Generating components, not tokens
On today’s episode, Ben and Ryan chat with Laly Bar-Ilan, Chief Scientist at Bit.
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Wait, what is agentic AI?
Is “agentic AI” just a buzzword, or is it the sea change it seems?
How AI can prevent clinician burnout
In today’s episode, Ryan sits down with Richard “Spencer” Schaefer, cofounder and CTO of Lunar Analytics and a federal AI officer, and Caroline Zhang, cofounder and CTO of Knowtex, which provides AI-powered voice technology to automate workflows. They talk about safeguarding patient privacy, how AI changes doctor-patient interactions and healthcare delivery, the challenges inherent in rolling out AI technology, and the importance of quality data to fuel AI initiatives. Also included: a chat with Jeff Berkowitz, cofounder and CEO of Delve Deep Learning.
Like self-driving cars, fully AI-automated sysadmins don't exist
As with cars, there are few system administration tasks that involve little to no automation.
How do you fact-check an AI?
Ryan chats with Amr Awadallah, founder and CEO of GenAI platform Vectara about how retrieval-augmented generation (RAG) has advanced, why fact-checking and accurate data are essential in building AI applications, and how Vectara’s Mockingbird model seeks to minimize hallucinations.
Bottom of the first: A veteran VC’s take on the AI landscape
Ryan welcomes Tomasz Tunguz of Theory Ventures back to the podcast to talk about the intersection of AI and venture capital, the implications of AI on the labor market, and the future of AI applications.
Open-source AI: Are younger developers leading the way?
In March, over 1,000 developers and technologists gave us insights into what they think about open source and the role it plays with AI.
Is AI a bubble or a revolution? The answer is yes.
At HumanX 2025, Ryan sat down with HumanX CEO Stefan Weitz and Crunchbase CEO Jager McConnell to talk about where the money is in the AI space, where most enterprise AI strategies fall short, how companies can build business models when AI tech is evolving so quickly, and why this is AI’s microservices moment.
Not all AI is generative: Efficient scheduling with mathematics
Efficiently solving a complex scheduling problem using simulated annealing.
Boots on the ground: Holistic AI and Audioshake at HumanX
Two interviews for the price of one, direct from HumanX 2025! Ryan sits down with Raj Patel, AI transformation lead at Holistic AI, and then chats with Audioshake cofounder and CEO Jessica Powell.
“Are AI agents ready for the enterprise?”
Deepak Singh, VP of Developer Agents and Experiences at AWS, helps Ryan break down the hype around agentic AI in software development. They cover the definition and real-world functionality of AI agents, how developers can integrate them into existing workflows, and the importance of establishing guardrails to ensure trust and security in agentic AI.
“The power of the humble embedding”
Ryan speaks with Edo Liberty, Founder and CEO of Pinecone, about building vector databases, the power of embeddings, the evolution of RAG, and fine-tuning AI models.
An AI future free of slop
Stack Overflow CEO Prashanth Chandrasekar sat down with Ryan at HumanX 2025 to talk about how Stack is integrating AI into its public platform, the enormous importance of a high-quality knowledge base in your AI journey, how AI tools are empowering junior developers to build better software, and much more.
Improving error monitoring with AI
Tillman Elser, AI/ML lead at Sentry, joins Ryan for a conversation about improving error monitoring with AI and ML. They talk through the challenges of analyzing stack traces, the innovative use of embeddings to improve error grouping, the trial-and-error process of developing algorithms, and where Sentry’s AI capabilities are headed next.
What we learned at TDX 2025
Some high-level takeaways, with more to come.
Can climate tech startups address the current crisis?
Lisbeth Kaufman, Head of Climate Tech at AWS, sits down with Ryan to talk about her work helping climate tech startups get off the ground and the role startups can play in addressing the climate change crisis. She highlights a few projects to get excited about, including ones focused on fusion energy and sustainable agriculture.
A look under the hood: How (and why) we built Question Assistant
Evaluating question quality and determining the appropriate feedback required some classic ML techniques in addition to our GenAI solution.
How can AI perform on the edge?
What are the capabilities, constraints, and benefits of running AI models on edge devices?
“Translation is the tip of the iceberg”: A deep dive into specialty models
Olga Beregovaya, VP of AI at Smartling, joins Ryan and Ben to explore the evolution and specialization of language models in AI.
Variants of LoRA
Want to train a specialized LLM on your own data? The easiest way to do this is with low rank adaptation (LoRA), but many variants of LoRA exist.
Writing tests with AI, but not LLMs
How Diffblue leverages machine learning techniques to write effective unit tests.
Solving the data doom loop
Ken Stott, Field CTO of API platform Hasura, tells Ryan about the data doom loop: the concept that organizations are spending lots of money on data systems without seeing improvements in data quality or efficiency.
How to harness APIs and AI for intelligent automation
APIs have steadily become the backbone of AI systems, connecting data and tools seamlessly. Discover how they can drive scalable and secure training for AI models and intelligence automation.
“In the short term, more chaos”: What’s next for API design
Sagar Batchu, CEO and cofounder of API tooling company Speakeasy, talks with Ryan about the evolving API landscape, AI integration, the role of human technologists in an increasingly automated environment, and what people building APIs right now should keep in mind.