Software Huddle

Today we have the excellent Kent C. Dodds on the program. Kent is an amazing teacher in the web development space, and I've learned a ton from him about React, JavaScript testing, and general web dev. Lately, Kent has been going all-in on AI, especially with the model context protocol (MCP) space. He's sharing a ton of useful material in this area as he works on a new course. We spent a lot of time going over what MCP is, why it's useful, and why Kent thinks our own personal Jarvis is the next step. We cover a bunch of other topics too, like what it's like putting on a conference (Epic Web Conf) plus how AI has changed the educational space. Check it out! *Timestamps* 01:12 Start 06:52 The pitch for MCP 14:30 Where does MCP architecturally sit? 17:27 Contrasting with REST 23:07 Should I be building these now? 23:47 Are there any frameworks? 26:31 Why Cloudflare 34:10 MCP Spec 35:35 Authentication 38:29 A2A by Google 41:50 What caught Kent's attention? 44:28 What got Kent interested in React? 46:16 Jarvis 47:44 Frontend Development in the long run 51:44 What needs to get better for this to happen? 57:42 How has AI impacted education landscape? 01:04:46 Like the travel? 01:12:35 App Stack 01:13:48 React Server Components Follow Kent: https://twitter.com/kentcdodds Follow Alex: https://twitter.com/alexbdebrie Follow Sean: https://twitter.com/seanfalconer *Software Huddle ⤵︎* X: https://twitter.com/SoftwareHuddle

So if you're writing code or keeping systems running, you probably know the drill. Late night pages, chasing down weird bugs, dealing with alert storms. It's tough! It costs money when things break, and honestly, nobody loves that experience. So the big question is, can we actually use something like AI, AI agents in particular, to make reliability less painful, more systematic? That's what we're talking about today. We have on the show with us Amal Kiran, the CEO and Co-founder of Temperstack. They're building tools aimed at automating SRE tasks, think, automatically finding monitoring gaps, alerts, helping with root cause analysis, even generating Runbooks using AI. So if you wanna hear about applying AI to real world SRE problems and all the tech behind it, we think you're gonna enjoy this.

Today we have Hassan back on the show. Hassan was one of our first guests for Huddle when he was working at Vercel, but since then, he's joined Together AI, one of the hottest companies in the world. They just raised a massive series B round. Hassan joins us to talk about Together AI, inference optimization and building AI applications. We touch on a bunch of topics like customer uses of AI, best practices for building apps, and what's next for Together AI. Timestamps 01:42 Opportunity at Together AI 04:26 Together raised a big round 06:06 Vision Behind Together AI 08:32 Problems in running Open Source Models 11:40 Speed For Inference 14:24 Fine Tuning 19:23 One or Two Models or a Combination of them 21:32 Serverless 22:21 Cold Start issues? 27:46 How much data do you need? 30:00 Balancing Reliability and Cost 34:07 How customers are using Together 42:36 Agent Recipes 47:03 Typical Mistakes buiilding AI apps

Today, we have Sam Lambert back on the show! Sam is the CEO of PlanetScale, and if you follow him on X, you know he’s one of the sharpest voices in the database space—cutting through the hype with deep experience and a no-nonsense approach. In this episode, we dive into PlanetScale’s new Metal offering, which has been battle-tested with PlanetScale’s high-scale cloud business partners and is now GA. Sam also shares why staying profitable is crucial—not just for the business but for the stability and reliability it guarantees for customers. While many cloud infrastructure companies chase the next hype cycle, Sam prefers to keep it boring—delivering rock-solid performance with no surprises Finally, we close with Sam's thoughts on other happenings in the database space -- Aurora DSQL, Aurora Limitless, MySQL benchmarks, and multi-region strong consistency. Tune in for a deep dive into databases, cloud infrastructure, and what it takes to build a sustainable, high-performance tech company. Timestamps 01:34 Start 06:42 PlanetScale Metal 11:15 The problem with separation of storage and compute 15:02 EBS Tax 17:32 How does Vitess handle durability 22:58 Metal recommended for all PlanetScale users? 27:20 The hidden expense of IOPS for cloud databases 37:41 Timeline of creating PlanetScale Metal 41:32 Focus on profitability 47:52 Removal of hobby plan 57:45 Deprecation of PlanetScale Boost 01:00:24 DSQL 01:01:51 Aurora Limitless 01:04:15 AWS as a partner 01:07:00 The spectacle of AWS re:Invent 01:12:22 Benchmarks and benchmarketing 01:15:51 AWS Databases + multi-region strong consistency

Today, we’re joined by Johann Schleier-Smith. Johann co-founded Tagged during the early days of social media, a time when building scalable systems for the web was uncharted territory. Back then, cloud computing didn’t exist—everything ran on on-premises servers or in co-located data centers. We discuss the challenges of scaling Tagged and draw parallels to the current wave of innovation around Generative AI and large language models. Johann shares how building with these technologies feels like a similar uphill climb. We also dive into his new venture, CrystalDBA, and how it’s leveraging AI to optimize databases, making advanced database management accessible to everyone.

Today we have Philip Kiely from Baseten on the show. Baseten is a Series B startup focused on providing infrastructure for AI workloads. We go deep on Inference Optimization. We cover choosing a model, discuss the hype around Compound AI, choosing an Inference Engine, Optimization Techniques like Quantization and Speculative Decoding all the way down to your GPU choice.

Today we have Glauber Costa on the show, who's the CEO and founder at Turso. They provide a managed SQLite service with some really interesting capabilities that's changing some of the application patterns you can do. He shares a lot of really good technical stuff on Twitter. He worked in the kernel, he worked on high-performance databases at ScyllaDB, and now he's working on Turso. He also has a great and interesting podcast, the Save File, which is about developers and religion. Glauber had some great thoughts on the future of databases, including what the future of NoSQL is like and whether we'll see vector databases as a separate category or as a feature of general-purpose databases. We’ve seen arguments both ways, but he was the most effective at changing our mind.

Today we have Tejas Kumar on the show. Tejas is part of the Developer Relations team at Datastax. He's really good at frontend, got a great podcast and he has written a book called Fluent React. He spoke recently at the Shift Conference in Croatia, where he talked about AI engineering and what that means. So we talked about AI Engineering, we talked about React, content creation, education, and much more. This episode is full of value and we think you'd love this one.