Ryan is joined by Jan Liphardt, CEO and co-founder of OpenMind, to chat about the rapidly evolving world of humanoid robotics and what it means for humans, why OpenMind is building an open source operating system for robots that processes logic in natural language, and how putting Asimov’s Laws on the blockchain might be the key to robotics guardrails.
The difference between AI that impresses people in demos and AI that drives production value is context.
Ryan welcomes Kari Briski, NVIDIA’s VP of Generative AI Software for Enterprise, to the show to explore how a chip manufacturer got into the model development game.
From interoperability to knowledge architecture to creating AI tools people can actually use, here’s a recap of what we learned from DeveloperWeek 2026.
Ryan sits down with Member of the Technical Staff at Anthropic and Model Context Protocol co-creator David Soria Parra to talk the evolution of MCP from local-only to remote connectivity, how security and privacy fit into their work with OAuth2 for authentication and authorization, and how they’re keeping MCP completely open-source and widely available by moving it to the Linux Foundation.
Ryan welcomes Marcus Fontoura, technical fellow at Microsoft and author of Human Agency in the Digital World, to discuss the intersection of technology, society, and human dignity in a digital-first world.
For most of the web's history, content platforms operated on a simple binary: open or blocked. Then generative AI changed everything.
Ryan welcomes Thibault Sottiaux, OpenAI’s engineering lead on Codex, to discuss how the Codex team dogfoods Codex to build Codex, what distinguishes an agentic coding tool from a chat-based code assistant, and why they’re focusing on a safe and secure agentic SDLC rather than just code generation.
Ryan is joined by Philippe Saade, the AI project lead at Wikimedia Deutschland, to dive into the Wikidata Embedding Project and how their team vectorized 30 million of Wikidata’s 119 million entries for semantic search.
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.
Recorded last December at AWS re:Invent, Ryan welcomes CEO and co-founder of Deepgram, Scott Stephenson, for a conversation on advancing voice AI technology.
There are big hitters in the AI space that use this tech for humanitarian and environmental good—from start-ups fighting climate change to voice recognition experts diagnosing diseases. But you don't need to be backed by AWS or Microsoft to do good. In part two of this series, we dive into how anyone can use AI for good.
In a world where AI is replacing human workers, using up energy and water, and deepening disconnect, is AI for humanitarian good even possible? The answer is yes. In the first part of this two-part series, we're taking a look at just a few AI do-gooders and what they're doing to fight climate change, make healthcare more accessible, and help their communities.
Ryan is joined by Professor Tom Griffiths, the head of Princeton University’s AI Lab, to dive into findings from his new book The Laws of Thought, which explores the history of the philosophy, mathematics, and logic that underlie artificial intelligence, and scientists' efforts to describe our minds using mathematics.
Not only is there a future for software development, but we’re on the cusp of enormous demand for code developed by humans.
We have another two-for-one special this week, with two more interviews from the floor of re:Invent.
Quality software still needs high-quality code, AI agents or not.
Two guests for the price of one! This episode has two interviews recorded at AWS re:Invent back in December.
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.
