Software Huddle

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 Søren from Prisma on the show. Prisma has been the most popular ORM in the TypeScript world for a while, and now they're moving more into hosted infrastructure. We spend a lot of time talking about their new offering called Prisma Postgres, which is this unikernel-based Postgres offering. It's a really unique offering from both a technical and a product perspective. On the technical side, they're doing some interesting work compared to other Postgres providers. They're running on bare metal in a colocation facility rather than the default public clouds like AWS, GCP, and Azure. Further, they're using unikernels in a Firecracker VM, giving them unique startup and security characteristics. These technical decisions give them unique economics compared to standard providers, so they're able to have a generous free tier and a unique billing model that works great for serverless applications with spiky workloads. Around all of this, it's very interesting to see a company with such a unique spread of products — a popular, mature open-source library paired with a mission-critical infrastructure service offering. We talked about the difficulties in building a company that accommodates these two very different products. Timestamps 01:51 Start 06:08 Prisma Postgres 09:10 Accelerate 11:39 Why Postgres 17:32 How Prisma Postgres Works 21:32 Colocation Facility 22:05 Unikernels 27:56 CoLo vs Public Cloud 29:11 Building the team 31:46 Missing Features that are being worked on 32:31 Use Cases 33:37 Colo Locations 34:53 Cloudflare 35:42 Biggest surprises since release 37:34 More Unikernel adoption? 39:08 Supporting Prisma ORM 46:43 Mongo 47:51 Life as A CEO 53:04 MCP 57:23 Søren Questions Alex Software Huddle ⤵︎ X: https://twitter.com/SoftwareHuddle Substack: https://softwarehuddle.substack.com

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 on the show, we talked with Yujian Tang. He was on the show previously when he worked at Zilliz, when we talked about vector databases and RAG. He's since branched out on his own, building the tech startup scene in Seattle and organizing AI events all over the place. We talk about his latest venture, the Seattle Startup Summit, coming up on March 28th. They're still Early Bird Tickets available if you're interested. We also talk about AI models, the impact AI is having on programming, including our own programming projects and share our takes on some of the recent acquisitions that have happened in tech, including Voyage AI.

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

Redis is consistently one of the most beloved pieces of infrastructure for developers. And in the last few years, we've seen a number of new Redis-compatible projects that aim to improve on the core of Redis in some way. One of those projects is DragonflyDB, a multi-threaded version of Redis that allows for significantly higher throughput on a single instance. Roman Gershman is the co-founder and CTO at Dragonfly, and he has a fascinating background. Roman initially worked at Google and then was a frustrated user of Redis while working as an engineer at a fast-growing startup. He did a stint on the ElastiCache team at AWS but struck off on his own to make a new, faster version of Redis. In this episode, we talk through the improvements that Dragonfly makes to Redis and why it matters to high-scale users. We go through the different needs and requirements of high-scale cache applications and what Roman learned at AWS. We also go through the Redis licensing drama and how to attract developer attention in 2025.

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 David Cramer on the show. David is one of the co-founders of Sentry, an application monitoring tool that's one of the most widely-adopted tools for developers. Sentry does over 300,000 events per second on average, and there's a lot of fancy work to process these application errors, from rate limiting to fingerprinting to counting to source map unminifying. We walk through some of the architectural changes and systems design work here, including some of David's thoughts on shipping. David and Sentry also have a unique approach to developer marketing. They do some cool things -- sponsoring and then buying the amazing SyntaxFM podcast, sending $100k of free gifts to developers, and launching the Open Source Pledge with $500k donated to open source developers.

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 on the show, we have Kevin Dubois. Kevin is a Senior Principal Developer Advocate at Red Hat, Java Champion, and well known open source contributor. In our conversation with Kevin, we talk about his history with Java and the evolution of the language and where it now fits within the world of AI. Kevin's been building AI applications with Java using Quarkus andLangChain4j. Kevin's a java expert. He's not an AI expert. It's amazing to see how much he's building with AI even without having that background. We also talk a lot about the mindset shift you need to successfully build with generative AI models.

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 Mike Buckbee on the show. Mike is the co-founder of Wafris, and he wrote a really insightful article last week about moving from Redis to SQLite for an aspect of their architecture. The article was nuanced in describing why it worked for their specific needs, and it has some surprising takeaways, including that SQLite was 3x faster than a local Redis instance for their workload. Mike has built a few different WAF (Web Application Firewall) products, so we covered that area as well. He's seen a lot here, so we walked through all the nefarious traffic patterns and the speed in which these bots adapt to new vulnerabilities. Finally, Mike has a wide-ranging skillset that includes marketing. Developers are notoriously tricky to market to, so we talked about his experience in effective marketing to developers without being disingenuous. Links Blog Post: https://wafris.org/blog/rearchitecting-for-sqlite For A Good Strftime: www.foragoodstrftime.com IP Lookup: wafris.org/ip-lookup Timestamps 01:11 Start 03:41 Wafris 07:22 Redis and SQLite 19:09 Flatfile 21:50 Knowatoa 28:22 Web Application Firewalls 46:21 Jumpstart Pro 48:11 Marketing to Developers

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.

Today on the show, we have Peter Hanssens, the CEO and founder of Cloud Shuttle and creator of the DataEngBytes Conference. Peter has helped build an incredible data engineering community in Australia. He runs meetups, user groups, luncheons, and entire conferences. And he's also super knowledgeable. He's been working in the data space for a long time. We picked his brain about the history of data tooling, trends he's seeing in the industry and the relationship between data engineers and other types of engineering. Even if you aren't in the data world, we think you will enjoy the conversation.

Today we have a special guest. We have Jeremy Daly, who's been in the cloud space for a while. Jeremy is the co-founder of Ampt, which is building an abstraction infrastructure layer on top of AWS, just to make it simpler to sift through all the different options and develop on AWS and do best practices there. So we wanted to get his opinions on a lot of different infrastructure stuff that he's seeing and how AI is changing development. We even talk about some front end stuff at the end and HTMX and whether it's real, whether it's a troll. So lots of good stuff in this episode. Timestamps 01:56 Start 04:28 Jeremy's Background 07:26 Hard things about building ampt 11:59 Infrastructure from Code 17:07 App Runner 20:10 Comparing ampt and PaaS 27:22 Managing a lot of AWS accounts 30:46 Better than AWS 35:27 Thoughts on AWS deprecating services 47:11 Using AI 57:20 ChatGPT Adoption - Non Programmers 01:06:19 AI affecting the job market 01:18:37 HTMX Software Huddle ⤵︎ X: https://twitter.com/SoftwareHuddle Substack: https://softwarehuddle.substack.com/

Today we have Stephen Chin, VP of developer relations at Neo4j on the show. Stephen is an author, speaker, and Java expert, we'll actually be crossing paths in person at the upcoming Infobip Shift conference in September. We got together to talk about GraphRAG. His CTO recently wrote an article titled The GraphRAG Manifesto, and Stephen joined us to explain how a knowledge graph can be used to improve performance over traditional RAG architectures. It also helps address some of the fundamental limitations to LLM adoption from enterprises today, like hallucinations and explainability. GraphRAG is relatively new, but looks like a very promising approach to improving performance for certain generative AI use cases, like customer support.

Today's episode is with database educator, PHP enthusiast, and all-around good guy Aaron Francis. Aaron is one of the best out there at delivering high-quality educational content. Somehow, he's managed to have three different video courses sell over $100k in wildly different fields -- a college corporate accounting class aide, video screencasting, and high-performance SQLite. In this episode, we talked about a lot of things, including: - Why (and when!) to use SQLite - What courses he's looking at next - How to stay sharp when doing educational content - His origin story as a programmer - Getting kids to be high agency - How PHP became classy. Links https://www.epicweb.dev/why-you-should-probably-be-using-sqlite https://highperformancesqlite.com/ Timestamps Intro 01:41 Why SQLite 03:31 When to use SQLite 09:14 SQLite Creators 14:20 Holy smokes 17:29 jsonb Indexing? 22:07 SQLite Course 23:54 Vendor Specific Courses? 26:17 Postgres Course Timing 30:26 Nights and Weekends 30:46 Getting into Databases 35:38 Going back to Programming 39:22 In 20 years 40:48 Kids 42:08 Making money is a skill? 47:52 Balancing Video Creation and Programming 50:43 Sustainable Business 54:23 Doing SaaS 56:13 Working for someone else 57:38 Secret Sauce for Video Content 58:34 PHP 01:05:56 Taylor and Laravel 01:13:31 Vue 01:18:39 Warp-up 01:20:41

Today, we have Dax Raad on the show. Dax is a must-follow on tech Twitter, known for his blend of humor and insightful tech opinions. We talked a lot about SST, which is the infrastructure as code tool that he works on. They've got a new engine called Ion that's releasing. So we talked about what that looks like and how that's going to help users. We picked his brain on questions like, "Which cloud providers do you trust?" "Which services do you rely on?" and touched on topics like frontend development, databases, and more. We also talked about marketing to developers, he's got a unique take on that. So a lot of interesting stuff here.

Today, we have Manny Silva, Head of Docs at Skyflow, on the show to talk about two open source projects he created, Docs as Tests and Doc Detective. Docs as Tests is a framework to make sure that your docs are in sync with your product. It's essentially a way to test your docs just like engineers test their code, and Doc Detective is Manny's implementation of that framework. We discuss the history and motivation behind the projects, what they enable, and how people are using it today. Timestamps 01:57 Intro 06:51 Testing Documentation 09:26 Competing Against 11:26 Docs as Tests & Doc Detective 13:32 How does one apply these ideas? 16:49 How does test writing work? 19:26 Out of the box checks 23:15 Configurations Structure to create tests 24:28 Integration with the normal flow 28:20 Freshness 29:13 Tools used to build it 32:02 Open Source 33:27 Limitations 35:31 MongoDB's version of Docs as tests 36:42 Innovation Engine by Azure 37:27 Teams using Doc Detective 38:12 At Skyflow 40:52 Future 41:41 How to get started 45:18 Rapid Fire Links Docs as Tests: https://www.docsastests.com/ Doc Detective: https://doc-detective.com/

This week on the show, we talk with Bill Tarr, Principal Solutions Architect at AWS SaaS Factory. He's a super thoughtful guy, expert in SaaS architecture and architectural patterns. We talk about tenancy, infrastructure decisions, SaaS gotchas, security, permissioning, and even dip into technical challenges of building Gen AI into SaaS. Timestamps 00:01:29 Background 00:07:26 Common Challenges 00:11:46 Infrastructure Choices 00:14:29 Missteps 00:18:57 Control Plane & Application Plane 00:25:52 Permissioning in a Multi-tenant setup 00:32:54 Gen AI & SaaS 00:35:07 Amazon Bedrock 00:49:27 Quickfire questions 01:01:17 Security In SaaS

In this episode, Kyle Galbraith tells us about his company, Depot.dev, which is a way to make Docker builds and GitHub action runners complete much faster with basically no changes to your build step. Depot is growing like crazy and just surpassed *one million* builds per month. We looked at how he found the idea for Depot and some of the technology underlying the service. Kyle also shares a ton of wisdom about building a company and specifically a developer tools company. This includes his experience in YC (including how hard he worked on his YC application) and the importance of having "model companies" that are a few steps ahead of you in the process. We talk about how the funding market has change and how he thinks about hiring, fundraising, and profitability. His advice on company building and the focus on what's important is super helpful to those in a similar position.

Database performance is likely the biggest factor in whether your application is slow or not, and yet too many developers don't take the time to properly understand how their database works. In today's episode, we have Andrew Atkinson who just released a new book, High Performance PostgreSQL for Rails. Andrew is one of those "Accidental DBAs" that fell into learning about database optimization at his job and ended up getting pretty dang good at it. In this episode, We hit Andrew with a bunch of questions about using Postgres properly, including how tight to your schema should be, how to handle Postgres operations, and how to think about performance testing with Postgres. We also got into some aspects about the process of writing a book and what he recommends for others. If you're building an application with a relational database, this book will help you. It has real code repositories so you can walk through the steps yourself, and it teaches the concepts in addition to the practical aspects so you understand what's happening.

ParadeDB is Postgres for search and analytics. As Postgres continues to rise in popularity, the "Just Use Postgres'' movement is getting stronger and stronger. Yet there are still things that standard Postgres doesn't do well, and advanced search and analytics functionality is near the top of the list. The ParadeDB team provides a pair of Postgres extensions. The first, pg_search, brings a more performant and full-featured search experience to Postgres. It uses Tantivy (think: Lucene but Rust) as the search engine and provides advanced ranking and querying functionality. The second, pg_lakehouse, allows you to perform large analytical queries over object store data. Together, these provide compelling new features wrapped in a familiar operational package. Philippe Noël is one of the founders of ParadeDB. In this episode, we talk about why these extensions were needed, why the 'Just Use Postgres' movement exists, and where ParadeDB fits in your architecture. Follow Philippe: https://x.com/philippemnoel Follow Alex: https://x.com/alexbdebrie Follow Sean: https://x.com/seanfalconer Check Out ParadeDB: https://www.paradedb.com/ Timestamps 01:50:18 Intro 04:30:23 Where does seach on Postgres fall down? 05:33:09 BM25 and TF-IDF 07:23:03 Postgres Tipping Point 10:05:08 Tantivy 11:50:14 Tantivy vs Lucene 13:07:06 vs ZomboDB 15:35:21 Just Use Postgres for Everything? 17:57:17 Developing a Postgres Extension 19:26:03 Arvid's Problem 20:27:08 Postgres and Log Data 23:28:01 Separate OLTP and Search Instances 28:32:01 Search Nodes vs OLTP Nodes 30:02:12 ParadeDB Analytics 35:27:05 Hosted Service 39:03:15 Stumbling upon the Idea 39:51:22 Community 41:01:15 Getting Started with ParadeDB

Today we have Mark Huang on the show. Mark has previously held roles in Data Science and ML at companies like Box and Splunk and is now the co-founder and chief architect of Gradient, an enterprise AI platform to build and deploy autonomous assistants. In our chat, we get into some of the stuff he's seeing around autonomous AI agents and why people are so excited about that space. Mark and his team has also recently been working on a project to extend the Llama-3 context window. They were able to extend the model from 8K tokens all the way to 1 million through a technique called theta-scaling. He walks us through the details of this project and how longer context windows will impact the types of use cases we can serve with LLMs. Follow Mark: https://x.com/markatgradient Follow Sean: https://x.com/seanfalconer

Today we have Bob van Luijt, the CEO and founder of Weaviate on the show. Bob talks about building AI native applications and what that means, the role a vector database will play in the future of AI applications, and how Weaviate works under the hood. We also get into why a specialized vector database is needed versus using vectors as a feature within conventional databases. Bob van Luijt: https://www.linkedin.com/in/bobvanluijt/ Sean on X: https://x.com/seanfalconer Software Huddle ⤵︎ X: https://twitter.com/SoftwareHuddle Substack: https://softwarehuddle.substack.com/

Today, we have Talia Nassi on the show. Talia's been leading Developer Advocacy at Akamai. Akamai is in a really interesting space where they've been around for a long time, as a CDN provider, as a security provider, and now they acquired Linode, and acquired a bunch of other companies which has expanded them into more of like a full fledged cloud provider. We had a really interesting discussion talking about the expansion, we also talked about her thoughts on infrastructure as code, multi cloud, and just getting into DevRel and what that experience has been like for her.

Today we have Brian Rinaldi from LaunchDarkly on the show. This is the final episode of our in person coverage at the SHIFT Conference in Miami. And although Brian works at LaunchDarkly, we actually didn't talk at all about his employer and instead chatted about Jamstack. Brian has a long history with Jamstack, has written a lot about it. Jamstack was popularized and created by Netlify. And there's been a lot of history of controversy with the term. Some people think of it's merely a branding ploy or a marketing thing, and others find it simply confusing because we have terms like LAMP stack, MEAN stack and MERN stack. So Jamstack automatically gets lumped in with those, but it's not actually a technology stack. It's an architectural pattern. Recently, Jamstack has been giving away to what is known as composable frontends and we picked Brian's brain on this and what this means not only for Jamstack, but also the future web development.

Today we have Emanuel Lacić on the  show. He was in academia for a while. Now he's been working at Infobip for the last couple of years, building some of this AI stuff and putting it into production. We picked his brain about the best practices when it comes to AI and what we can expect to see over the next couple of years.

Today, on the show we have Christine Spang, Co-founder and CTO of Nylas. Christine was the keynote at the recent Shift Developer Conference in Miami, and we caught up with her there. Nylas is a unified API for email, calendar, and contacts. We talked to Christine about why she started Nylas, and the challenges with building an API for email. Email is this massive distributed system with a very diverse set of implementations, it's a super gnarly ecosystem going back decades. It's generally not something you want to spend a lot of time on if you don't have to. Christine was a lot of fun to have on the show. Follow Christine: https://twitter.com/spang Follow Sean: https://twitter.com/seanfalconer Follow Alex: https://twitter.com/alexbdebrie Nylas: https://www.nylas.com/ Software Huddle ⤵︎ X: https://twitter.com/SoftwareHuddle Substack: https://softwarehuddle.substack.com

Today's guest is Ivan Burazin, the co-founder and CEO of Daytona, an actual creator of the Shift Developer Conference that he sold some time ago to Infobip. Ivan has tons of experience building developer tools, he has been working on dev environments for over a decade. In this interview, we talk about another company he founded called CodeAnywhere that eventually led to the founding of Daytona. Daytona is a dev environment management platform. It sits between your IDE and the cloud, taking care of standardizing your dev environments, regardless of whether you're building on your desktop or deploying to production. They're taking the best of what leading technology companies like Google, Uber, and Meta have built internally and bringing that to the rest of the world. Software Huddle ⤵︎ X: https://twitter.com/SoftwareHuddle Substack: https://softwarehuddle.substack.com/

Today's episode is with Nikhil Benesch, who's the co-founder and CTO at Materialize, an Operational Data Warehouse. Materialize gets you the best of both worlds, combining the capabilities of your data warehouse with the immediacy of streaming. This fusion allows businesses to operate with data in real-time. We discussed the data infrastructure stuff of it, how they built it, how they think about billing, how they think about cloud primitives and what they wish they had.

Today's episode is with Khawaja Shams. Khawaja is the CEO and co-founder of Momento, which is a Serverless Cache.  He used to lead the DynamoDB team at AWS and now he's doing Memento. We talk about a lot of different things, including multi-tenancy and cellular architecture and what it's like to build on AWS and sell infrastructure products to end customers and just a lot of other really good stuff. We hope you enjoy this episode. 01:12 Introduction 03:38 multi-tenancy 08:13 S3 and Tigris 15:09 Aurora 19:11 Momento 31:21 Cellular Architecture 41:16 Most people are doing cross-AZ wrong 52:23 Elasticsearch 01:03:08 Rapid Fire

In today's episode with Tim McNamara, we talk all about Rust. Tim is one of the leading educators in the whole Rust educational space. He wrote the Rust in Action book, which is probably the best Rust book out there. He has a YouTube channel, he taught and did a lot of educational work on Rust at Amazon AWS. We talked about object ownership and object lifetimes and just all these interesting things that Rust has and why is this language loved by so many and why it's continuing to grow. He also gets into what it's like being an independent educator, creator, and some of the difficulties with that, how to get started, and how he deals with doubt.

Today, we have Kent C Dodds on the show. If you don't know Kent, he's a well known expert in JavaScript, Web Development and Teaching. His courses like Testing JavaScript, Epic React, and Epic Web Dev have helped countless developers uplevel their skills and develop whole new ones. During our conversation, we discussed how he got to start in creating courses in the background on his latest project, Epic Web Dev. We also picked his brain about JavaScript. Why the heck do we have so many JavaScript frameworks? Are we just perpetually dissatisfied with what we have? Or is there a fundamental problem with how the web is actually designed? There's a lot of meat in the bone on this one, and we hope you enjoy it. Show Notes: The Web's Next Transition https://www.epicweb.dev/the-webs-next-transition Epic Web Conference 2024 CONFERENCE DAY April 11th, 2024 WORKSHOP DAY April 10th, 2024 https://www.epicweb.dev/conf Timestamps 01:46 Kent's Background 05:38 Epic Web Dev 15:07 Creating an engaging course 19:07 How long does it take to finish the course 23:01 JavaScript and CS 25:47 Things that you should know 29:09 JS frameworks 36:28 Re-building the Web from Scratch? 42:59 PESPA Architecture 53:04 Rapid Fire

Welcome back to an episode where we're talking Vectors, Vector Databases, and AI with Linpeng Tang, CTO and co-founder of MyScale. MyScale is a super interesting technology. They're combining the best of OLAP databases with Vector Search. The project started back in 2019 where they forked ClickHouse and then adapted it to support Vector Storage, Indexing, and Search. The really unique and cool thing is you get the familiarity and usability of SQL with the power of being able to compare the similarity between unstructured data. We think this has really fascinating use cases for analytics well beyond what we're seeing with other vector database technology that's mostly restricted to building RAG models for LLMs. Also, because it's built on ClickHouse, MyScale is massively scalable, which is an area that many of the dedicated vector databases actually struggle with. We cover a lot about how vector databases work, why they decided to build off of ClickHouse, and how they plan to open source the database. Timestamps 02:29 Introduction 06:22 Value of a Vector Database 12:40 Forking ClickHouse 18:53 Transforming Clickhouse into a SQL vector database 32:08 Data modeling 32:56 What data can be Vectorized 38:37 Indexing 43:35 Achieving Scale 46:35 Bottlenecks 48:41 MyScale vs other dedicated Vector Databases 51:38 Going Open Source 56:04 Closing thoughts

Today's guest is Yujian Tang from Zilliz, one of the big players in the vector database market. This is the first episode in a series of episodes we're doing on vectors and vector databases. We start with the basics, what is a vector? What are vector embeddings? How does vector search work? And why the heck do I even need a vector database? RAG models for customizing LLMs is where vector databases are getting a lot of their use. On the surface, it seems pretty simple, but in reality, there's a lot of tinkering that goes into taking RAG to production. Yujian explains some of the tripwires that you might run into and how to think through those problems. We think you're going to really enjoy this episode. Timestamps 02:08 Introduction 03:16 What is a Vector? 07:01 How does Vector Search work? 14:08 Why need a Vector database? 15:11 Use Cases 17:37 What is RAG? 20:34 RAG vs fine-tuning 29:51 Measuring Performance 32:32 Is RAG here to stay? 35:43 Milvus 37:17 History of Milvus 47:44 Rapid Fire X https://twitter.com/yujian_tang https://twitter.com/seanfalconer

Today's episode is with Tyler Wells. Tyler is the CTO and co-founder at Propel. He was an early employee at Skype (and Microsoft after the acquisition) as well as Twilio. While at Twilio, Tyler helped build a data platform to power customer-facing analytics for a major Twilio feature. Propel is the productized version of that for other teams looking to build similar experiences. In this episode, we see how this real-time, flexible analytics problem is tricky for a lot of teams, as well as how Propel is helping to solve the problem. We also cover some of Alex's favorite hobby horses for infrastructure developers -- what it's like building infrastructure services, how to think about billing, how S3 is becoming ubiquitous, and what to do about cross-AZ network costs. Timestamps 02:29 Introduction 08:05 What is Propel? 22:28 ClickHouse 29:15 Target Customers 30:28 Billing Model 35:10 S3 becoming a key part? 36:47 Cross AZ Network Costs 41:56 Current Support 51:39 Access Policies 55:39 Rapid Fire 01:03:16 AI replacing Software Engineers? Show Notes Data Chaos Podcast https://www.propeldata.com/

Today, we have Philipp Krenn on the show. He's the head of DevRel for Elastic, and we took a deep dive on all the Elasticsearch stuff like Indexes, Mappings, Shards and Replicas and how to think about performance and all that stuff. We also discussed the Use Cases and applications where Elastic is not suitable to use. This episode is packed with fundamentals and we think you'd love it. Timestamps 02:00 Introduction 04:13 What is Elasticsearch 05:33 Use Cases 11:25 Where not to use Elasticsearch 13:51 Index 16:44 Shards 23:29 Routing 33:57 Replicas 41:08 Bottlenecks 01:02:30 Upgrading an Elasticsearch Cluster 01:06:12 Rapid Fire

Zig is a new programming language with big ambitions: to be a better C. Loris Cro is the VP of Community at the Zig Software Foundation, and he takes us through the ins and outs of Zig -- how was it created, what problems is it trying to solve, and where is it being used. We heard Joran Dirk Greef rave about Zig during our TigerBeetle episode, and there are a lot of passionate Zig fans out there. Zig has some really unique aspects, particularly the comptime keyword that allows for running arbitrary code at compile time. We also talk about Loris's background and his rapid rise to lead marketing for a software foundation. Loris talks about how he got there, how Zig things about community, and how they're working to make Zig sustainable.

Today, we have Joe Reis on the show. Joe is the co author of the book, Fundamentals of Data Engineering, probably the best and most comprehensive book on data engineering you could think to read. We talk about the culture of Data Engineering, Relationship with Data Science, the downside of chasing bleeding edge technology in approaches to Data Modeling. Joe's got lots to say, lots of opinions and is super knowledgeable. So even if Data Engineering, Data Science isn't your thing. We think you're still going to really enjoy listening to the interview.

Our special episode is back! Join Sean, Alex & Vino in this fun conversation. 00:00 Introduction 10:08 Sora by OpenAi 16:11 Google Gemini 1.5 22:05 Mixture-of-Experts 38:02 Nvidia's Valuation 40:19 Apple Vision Pro 49:05 Tech Layoffs

Today's episode is with Craig Kerstiens, Craig has been in the Postgres space for a long time. First at Heroku, doing Heroku Postgres. Then at Citus, doing Distributed Postgres. Now at Crunchy Data, he's Chief Product Officer there. He's done a lot of Postgres advocacy and a lot of interesting stuff. In this episode we'll talk about the Postgres ecosystem, some of the Postgres features, some of the naysayers about Postgres, and just get Craig's thoughts on those.

Today on the show, we have the founder and CEO of Akita Software and now head of product at Postman, Dr. Professor Jean Yang. Jean has a super interesting background, a former computer science professor at Carnegie Mellon University with a focus on programming language research. She then went on to found Akita Software, which was focused on solving hard problems around the API observability space. And last year, the company was acquired by Postman. And during the interview, we covered a lot of ground talking about Jean's academic experience, motivations for starting a company, and the problem Akita set out to work on. 01:05 Intro 06:40 Software as a Social Problem 12:10 Over engineering 20:44 Motivation 25:22 The problems 32:10 Existing methods to solve 36:21 Some other similar systems 36:21 Packet to Reconstruction 39:43 Aha moments for customers 41:33 Why sell to Postman 47:23 Would you do it again? 52:03 Rapid Fire

Today's guest is a legend in the distributed systems community. Stephan Ewan was one of the creators of Apache Flink, a stream processing engine that took off with the rise of Apache Kafka. Stephan is now working on core transactional problems by building a durable async/await system that integrates with any programming language. It's designed to help with a number of difficult problems in transactional processing, including idempotency, dual writes, distributed locks, and even simple retries and cancellation. In this episode, we get into the details of how Restate works and what it does. We cover core use cases and how people are solving these problems today. Then, we dive into the core of the Restate engine to learn why they're building on a log-based system. Finally, we cover lessons learned from Stephan's time with Flink and what's next for Restate.

Today's guest is Bain Capital partner Rak Garg. Rak is a super smart guy that's worked as an ML researcher. Then he was in product at Atlassian before moving over to the venture capital side of the world. In this episode, we talk about BCV Labs, an AI incubator and community for AI founders that Rak helped establish. Rak shares his thoughts on the big opportunities he sees in AI and how it's going to impact the world, both in the short and long term, and how BCV Labs is helping support AI founders bring these visions to reality. There's a huge amount of opportunity to automate away a lot of manual tasks across industries like legal, insurance, and healthcare. But of course, there's a lot of complexity with actually bringing this technology to market.

In this episode, We spoke with the founders of WarpStream Labs, Richard Artoul and Ryan Worl. WarpStream is a fascinating rethink of Kafka -- how could you simplify and improve the Kafka design by slightly tweaking your constraints? The result is very compelling -- a Kafka-compatible API that bypasses local disk by writing everything directly to S3. For the tradeoff of a slightly higher end-to-end latency, you can get a Kafka cluster that's much cheaper and way easier to operate. Richie and Ryan have been working on high-scale data systems for years and were the engineers behind Husky, Datadog's custom-built database for logs and metrics. In this episode, they walk us through their experience building WarpStream. They touch on all the hard parts of building your own system (including why it's gotten easier!), as well as some of the difficult problems they had to solve for full compatibility with existing Kafka client libraries. They also touch on using FoundationDB, their thoughts on S3 Express One Zone, and whether AWS's cross-AZ network costs are a scam. Lots of interesting thoughts here from a really sharp team.

Today, we have Cassidy Williams, CTO of Contenda. Contenda unbelievably started as a sticker distribution platform that pivoted into a product that converts podcasts and videos into various other forms of written content via AI. But in our conversation with Cassidy today, we talk about their latest pivot to a product called Brainstory, which is an AI based brainstorming application. We talked through some of their product choices around focusing on speech as the main input mechanism, some of the technical challenges they've had to overcome, how they're using multiple AI models in the backend to make all this magic happen, and where they're seeing initial product traction. If you're a founder or thinking of starting a company, we think you'll find this conversation super interesting. Check Out Brainstory: https://www.brainstory.ai/ Software Huddle: https://twitter.com/SoftwareHuddle Cassidy: https://twitter.com/cassidoo Sean: https://twitter.com/seanfalconer

In this special end of the year clips episode of Software Huddle, we took some time to highlight some of our favorite clips from our interviews since we launched the show back in August. Software Huddle: https://twitter.com/SoftwareHuddle Alex: https://twitter.com/alexbdebrie Sean: https://twitter.com/seanfalconer

On today's show, we have quite the lineup. We have Rizel Scarlett, Leandro Margulis and Katherine Miller all joining Sean to talk about AI for developers. This came together because the four of them had participated on a conference panel earlier this year discussing the topic. We discuss our impressions of AI for developers, what impact it may or may not have, privacy and security, ethics concerns, what the future might look like, and a whole lot more. Today's guests have a diverse set of roles spanning product, marketing, and developer relations, so we think we were able to bring a lot of different perspectives to the topic. Timestamps: 02:25 Introduction 05:45 Will AI's net impact be positive? 11:10 Customer support chatbots 17:18 Speed of Innovation 26:15 Safeguarding Sensitive Data 28:47 Creating your own Models 31:55 Using LLMs responsibly 41:27 Everything GPT 45:08 Existential Risk 51:17 Psychological Safety Links: https://www.youtube.com/watch?v=Wh02qPQasfk

In this episode, we spoke with Vino Duraisamy, Developer advocate at Snowflake. Vino has been working as a data and AI engineer for her entire career across companies like Apple, Treeverse, and now Snowflake. And in this episode, we dive into her thoughts on what's happening in AI right now and what a practical LLM strategy for a company should look like. We discussed the hard, unsolved problems in the space like privacy, hallucinations, transparency, testing, and bias. There's a lot of problems. We're very much in the Wild West days of AI, and it still takes a ton of work to move beyond prototype to production with any AI application. There's lots of hype, but not necessarily that many enterprises actually launching products that take advantage of these generative AI systems yet. We thought Vino had a lot of real world perspective to share, and we think you're going to enjoy the conversation. Follow Vino: https://twitter.com/vinodhini_sd Follow Sean: https://twitter.com/seanfalconer

Today we have the former CEO of Snowflake, a 23 year veteran of Microsoft, Bob Muglia on the show. In this interview, we discuss Bob's book, Datapreneurs, which takes you on a journey about the people behind the first relational databases in the 1970s and early 80s, to Bob's experience launching Microsoft SQL Server and a ton of other products, developing the Data Cloud at Snowflake, and to the future of data and AI. We cover a lot of ground, including some of his experience working alongside the likes of Bill Gates and Steve Ballmer. Timestamps: 02:24 Introduction 04:53 Relational Databases 18:43 Speed of Innovations 24:30 Keeping the Early Stage Culture 31:04 Most successful leaders are difficult to deal with 34:31 Setting up Cloud Data Center at home 36:25 Joining Snowflake as the CEO 38:54 AWS made Snowflake happen 42:18 Google, AWS Missing the Snowflake Opportunity 46:13 Impact On Jobs 50:48 Existential Risk 52:28 Staying Optimistic Links: The Datapreneurs: The Promise of AI and the Creators Building Our Future https://www.thedatapreneurs.com/ Follow Bob: https://twitter.com/Bob_Muglia Follow Sean: https://twitter.com/seanfalconer Software Huddle ⤵︎ X: https://twitter.com/SoftwareHuddle LinkedIn: https://www.linkedin.com/company/softwarehuddle/ Substack: https://softwarehuddle.substack.com/