Agent Swarms and Knowledge Graphs for Autonomous Software Development with Siddhant Pardeshi

**Sam Charrington** (0:01)
A big thanks to Blitzy for supporting the podcast and sponsoring this episode. Want to accelerate software development velocity by 5x? You need Blitzy, which brings autonomous software development to your enterprise codebase. Your engineers declare intent and Blitzy agents map your codebase and generate an agent action plan. Once approved, Blitzy gets to work, autonomously generating hundreds of thousands of lines of validated end-to-end tested code. More than 80% of the work completed in a single run. Blitzy is not just generating code, it's developing software at the speed of compute. Experience Blitzy firsthand at blitzy.com/twiml.
That's blitzy.com/twiml.

**Siddhant Pardeshi** (0:48)
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. We've been able to apply that successfully and we frequently write hundreds of thousands of lines, millions of lines of code, everything compiles, everything runs, all tests pass, the UI works, it's pixel perfect. We've perfected that really.

**Sam Charrington** (1:30)
All right, everyone, welcome to another episode of The TWIML AI Podcast. I am your host, Sam Charrington. Today, I'm joined by Siddhant Pardeshi. Siddhant is co-founder and CTO of Blitzy. Before we get going, be sure to take a moment to hit that subscribe button wherever you're listening to today's show. Welcome to the podcast, Sid.

**Siddhant Pardeshi** (1:49)
Thanks, Sam. Glad to be here. I'm a long-time listener. I've been listening since 2019

**Sam Charrington** (1:54)
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 Blitzy, where you're working on autonomous development. So let's dig right in, but start by talking a little bit about your background. You were at NVIDIA before you started Blitzy?

**Siddhant Pardeshi** (2:19)
Yeah, I was at NVIDIA since 2016, January 2016 And back then, the day I joined NVIDIA's stock was worth $32 billion. That was NVIDIA's market cap, $32 billion. And I think Anthropix's revenue today is more than that. It was quite an experience being at NVIDIA at that time. And NVIDIA was structured, 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 when the attention is all you need, paper dropped, I was right there. I was inventing things for NVIDIA in the generative AI space. I was deep into GANs, or generative adversarial networks and various autoencoders. And I was brushing with NLP. It was still quite earlier. You had BERT, we were using BERT for translation and stuff like that.
But the transformer was ground breaking tech. And eventually when I realized the potential of what it could do, and simultaneously had an opportunity to go to HBS, to do a joint master's program in an MBA and an MS, I chose that. And I met Brian at HBS, my co-founder and CEO, and we decided to form Blitzy based on the idea that AI will catch up eventually with humans. And we made this bet back when the context window was about 10,000 tokens and it could barely write like usable code, right? But we made this bet that AI is going to be as good, if not better, than humans at writing code. And there'll be a section of software development that's not just about code generation, but entire software engineering that will get completely automated by autonomous development. And that's what Blitzy is all about.

**Sam Charrington** (4:12)
It certainly is true that one of the areas where AI is having the most impact today is in software development. When you think about software development, do you have a way that you taxonomize the space and the opportunity?

**Siddhant Pardeshi** (4:29)
So I think software development is the best opportunity and space for to apply AI. And the reason for that is because software is verifiable, it's compilable, it's testable.
You can visualize it and there is the concept of a correct answer. There could be many correct answers, but there are correct answers and wrong answers, which is not always the case in other domains, right? So it's super important to get, you know, to realize that. And then if you think about the space itself, I think we all got started with AI assisted development, right? You had copilots, today you have CLIs and IDEs, ID tools with embedded AI assistance, and they all have the ability to, for example, do tasks asynchronously. Like, for example, you can give it a job that will take even an AI maybe like hours to complete, and it will think for some time, go off asynchronously, ask you follow up questions, and then what not. And then you have another part of the space which is about autonomous development. There are tools in this category. There's, I believe, Devin from Cognition that falls into that category. We operate in that category. And the idea here is that you hit, build, and out comes a PR, right? But the PR that comes out is already tested, validated. Everything works, and it's exactly how you intended it to be, right? There's no errors. The code is acceptable, right? So the biggest challenge that we have on both sides of the spectrum is code acceptance, right? You can write a lot of code, and code is a commodity now. Getting AI to write code is very easy. Getting any code is easy. Getting code that follows your standards, code that is really good, it goes as secure, code that is ready for production, is a completely different story, right? Because you have, on one hand, you have these green field builds, or like new products that you can build from scratch. And AI is really good at that. If you look at the demos that the labs put out, hey, I built this game, and it looks amazing. I can't believe it. But then when you put the same AI on an enterprise code base, and you're supposed to work with the...