Today we have Dr. Ewelina Kurtys on the show. Ewelina has a background in Neuroscience and is currently working at FinalSpark.

FinalSpark is using live Neurons for computations instead of traditional electric CPUs. The advantage is that live Neurons are significantly more energy efficient than traditional computing, and given all the energy concerns right now with regards to running AI workloads and data centers, this seems quite relevant, even though bioprocessors are still very much in the research phase. 

Today we're talking with one of our favorite engineers, Rafal Wilinski. Rafal has been on the cutting edge of AI development in the last few years as he has led AI teams at Zapier and Vendr.

If you’ve ever felt like engineering teams are stuck in execution mode—heads down, building what they’re told—then today’s episode is for you. We're talking about what it really takes to build high ownership engineering cultures where devs aren't simply just shipping code, but they're helping shape the product.

And our guest this week is Matt Watson. He's a long time founder, engineer, and now the CEO of Full Scale, a company that helps startups and scale ups, grow their engineering teams with top talent from the Philippines. Matt's also the author of a book called Product Driven that shows how engineers can build with more clarity, purpose, customer focus and we get into some of the details in that book during this podcast.

So in this episode, we get into everything from the downsides of specialization to the importance of empathy, to why code shipped isn't the same as value delivered. We hope you enjoy it.

Today's episode is with Aayush Shah. Aayush is one of the co-founders of Blacksmith, which is a CI compute platform. Basically, Blacksmith will run your GitHub Actions jobs faster and with more visibility with the standard GitHub Actions CI runners.

The founding team has a fun background doing systems work at Cockroach and Faire, and they're taking on a big problem in running this massive CI fleet.

The explosion in AI agents has really changed the CI world. CI is more useful than ever, as you want to be sure the changes from your agents aren't breaking your existing functionality. At the same time, there's a huge increase in demand and spikiness of CI workloads as developers can fire off multiple agents to work in parallel, each needing to run the CI suite before merging. Aayush talked about how they're handling this load and facilitating visibility into test failures.

We also covered cloud economics. Aayush said the traditional cloud-based storage options don't work for them -- EBS and locally attached SSDs are too expensive for their workloads where they don't need the standard durability guarantees. He walks us through building their own fleet outside the hyperscalers and the plans going forward, along with some of the economics of multi-tenancy that Blacksmith has previously written about.

Today, we're talking Valkey, Redis, and all things caching. Our guest is Madelyn Olson, who is a principal engineer at AWS working on Elasticache and is one of the most well-known people in the caching community. She was a core maintainer of Redis prior to the fork and was one of the creators of Valkey, an open-source fork of Redis.

Today, Sam Lambert from Planetscale is back for a third time. Planetscale just announced Planetscale Postgres, so we had to get Sam back to tell us how and why they decided to add support for Postgres. It's always great to have Sam on -- he brings great stories about real customers and honest insight about the state of the database industry.

Big time guest today as Arvid Kahl joins us. Arvid is my favorite type of guest -- a deeply technical founder that can talk about both the technical and business challenges of a startup. Lots to enjoy from this episode.

Arvid is known as the Bootstrapped Founder and has documented his path to selling Feedback Panda back in 2019. He's now building Podscan and sharing his journey as he goes.

Podscan is a fascinating project. It's making the content of *every* podcast episode around the world fully searchable. He currently has 3.5 million episodes transcribed and adds another 30,000 - 50,000 episodes every day.

This involves a ton of technical challenges, including how to get the best transcription results from the latest LLMs, whether you should use APIs from public providers or run your own LLMs, and how to efficiently provide full-text search across terabytes of transcription data. Arvid shares the lessons he's learned and the various strategies he's tried over the years.

But there are also unique business challenges. For most technical businesses, your infrastructure costs grow in line with your customers. More customers == more data == more servers. With Podscan, Arvid has to index the entire podcast ecosystem regardless of his customers. This means a lot of upfront investment as he looks to grow his customer base. Arvid tells us how he's optimized his infrastructure to account for this unique challenge.

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.

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

Today's guest is AJ Stuyvenberg, a Staff Engineer at Datadog working on their Serverless observability project. He had a great article recently about how they rewrote their AWS Lambda extension in Rust. It's a really interesting look at a big, hard project, from thinking about when it's a good idea to do a rewrite to talking about their focus on performance and reliability above all else and what he thinks about the Rust ecosystem.

Beyond that, AJ is just a learning machine, so I got his thoughts on all kinds of software development topics, from underrated AWS services and our favorite databases to the AWS Free Tier and the annoyances of a new AWS account.

Finally, AJ dishes out some career advice for curious, ambitious developers.

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.