We’re doing a live show in Denver this July, Danilo Alonso has seen the ‘developer replacement’ hype cycle many times, Dan Sinker says we’re in the Who Cares Era, Cap looks like a solid alternative to typical CAPTCHA solutions, Michael Flarup on the return of texture, depth, and expressiveness in UI & Kan is an open source alternative to Trello.

In July of 2020, Joran Dirk Greef stumbled into a fundamental limitation in the general-purpose database design for transaction processing. This sent him on a path that ended with TigerBeetle, a redesigned distributed database for financial transactions that yielded three orders of magnitude faster OLTP performance over the usual (general-purpose) suspects.

On this episode, Joran joins Jerod to explain how TigerBeetle got so fast, to defend its resilience and durability claims as a new market entrant, and to stake his claim at the intersection of open source and business. Oh, plus the age old question: Why Zig?

Anurag Goel, Founder/CEO of Render, joins Adam to discuss what they’re doing to solve cloud problems for application developers. They just raised $80M they don’t even need and they’re poised to solve boring problems like object storage, and less boring things like building for the AI era.

Kurt Mackey is back for a deep dive into what it takes to build the developer cloud. Kurt joins Adam to discuss the alliance between companies and cloud, something Kurt refers to as the “Rebel Alliance,” cloud complexity vs usability, Fly’s future with Postgres and why they’ve waited, thoughts on Neon and Supabase (Kurt shares a hot take), and our CDN saga and plan to build a simple CDN on Fly called Pipely (still a Pipedream).

We are at GenAI saturation, so let’s talk about scikit-learn, a long time favorite for data scientists building classifiers, time series analyzers, dimensionality reducers, and more! Scikit-learn is deployed across industry and driving a significant portion of the “AI” that is actually in production. :probabl is a new kind of company that is stewarding this project along with a variety of other open source projects. Yann Lechelle and Guillaume Lemaitre share some of the vision behind the company and talk about the future of scikit-learn!

Daniel Quinn weighs in on how to develop with Docker The Right Way, Mitchell Hashimoto says Ghostty will be publicly released this coming December, Kevin Li writes about the value of learning how to learn, The Browser Company moves on from Arc & the React Native team ships its new architecture.

We are on the other side of “big data” hype, but what is the future of analytics and how does AI fit in? Till and Adithya from MotherDuck join us to discuss why DuckDB is taking the analytics and AI world by storm. We dive into what makes DuckDB, a free, in-process SQL OLAP database management system, unique including its ability to execute lighting fast analytics queries against a variety of data sources, even on your laptop! Along the way we dig into the intersections with AI, such as text-to-sql, vector search, and AI-driven SQL query correction.

Abi Noda, co-founder and CEO at DX, joins the show to talk through data shared from the Stack Overflow 2024 Developer Survey, why devs are really unhappy, and what they’re doing at DX to help orgs and teams to understand the metrics behind their developer’s happiness and productivity.

How do you systematically measure, optimize, and improve the performance of LLM applications (like those powered by RAG or tool use)? Ragas is an open source effort that has been trying to answer this question comprehensively, and they are promoting a “Metrics Driven Development” approach. Shahul from Ragas joins us to discuss Ragas in this episode, and we dig into specific metrics, the difference between benchmarking models and evaluating LLM apps, generating synthetic test data and more.

Chris Stjernlöf got nerd-sniped and ended up writing down his practices of reliable software design, Ben Visness has had enough with the npm community’s propensity to pull in micro-libraries to suit every need, “Stay SaaSy” makes three metaphors for problem solving categories, Troy Hunt takes us inside the “3 billion people” National Public Data breach & Dasel is one data tool to rule them all.

You might have heard that “AI is only as good as the data.” What does that mean and what data are we talking about? Chris and Daniel dig into that topic in the episode exploring the categories of data that you might encounter working in AI (for training, testing, fine-tuning, benchmarks, etc.). They also discuss the latest developments in AI regulation with the EU’s AI Act coming into force.

Database aficionado, Ben Johnson, joins Jerod to answer the age ol’ question: which database should you use? Answering that isn’t always easy, which means it’s time to play the “It Depends” jingle & weigh (some of) the options.

We’re talking OpenAPI this week! Kris & Johnny are joined by Jamie Tanna, one of the maintainers of oapi-codegen, to discuss OpenAPI, API design philosophies, versioning, and open source maintenance and sustainability. In addition to the usual laughs and unpopular opinions, this week’s episode includes a Changelog++ section that you don’t want to miss.

Benn Stancil’s weekly Substack on data and technology provides a fascinating perspective on the modern data stack & the industry building it. On this episode, Benn joins Jerod to dissect a few of his essays, discuss opportunities he sees during this slowdown & explain why he thinks maybe we should disband the analytics team.

We’ve all heard about breaches of privacy and leaks of private health information (PHI). For healthcare providers and those storing this data, knowing where all the sensitive data is stored is non-trivial. Ramin, from Tausight, joins us to discuss how they have deploy edge AI models to help company search through billions of records for PHI.

We’re back with another spicy YepNope debate! This time, Nick & regular guest Eric Clemmons are arguing that web development should need a build step, while KBall & special guest Amy Dutton argue that we really shouldn’t. Of course, the stance each panelist is taking is assigned ahead of time. Is that how they really feel? Tune in to find out!

Birk Jernström from Polar joins the show to tell us all about the creator platform for developers: why he built it, how it works, why it works how it works, what’s in store for the future & we even give Birk some super deep UX feedback on the funding flow.

In this episode we answer any/all questions from a new Go developer. Features, best practices, quirks of the language… it’s all on the table for discussion.

Nous Research has been pumping out some of the best open access LLMs using SOTA data synthesis techniques. Their Hermes family of models is incredibly popular! In this episode, Karan from Nous talks about the origins of Nous as a distributed collective of LLM researchers. We also get into fine-tuning strategies and why data synthesis works so well.

Hello 2024! We’re kicking off the year with Dan Moore, author of ‘Letters to a New Developer’ — a blog series of letters of what Dan wished he had known when starting his developer career. We discuss the value of online communities for new developers, the importance of communication skills, and the need to stay relevant in a rapidly changing industry. Dan shares his best advice for new developers, including the importance of saying no, leaving code better than you found it, and the value of skill stacking. So much wisdom and advice in this episode!

It seems like everyone is interested in Rust these days. Even the most popular Python linter, Ruff, isn’t written in Python! It’s written in Rust. But what is the state of training or inferencing deep learning models in Rust? In this episode, we are joined by Nathaniel Simard, the creator burn. We discuss Rust in general, the need to have support for AI in multiple languages, and the current state of doing “AI things” in Rust.

A hoy hoy! Our old friend Nick Nisi does his best to bring up TypeScript, Vim & Tmux as many times as possible while we discuss a new batch of web browsers, justify why we like the ones we do & try to figure out what it’d take to disrupt the status quo of Big Browser.

Today we’re talking with Alice Merrick & Andy Walker about building a world-class developer experience. You know it when you see it, things just feel right. But it’s more than just a pleasant UI or lipstick on a pig (which is a saying), it really matters.

This week we’re joined by Solomon Hykes, the creator of Docker. Now he’s back with his next big thing called Dagger — CI/CD as code that runs anywhere. We’re users of Dagger so check out our codebase if you want to see how it works. On today’s show Solomon takes us back to the days of Docker, what it was like on that 10 year journey, his transition from Docker to Dagger, Dagger’s community-led growth model, their focus on open source and community, how it works, and even a cameo from Kelsey Hightower to explain how Dagger works.

So, do we like generics or not? Some people feared they’d be the end of the language. Others were very hopeful, and had clear use cases, and were thrilled about the feature coming to the language. It was also often touted as the reason a lot of people didn’t adopt Go. So what do we think now? Mat and Kris are joined by Roger Peppe and Bryan Boreham to discuss the state of Generics in Go.

Chris sat down with Varun Mohan and Anshul Ramachandran, CEO / Cofounder and Lead of Enterprise and Partnership at Codeium, respectively. They discussed how to streamline and enable modern development in generative AI and large language models (LLMs). Their new tool, Codeium, was born out of the insights they gleaned from their work in GPU software and solutions development, particularly with respect to generative AI, large language models, and supporting infrastructure. Codeium is a free AI-powered toolkit for developers, with in-house models and infrastructure - not another API wrapper.

This week Adam is joined by Scott Johnston, CEO of Docker. Scott shares his journey to the CEO role, how he’s leading the company to not only grow revenue, but to also invest in developer facing features, their shift from a enterprise sales focus to a PLG driven model, and we even talk about Docker Desktop, the competition it faces, and the struggle they face when considering making it open source.

Large Language Models (LLMs) continue to amaze us with their capabilities. However, the utilization of LLMs in production AI applications requires the integration of private data. Join us as we have a captivating conversation with Jerry Liu from LlamaIndex, where he provides valuable insights into the process of data ingestion, indexing, and query specifically tailored for LLM applications. Delving into the topic, we uncover different query patterns and venture beyond the realm of vector databases.

This week Adam is joined by Alex Gallego, Founder & CEO at Redpanda Data, to share his builder journey to create the Redpanda streaming data platform.