What we learned at TDX 2025
Some high-level takeaways, with more to come.
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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.
Why build your own vector DB? To process 25,000 images per second
Ben and Ryan chat with Babak Behzad, senior engineering manager at Verkada, about running a pipeline that vectorizes 25,000 images per second into a custom-built vector database. They discuss whether the speed is due to technical brains or brawn, the benefits of processing on device vs. off, and the importance of privacy when using image recognition on frames from a video camera.
The developer skill you might be neglecting
Ben and Ryan talk with Geoffrey (Jef) Huck, a software developer turned public speaking coach, about the importance of soft skills in the tech industry—in particular, speaking and communication skills. Their conversation touches on how Huck’s experiences with anxiety shaped his efforts to become a better communicator, practical techniques for dispelling anxiety and connecting with the audience, and the MVP approach to public speaking.
Robots building robots in a robotic factory
Ryan talks with Sterling Chin, a senior developer advocate at Postman, about the intersection of APIs and AI. They cover the emergence of AI APIs, the importance of quality APIs for AI integrations, and the evolving role of GraphQL in this new landscape. Sterling explains how some organizations are shifting toward an API-first development approach and talks about the future of data access in the agentic era, where APIs will play a crucial role in AI interactions.
“Data is the key”: Twilio’s Head of R&D on the need for good data
In this episode, Ben and Ryan sit down with Inbal Shani, Chief Product Officer and Head of R&D at Twilio. They talk about how Twilio is incorporating AI into its offerings, the enormous importance of data quality in achieving high-quality responses from AI, the challenges of integrating cutting-edge AI technology into legacy systems, and how companies are turning to AI to improve developer productivity and customer engagement.
How AI apps are like Google Search
Happy New Year! In this episode, Ryan talks with Jetify founder and CEO Daniel Loreto, a former engineering lead at Google and Twitter, about what AI applications have in common with Google Search. They also discuss the challenges inherent in developing AI systems, why a data-driven approach to AI development is important, the implications of non-determinism, and the future of test automation.
How developers (really) used AI coding tools in 2024
During the holidays, we’re releasing some highlights from a year full of conversations with developers and technologists. Enjoy! We’ll see you in 2025.
Legal advice from an AI is illegal
Mark Doble, CEO of Alexi, an AI-powered litigation platform, joins Ben to talk about GenAI’s transformative effect on the legal world. Their conversation touches on the importance of ensuring accurate results and eliminating hallucinations when AI tools are used for legal work, how lawyers (like the rest of us) can adapt to GenAI, and what Alexi’s tech stack looks like.
It’s not what you know, it’s how you know you know it
The complex relationship of give-and-take in the knowledge journey is untangled in the results from the latest Stack Overflow Knows survey.
“You don’t want to be that person”: What security teams need to understand about developers
The home team is joined by Kinnaird McQuaid, founder and CTO of NightVision, which offers developer-friendly API and web app security testing. Kinnaird talks about his path from school-age hacker to white-hat security expert, why it’s important to build security practices into the software development lifecycle, how GenAI is changing security testing, and what security teams need to understand about developers’ working lives.
From bugs to performance to perfection: pushing code quality in mobile apps
Ben and Ryan talk all things mobile app development with Kenny Johnston, Chief Product Officer at Instabug. They explore what’s unique about mobile observability, how AI tools can reduce developer toil, and why user experience matters so much for app quality.
Four approaches to creating a specialized LLM
Wondering how to go about creating an LLM that understands your custom data? Start here.
Even high-quality code can lead to tech debt
Ben talks with Eran Yahav, a former researcher on IBM Watson who’s now the CTO and cofounder of AI coding company Tabnine. Ben and Eran talk about the intersection of software development and AI, the evolution of program synthesis, and Eran’s path from IBM research to startup CTO. They also discuss how to balance the productivity and learning gains of AI coding tools (especially for junior devs) against very real concerns around quality, security, and tech debt.
Your docs are your infrastructure
Fabrizio Ferri-Benedetti, who spent many years as a technical writer for Splunk and New Relic, joins Ben and Ryan for a conversation about the evolving role of documentation in software development. They explore how documentation can (and should) be integrated with code, the importance of quality control, and the hurdles to maintaining up-to-date documentation. Plus: Why technical writers shouldn’t be afraid of LLMs.
The open-source ecosystem built to reduce tech debt
Today’s guest is Jonathan Schneider, co-founder and CEO of Moderne and creator of OpenRewrite, an open-source automated refactoring ecosystem for source code built to help developers eliminate tech debt. He tells Ben and Ryan about the challenges of automatic refactoring, how Java continues to evolve, and what kind of impact tech debt has on software development. Jonathan also describes the transition from open-source project to startup, why clean code is so important, and the role AI plays for developers right now.