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

In this episode, Sid Pardeshi, co-founder and CTO of Blitzy, joins us to discuss building autonomous development systems able to deliver production-ready software at enterprise scale. Sid contrasts AI-assisted coding with end-to-end autonomy, arguing that “code is a commodity” and acceptance is the real metric—security, standards, tests, and maintainability included. We explore Blitzy’s hybrid graph-plus-vector approach, which grounds agents and combines semantic signals with keyword search to navigate large repositories efficiently. Sid breaks down context and agent engineering, how effective context windows have plateaued, and why dynamic agent personas, tool selection, and model-specific prompting matter at scale. He details their orchestration of large swarms of AI agents to collaboratively analyze codebases, plan tasks, and execute complex tasks in parallel. We also dig into why Agents.md and flat memories break down, storing feedback in the knowledge graph, and building real-world evals beyond leaderboards to choose the right model for each task.