AI Skills with Matt Pocock
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What is the episode’s introduction and who is the guest?
I got the grillligum my life in building a pretty simple API endpoint using the Grill Me skill. It asked me 35 questions, I kid you not. It was intense and annoying. And it forced me to think more. Today's guest is the creator of this popular skill, Matt Polcock. Matt is a developer turned educator, well known for his Total TypeScript series, and now for his AI skills and educational videos. Today we cover Matt's unusual path into tech after years of being a voice coach and building his own DIY coaching software. Matt's popular skills, Grail Me, Wayfinder, and why these skills became so widespread. Taking inspiration from decades old programming books to build better software. Software with AI and many more.
If you want to understand which software engineering fundamental approaches remain very useful when working with AI agents, this episode is for you. This episode is presented by TurboPuffer, Vector and Full Text Search built on object storage. It's fast, cheap, and extremely scalable. This episode is presented by Linear, and I wanted to take you back in time to remind you how we used to get work done. Back when every lineup code was written by an engineer like you or me, a track Hacker's job was to keep people in sync without slowing people down. Linear was built to be fast and low friction, and you could tell. In last year's Pragmatic Engineer survey, Linear was the most loved tracker tool, and Jira the most disliked one for its sluggish performance.
And data coming from the Pragmatic Engineer audience showed how Linear started to gain traction against existing tools, especially as startups and mid-sized companies. And since then, Linear grew up. They added all the stuff that larger companies need to manage work, projects, initiatives, roadmaps, and customer requests. And large companies started to switch. For example, healthcare company Oscar helped move 600 engineers from Jira to Lanier. OpenAI started with a hundred seats and moved all three thousand staff without any mandate. Coinbase, Cash App, Brexit and Ramp are all on the near. Many of them saw Linear as a way to consolidate a single tool that brings planning and building together. So now let's fast forward to today.
When you have AI agents inside a company, those agents need context to work well. They need access to things like specs, customer requests, history. Oh wait, these are all already in linear. So when agents arrived, Linear became the ideal context layer. Today, 80% of enterprise workspaces in Linear have adopted agents. You can use agents like Codecs, Cloud Code Linear Agent, or your own agent. Coinbase and RAM both built their own internal agents and describe Blinear as a place that their agent goes and picks up the context before starting work. See how it works at linear dot app slash pragmatic.
Matt, it's great to have you on the podcast. Great to finally be here. I'm a huge fan. I've watched so many of these. I feel like this is like the tiny desk of being a software engineer. You know what I mean? This is this is big stuff, so I'm glad to be here.
And it's also great to reconnect because about a year ago we we we had lunch uh after at Microsoft Build as well, which which was really fun. But now it's it's good to jump into this. And with this, I wanted to ask about your background. You un unlike many people in tech and on this podcast, you didn't start out to study computer science, right?
Absolutely not. So For six years before I became a developer, I was a voice coach. I was a singing teacher working uh in London and working in X tool when I went to university. I was teaching accents, I was teaching singing, I was teaching voice, I did a master's in it. I spent a lot of time thinking that was what my career was gonna be. You know, I didn't have any inkling of tech, didn't sort of think about it at all. I sort of ran my own website and stuff, but yeah. Yeah, so I did that for a long time and it's been an extremely important influence on my life and I think my personality as well. Where where did the
voice come from and what do you do as a voice coach?
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Chapters
6 chapters
1
What is the episode’s introduction and who is the guest?
0:00–6:10
2
How did Matt transition from a voice‑coach career to software engineering?
6:10–18:44
3
What motivated Matt to start contributing to open‑source projects?
18:44–31:52
4
What was Matt’s experience working at Vercel and on Turbopack?
31:52–51:54
5
How was the Total TypeScript course created and why did it succeed?
51:54–1:19:00
6
How is AI changing technical education and the way engineers learn?
1:19:00–1:35:30