Sidhant describes Blitzy's core architecture—agent swarms coordinated via the database rather than a single orchestrator—as the key to scaling autonomous code generation to millions of lines that compile and pass all tests. ✦ AI generated
Sidhant Pardeshi · The TWIML AI Podcast · 2026-03-10 · original ↗
starts at this moment · 0:00
“So, multi-agentic, where does that come in?”
The approach that we took has been to dynamically recruit multiple swarms of agents and use the database as part of the orchestration layer. And you can recruit tens of thousands of agents, but not have to worry about this single orchestrator that's keeping track of everything that's happening.
verbatim transcript · starts at 0:00
0:00The approach that we took has been to dynamically recruit multiple swarms of agents and use the database as part of the orchestration layer. And you can recruit tens of thousands of agents, but not have to worry about this single orchestrator that's keeping track of everything that's happening. We've been able to apply that successfully and we frequently write hundreds of thousands of lines, millions of lines of code.
0:22Everything compiles, everything runs, all tests pass, the UI works, it's pixel perfect. Um and so we perfected that really All right, everyone. Welcome to another [music] episode of the Twilio AI podcast. I am your host Sam Charrington. Today I'm joined by Sidhant Pardeshi. Sidhant is co-founder and CTO of Blitzee. Before we get going, be sure to take a moment to hit that subscribe button wherever you're listening to
0:59today's show. Welcome to the podcast, Sid. Thanks, Sam. Glad to be here. I'm a long-time listener. I've been listening since 2019. That's amazing and it is so great to hear. I am excited to meet you and I'm really looking forward to digging into your experiences at Blitzee where you're working on autonomous development. So let's uh let's dig right in, but start by talking a little bit about your background. You
1:28were at Nvidia before you started Blitzee. Yeah, I was at Nvidia uh since 2016, January 2016. And back then, the day I joined uh Nvidia's stock was worth the 32 billion. That was Nvidia's market cap. 32 billion dollars. And I think Anthropic's revenue today is more than that. It was quite quite >> [laughter] >> experience, you know, being at Nvidia at that time. And um Nvidia was structured
1:59uh I don't know if they still are but it functioned very much like a startup for the entire time that I was there right from 2016 to 2022 and um I you know the when the attention is all you need paper dropped I was right there you know I was inventing things for Nvidia in the generative AI space. I was deep into GANs or generative adversarial networks and various autoencoders