What's left for infrastructure-as-code after AI moves in?
Ryan is joined by Rosemary Wang, Developer Advocate at IBM, to explore what infrastructure as code looks like once AI starts writing and deploying it.
The Stack Overflow Podcast
Agent orchestration is so two-years ago
Ryan welcomes Saahil Jain, CTO of You.com, to discuss why building agents with a 2024 mindset is a mistake as modern models improve at long-horizon tasks, why heavy orchestration layers can hurt model performance more than help it, and why the 2026 competitive edge actually comes from information retrieval and unique data paired with end-to-end evaluation.
The good, the bad, and the AI apps
Ryan welcomes Benny Chen, co-founder of Fireworks AI, to the show to explore what actually makes an AI application good or not, how to balance qualitative signals with quantitative metrics when evaluating AI, and how open-source eval protocols and community efforts are setting the standard for AI evaluation.
How do you turn AI coding chaos into a repeatable playbook?
Vivek Raghunathan, SVP of engineering at Snowflake, joins Leaders of Code at Snowflake Summit to break down the five-stage framework his org used to go from "let chaos reign" to a repeatable, org-wide system for AI-assisted engineering.
Why intent prediction needs more than an LLM
Ryan sits down with Frank Portman, CTO at Yobi, to talk about why next-token prediction, though great for language, isn’t the right inductive bias for forecasting human behavior. They discuss how Yobi builds a “foundation model of behavior” using transformers and graph neural networks instead of chat-style LLMs, and what it takes to run millions of personalization decisions per second while keeping consumer data private.
Code isn’t the only thing causing your production failures
Ryan sits down with Anish Agarwal, CEO and co-founder of Traversal, to chat about why AI coding agents have made writing code easier but running it safely in production harder, why production failures are really caused by interactions between systems and not just the code itself, and how teams can troubleshoot more effectively when traditional observability tools are not enough for agentic AI workflows.
Oh the places you’ll go with spatial data
Ryan is joined by Jeffrey Hightower, VP of Places Data at Microsoft, and Amy Rose, CTO of the Overture Maps Foundation, to chat about their partnership in bringing spatial data to the next generation of Microsoft tools; how Overture’s 50 organization members are creating open, standardized, and interoperable global spatial data sets; and their solutions to the innate challenges of trying to digitally map the world.
You don’t understand DNS like you think you do
Ryan welcomes Cricket Liu, DNS expert and Chief Evangelist at Infoblox, to the show to talk all things DNS. They cover the evolution of one of the oldest DNS server implementations, BIND, and what the future holds for protected DNS configurations; the realities of security threats like DDoS and DNS spoofing; and why outages often trace back to a lack of understanding of DNS’s fundamental role.
The new bottleneck
Engineering teams have upgraded their tools. Have they upgraded how they work?
If context is king, architecture is the castle
Recorded live at the AI Agent Conference, Ryan sits down with Apollo GraphQL CEO Matt DeBergalis to discuss how enterprises can leverage GraphQL and MCP as a structured semantic architecture to feed clean data to autonomous agents, safeguard internal microservices against unprecedented "east-west" data exfiltration risks, and rein in skyrocketing token spend by explicitly querying only the exact context required.
Developers are emotionally attached to their tools
Ryan welcomes Trisha Gee, a Java champion and developer productivity advocate, to explore how AI is transforming the role of IDEs and the broader developer experience; the relevance of traditional tools, muscle memory, the risks of hype; and how to adapt workflows for AI-driven development.
When the cost of code approaches zero, what does engineering leadership look like?
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.
Creating checkpoints by gaslighting a Postgres database
Ryan welcomes Bryan Clark, director of product for Lakebase at Databricks, to discuss what happens when AI agents become the primary creators and users of databases; why agents are “sloppy” about cleaning up infrastructure; and how database branching, scale-to-zero, and centralized access control can help teams keep up with agent-driven development.
Making the OWASP top ten in the vibe code era
Ryan welcomes back Tanya Janca, now part of the OWASP Top 10 team, to discuss what changed in the latest OWASP Top 10 release, how the list shifted from “outdated components” to a broader software supply chain focus, and why they added memory safety and vibe-coding as awareness items.
What it takes to be a player in the international AI game
From the floor of HumanX, Ryan welcomes Songyee Yoon, managing partner at Principal Venture Partners (PVP), to chat about AI development outside the US, from the need to adapt models to local languages and culture to the challenges of the global supply-chain for things like semiconductors to how venture capital is looking at international AI companies.
The find out stage of AI is just supply chain and password protection
In this two-for-one special recorded at HumanX, Ryan is joined by Dataiku’s Florian Douetteau to chat about the governance, orchestration, and data requirements for serious agentic systems and 1Password’s Nancy Wang for a conversation on making agent swarms secure.
Do you have what it takes to run AI in production?
From the floor of HumanX, Ryan Donovan is joined by Peter Salanki, CTO and co-founder of CoreWeave, to chat about what it really takes to run AI in production; the growing importance of observability, utilization, and scheduling; and Peter’s advice for avoiding the trap of over-architecting too early.
Breaking your AI storage bottlenecks
Recorded at HumanX, Ryan sits down with Garima Kapoor and Anand Babu Periasamy, co-founders and co-CEOs of MinIO, to chat about eliminating the storage bottlenecks that leave GPUs underutilized, their partnership with NVIDIA on the new STX reference architecture, and why modern AI infrastructure is converging on S3-compatible object storage.
Pack your agentic stack in Slack
Ryan welcomes Jaime DeLanghe, chief product officer at Slack, to chat about how they’re preparing to integrate everybody’s agents in their chat application.
Your fridge could be a threat to national security
On the floor of HumanX, Ryan is joined by Adam Meyers, Senior VP of Counter Adversary Operations at Crowdstrike, for a deep dive on their latest Global Threat Report that tracks over 281 adversaries across nation states, e-crime, and hacktivist organizations.
“You can't vibe code scale”: What the AI hype gets wrong about software engineering
Because someone still has to own the consequences of what gets built and whether it can function at scale.
Observability and human intuition in an AI world
In this two-for-one episode recorded at HumanX, Ryan is first joined by Christine Yen, CEO of Honeycomb, to discuss how AI compresses the software development lifecycle, making observability about capturing the right telemetry. Then, Spiros Xanthos, founder and CEO of Resolve AI, shares with us how AI coding increases code volume but decreases human intuition, making production operations harder than ever.
How Braze’s CTO is rethinking engineering for the agentic area
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.
Connecting the dots for accurate AI
At HumanX, Ryan is joined by Philip Rathle, CTO at Neo4j to discuss what knowledge context means for AI agents, how limitations like stale training data make the model-only approach to agents a bad fit for enterprise environments, and how Graph RAG raises the bar for accuracy and reduces context rot by combining vectors with a knowledge graph so agents are more targeted and connected.