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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.

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A new AI-led tech role has emerged with a massive increase of job postings, Corey Quinn explains why younger devs won't tolerate pain in the AWS, Thomas Ptacek makes the case that you should write an agent, Paul Kinlan goes deeper on his dead framework theory, and Andrew Gallagher says to stop vibe coding your unit tests.

This new AI role is exploding (Changelog News #169)

On this seventh iteration of our award-worthy game show filled with obscure jargon, fake definitions, and expert tomfoolery: past winners battle to determine the champion of champions. (Also, Adam.)

#define: sheer resistance (Changelog & Friends #116)

Andrew Nesbitt builds tools and open datasets to support, sustain, and secure critical digital infrastructure. He's been exploring the world of open source metadata for over a decade. First with libraries.io and now with ecosyste.ms, which tracks over 12 million packages, 287 million repos, 24.5 billion dependencies, and 1.9 million maintainers.

What has Andrew learned from all this, who is using this open dataset, and how does he hope others can build on top of it all? Tune in to find out.

The world of open source metadata (Changelog Interviews #665)

Ahmad Alfy explains how URLs are state containers, Shrivu Shankar shares how he uses every Claude Code feature, Yusuf Aytas laments how AI broke technical interviews, Wu Xiaoyun tells how he saved TikTok $300k during his internship, and TOON is a new serialization format to save us some LLM tokens.

The overlooked power of URLs (Changelog News #168)

It's a FRIGHT...when your record a podcast with dead projects all around. Tech debt, poor choices, timing, market shift, and optimizing for the wrong things are all lurking around waiting to pop out at you! Just don't forget to push record.

We see dead projects (Changelog & Friends #115)

Adam Jacob joins us to discuss how agentic systems for building and managing infrastructure have fundamentally altered how he thinks about everything, including the last six years of his life. Along the way, he opines on the recent AWS outage, debates whether we're in an AI-induced bubble, quells any concerns of AGI and a robot uprising, eats some humble pie, and more.

Agentic infra changes everything (Changelog Interviews #664)

The Dead Internet Theory dies, Geoffrey Litt tries to code like a surgeon, Matt Sephton thinks spreadsheets are great for UI design, Nate Meyvis advocates for front-end maximalism, Hemant Pandey thinks 9-5 employment is a great option for most, David Miranda compares React to Backbone in 2025.

Code like a surgeon (Changelog News #167)

It's our first Kaizen after the big Pipely launch in Denver and we have some serious mopping to do. Along the way, we brainstorm the next get-together, check out our new cache hit/miss ratio, give Pipely a deep speed test, discuss open video standards, and more!

Kaizen! Mop-up job (Changelog & Friends #114)

Ellie Huxtable's magical shell tool, Atuin, won developers' hearts by syncing, searching, and backing up our shell history with ease. Now Ellie is tackling the desktop with a GUI built to help teams make their workflows repeatable, shareable, and reliable.

Bringing Atuin to the desktop (Changelog Interviews #663)

Csaba Okrona lays out exactly what Flow is (then shows you how to engineer your way back to it), a smart vacuum turned against an innocent hacker, Matz and the Ruby core team step up to steward RubyGems, Simon Willison things Claude Skills could be bigger than MCP, and Luke Plant looks at technical debt from a more positive perspective.

The science behind developer flow states (Changelog News #166)

Why is ML is so poorly adopted in small organizations (hint: it's not because they don't have enough data)? In this episode, Kirsten Lum from Storytellers shares the patterns she has seen in small orgs that lead to a successful ML practice. We discuss how the job of a ML Engineer/Data Scientist is different in that environment and how end-to-end project management is key to adoption.

Machine learning at small organizations (Practical AI #207)

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