This week we’re talking to Rachel Potvin, former VP of Engineering at GitHub about what it takes to scale engineering. Rachel says it’s a game-changer when engineering scales beyond 100 people. So we asked to her to share everything she has learned in her career of leading and scaling engineering.
Amal sits down for a one-on-one with Alex Russell, Microsoft Partner on the Edge team, and former Web Standards Tech Lead for Chrome, whose recent post, The Market for Lemons, stirred up a BIG conversation in the web development community.
Have we really lost a decade in potential progress? What happened? Where do we go from here?
Our “what’s new in Go” correspondent Carl Johnson joins Mat & Johnny to discuss… what’s new in Go 1.20, of course! What’d you expect, an episode about Rust?! That’s preposterous…
Tim McNamara is known as New Zealand’s Rust guy. He is the author of Rust in Action, and also a Senior Software Engineer at AWS, where he helps other builders with all things Rust.
The main reason why Gerhard is intrigued by Rust is the incredible resource frugality. Fewer CPUs means less energy used, which is good for the planet, and good for the monthly bill. This becomes most noticeable at Amazon’s scale, when S3, Lambda, CloudFront and other services start adding Rust components.
We’ve been hearing about “serverless” CPUs for some time, but it’s taken a while to get to serverless GPUs. In this episode, Erik from Banana explains why its taken so long, and he helps us understand how these new workflows are unlocking state-of-the-art AI for application developers. Forget about servers, but don’t forget to listen to this one!
Alice Girard Guittard finds out how much she could you really get out of a $4 VPS, Brett Cannon wonders if using TOML for .env files is a good idea, Nic Mulvaney details how they count unique visitors to a website without using cookies, UIDS, or fingerprinting, after a few months, Chris Coyier is still using the Arc browser & Alex Kladov pens a love letter to Deno.
This week we invited our friend Mat Ryer to join us for some good conversation about some Git tooling that’s been on our radar. You may know Mat from Go Time and also Grafana’s Big Tent, which we help to produce. We speculate, we discuss, we laugh, and Mat even breaks into song a few times. It’s good fun.
The panel dives into the current hot topic that is Generative AI. They start by defining it (a surprisingly difficult topic), then go into experiences they’ve had, how to get started working with it as a developer, and where they think it will and will not be useful in the near future.
A quick look at the history of building web apps, followed by a discussion of htmx and how it compares to both modern and traditional ways of building.
Worlds are colliding! This week we join forces with the hosts of the MLOps.Community podcast to discuss all things machine learning operations. We talk about how the recent explosion of foundation models and generative models is influencing the world of MLOps, and we discuss related tooling, workflows, perceptions, etc.
OpenAI’s working on an AI classifier trained to distinguish between AI-written and human-written text, Oz Nova and Myles Byrne created a guide to teach yourself computer science, Charles Genschwap recently realized that all the various programming philosophies can be boiled down into a simple statement about how to work with state, you probably don’t need Lodash or Underscore anymore & Waseem Daher thinks scalability is overrated.
A deep dive into Qwik, how it makes your apps fast by default, and the carefully calibrated amount of “magic” that makes it uniquely powerful.
It’s “Call For Papers” (CFP) season in Go land, so we gathered some seriously experienced conference organizers to help YOUR submission be the best ever.
In our ops & infra world, we learn to optimise for redundancy, for mean time to recovery and for graceful degradation. We instinctively recognise single points of failure, and try to mitigate the risks associated with them.
For some years now, Daniel Vassallo has been doing the same, but in the context of life & work. Daniel talks about the role of randomness, about learning from small wins & about optimising for a lifestyle that matches your true preferences. Apparently, ideas too should be treated like cattle, not pets.
What’s the current reality and practical implications of using 3D environments for simulation and synthetic data creation? In this episode, we cut right through the hype of the Metaverse, Multiverse, Omniverse, and all the “verses” to understand how 3D assets and tooling are actually helping AI developers develop industrial robots, autonomous vehicles, and more. Beau Perschall is at the center of these innovations in his work with NVIDIA, and there is no one better to help us explore the topic!
Jeremia Kimelman takes stock of his “data tool belt”, Build Your Own Redis with C/C++ is ready to read, giscus is a comments system powered by GitHub Discussions, Matt Rickard says prompt engineering shouldn’t be a thing and won’t be a thing in the future & Kolja Lubitz’s ALPACA is engine for building adventure games and interactive comics.
This week we’re talking about mainframes with Cameron Seay, Adjunct Professor at East Carolina University and a member of the Governing Board of the Open Mainframe Project. If you’ve been curious about mainframes, this show will be a great guide.
Cameron explains exactly what a mainframe is and how it’s different from the cloud. We talk COBOL and the state of education and opportunities around that language. We cover the state-of-the-art in mainframe land, System Z, Linux on mainframes, and more.
Ole Bulbuk & Sandor SzĂĽcs join Natalie to discuss the ins & outs of long-term code maintenance. What does it take to maintain a codebase for a decade or more? How do you plan for that? What about inheriting a codebase for the long term? Oh, and (how) can AI help?
Last September, at the 🇨🇠Swiss Cloud Native Day, Florian Forster, co-founder & CEO of ZITADEL, talked about why they switched to serverless containers. ZITADEL has a really interesting workload that is both CPU intensive and latency sensitive. On top of this, their users are global, and traffic is bursty. Florian talks about how they evaluated AWS, GCP & Azure before they settled on the platform that met their requirements.
Creating and sharing reproducible development environments for AI experiments and production systems is a huge pain. You have all sorts of weird dependencies, and then you have to deal with GPUs and NVIDIA drivers on top of all that! brev.dev is attempting to mitigate this pain and create delightful GPU dev environments. Now that sounds practical!
Fred K. Schott joins the party again to discuss all the new and fun changes in Astro 2. Nick and KBall dig in on what’s new, what’s exciting, and what to expect from the framework built around content.
Max Countryman wrote up a framework for prioritizing tech debt, shadcn builds a copy/paste-able UI component library in public, Justin Etheredge shares 20 things he’s learned in his 20 years as a software engineer, Jacob Stopak’s git-sim lets you easily visualize git operations without affecting your repo & Mattias Wadman implemented jq in jq.
This week we’re talking about by Postgres with Craig Kerstiens, Chief Product Officer at Crunchy Data, and a well known ambassador for Postgres. Just Postgres. That’s what this week’s show is about.
Jerod & the gang analyze the State of JS 2022 survey results, play a wicked game of HeadLIES & share some Pro Tips to help you live your best dev life.
Lars is big on Elixir. Think apps that scale really well, tend to be monolithic, and have one of the most mature deployment models: self-contained releases & built-in hot code reloading. In episode 7, Gerhard talked to Lars about “Why Kubernetes”. There is a follow-up YouTube stream that showed how to automate deploys for an Elixir app using K3s & ArgoCD.
More than a year later, how does Lars think about running applications in production? What does simple & straightforward mean to him? Gerhard’s favourite: what is “human scale deployments”?
Tech lawyer Luis Villa returns to Go Time to school us once again on the intellectual property concerns of software creators in this crazy day we live in. This time around, we’re focusing on the implications of Large Language Models, code generation, and crazy stuff like that.
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.
WestArtFactory’s premium PCB cheat sheets, Maxime Topolov tells of a disappearing AWS dev, Juspay Technologies releases HyperSwitch for payment processing, Servo gets new funding for 2023 & Cloudflare’s open source Wildebeest.
Jerod is joined by Yehonathan Sharvit, author of Data-Oriented Programming, to discuss the virtues of treating data as a first-class citizen in our applications and the four principles that make it possible.
KBall and Chris dive into the current JavaScript trends towards smaller frameworks, compiled JavaScript, and why Chris believes “this time is different” with regards to developers caring about network speed and reducing JS sent over the wire.
