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Changelog Media

Your one-stop shop for all Changelog podcasts. Weekly shows about software development, developer culture, open source, building startups, artificial intelligence, shipping code to production, and the people involved. Yes, we focus on the people. Everything else is an implementation detail.

Changelog Master Feed

We're making some big Changelog changes in 2025, the previously featured Stanford study on ghost engineers doesn't live up to the hype, Git ingest is a simple service that turns any GitHub repository into a simple text ingest of its codebase, Simon Willison dishes out some hard-earned wisdom he acquired by working at Lanyrd / Eventbrite & Matheus Lima warns us about six mistakes that new managers make.

A new era for the Changelog Podcast Universe (Changelog News #124)

With so many great programming languages having emerged in the last decade, many of them purpose-built, when and where does Go still make sense and how do you make the case for it at work?

Pitching Go in 2025 (Go Time #339)

Today, Chris explores Shopify Magic and other AI offerings with Mike Tamir, Distinguished ML Engineer and Head of Machine Learning, and Matt Colyer, Director of Product Management for Sidekick. They talk about how Shopify uses generative AI and LLMs to enhance their products, and they take a deeper dive into Sidekick, a first-of-its-kind, AI-enabled commerce assistant that understands a merchant’s business (products, orders, customers) and has been trained to know all about Shopify.

Sidekick is an AI Shopify expert (Practical AI #299)

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).

Building the developer cloud (Changelog Interviews #621)

Gerhard is back for Kaizen 17! We discuss our CPU.fm changes in-depth, detail new Zulip / Neon integrations & put our Pipedream to the test. Oh, and a Gerhard surprise (of course)!

Kaizen! Three wise men? (Changelog & Friends #73)

Phillip Carter, Principal PM at Honeycomb, joins Justin & Autumn to discuss his work at Microsoft & Honeycomb, building AI infrastructure & more.

AI IRL at Honeycomb (Ship It! #134)

This episodes diverges from our traditional fare. I've reviewed the 50 previous editions and picked (IMHO) the coolest code, best prose & my favorite podcast episode from each month!

The code, prose & pods that shaped 2024 (Changelog News #125)

Mat gathers the entire cast (sans Natalie, sadly) alongside our producer, Jerod Santo, for one last Go Time. That's right, this is Go Time's finale episode. After eight years and 340 episodes, we are going out on top. Join us one last time, you won't regret it! 

We share our feelings, reminisce on the good times, list some of our favorite moments & share a few opinions, which may (or may not) be unpopular. 😉

That's Go Time! (Go Time #340)

Mitchell Hashimoto joins the show to discuss Ghostty, the newest terminal in town. Mitchell co-founded HashiCorp, took it all the way to IPO, exited in 2023—and now he's working on a terminal emulator called Ghostty. Ghostty is set to 1.0 this month, so we sat down to talk through all the details.

We ain't afraid of no Ghostty! (Changelog Interviews #622)

Daniel and Chris groove with Jeff Smith, Founder and CEO at CHRP.ai. Jeff describes how CHRP anonymously analyzes emotional wellness data, derived from employees' music preferences, giving HR leaders actionable insights to improve productivity, retention, and overall morale. By monitoring key trends and identifying shifts in emotional health across teams, CHRP.ai enables proactive decisions to ensure employees feel supported and engaged.

Mozart to Megadeath at CHRP (Practical AI #300)

Production ML systems include more than just the model. In these complicated systems, how do you ensure quality over time, especially when you are constantly updating your infrastructure, data and models? Tania Allard joins us to discuss the ins and outs of testing ML systems. Among other things, she presents a simple formula that helps you score your progress towards a robust system and identify problem areas.

Testing ML systems (Practical AI #74)

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