused AI strategies for companies, where market fit and proof points are more important than ever.
