Stay updated with the latest developments in Artificial Intelligence
Ryan sits down with Div Garg, CEO at AGI Inc., to talk about running AI agents entirely on mobile devices, optimizing models for edge computing chips, and building safety mechanisms into autonomous app interactions.
An MLOps workflow for evaluating deploying and rolling back AI applications
Founded in 2008, Stack Overflow’s public platform is used by nearly everyone who codes to learn, share their knowledge, collaborate, and build their careers.
Ryan chats with David Burns, Head of Developer Advocacy and Open Source at BrowserStack, about the value of professional skepticism in an AI-driven world, applying test-driven development to agentic engineering, and why fixing flaky tests comes down to managing application state.
Ryan chats with the GM of Slack, Rob Seaman, about how their new Code Channels feature is bringing multiplayer AI to your team chats.
Ryan chats with Anush Elangovan, VP of Software at AMD, about ROCm's open-source unified toolchain for GPUs, how agentic AI is drastically lowering the barrier to entry for low-level hardware programming, and the rapid convergence of software and hardware development timelines.
Ryan sits down with Tim O'Reilly, founder and CEO at O'Reilly Media, to talk about the role of books as user interfaces to knowledge, the power of "magic words" to extract better outputs from AI, and why human taste is becoming highly valuable as knowledge becomes a commodity.
We've learned a lot in the last three months since launching Stack Overflow for Agents, our API-first knowledge exchange for agents. Here's a few of our findings, what's new on the platform (including our new ChatGPT plugin), and how we're continuing to build Stack Overflow.
Ryan chats with Kevin Frazier, director of the AI Innovation and Law program at the University of Texas School of Law, about the legal and social impacts of data centers, the realities of workforce disruption, and regulating AI for child safety using existing consumer protection laws.
Ryan chats with Sam Curry, CSO at Zscaler, about where human intelligence sits in the new security landscape with AI, why shifting security protections closer to applications helps limit probes for vulnerabilities, and why building more resilient code infrastructure is the best way to address the…
For the past few years, we’ve been looking at ways to bring a little more of the individual developer back to Stack.
Ryan welcomes Markus Eisele to the program to talk about why your coding agent should be writing Java.
Ryan chats with Srini Venkatesan, CTO at PayPal, about validating AI-generated deterministic code for security, developing autonomous SDLC harnesses with iterative feedback loops, and creating a seamless headless checkout experience.
Ryan chats with Greg Jennings, VP of Engineering for AI Products at Anaconda, about what it takes to build a secure-by-default AI coding agent, why prompts shouldn't be treated as strict security guardrails, and how Anaconda is using strategic acquisitions to secure the AI software supply chain.
In our 2026.6 release, we are shipping updates across administrative security, programmatic API control, developer portal integrations, and platform-wide accessibility—ensuring both your engineers and your AI agents act on verified, decision-grade knowledge.
Andi Gutmans, head of Agentic Data Cloud at Google, returns for the second half of his Leaders of Code conversation to talk through the cost and infrastructure side of agentic development. ICYMI, part one covered judgment, code review, and data activation.
Ryan sits down with Tim Lindholm, an early contributor to the Java language at Sun Microsystems, to chat about what it was like building one of the most popular programming languages ever at its inception, why it was strategically important for the Java team to create a cross-platform ABI to…
Ryan chats with Leo de Moura, Senior Principal Applied Scientist at AWS and the creator of the Lean language, about proving correctness in AI agents with the Lean language, how automated reasoning complements probabilistic AI models, and the use of AI for continuous code optimization.
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