The Challenge
Coding agents like Claude, Codex, and Gemini are powerful but limited by sequential processing and lack of proper development tooling. Developers waste time waiting for single requests to complete and struggle with integrating AI assistance into real development workflows.
My Approach
I built on top of existing open-source coding agents, creating background agents for Claude Code, Codex, and Gemini CLI. The key insight was using VMs with GitHub integration to parallelize requests and provide proper development environments for AI agents.
The Solution
Prism Engineer spins up virtual machines for any coding query, running isolated instances of coding agents in parallel. Users can fire off multiple Claude Code requests simultaneously while maintaining proper version control through GitHub integration. The focus was on tooling—enabling the intelligence of coding agents with the infrastructure needed to push code fast and reliably.
Impact & Results
Developers could now parallelize their AI coding assistance, dramatically reducing wait times and increasing productivity. The VM approach ensured code quality and proper testing environments while the GitHub integration maintained workflow continuity.
Key Learnings
The bottleneck in AI-assisted development isn't intelligence—it's tooling and infrastructure. Parallel processing of coding requests unlocks entirely new development workflows. Proper isolation and version control are essential when scaling AI code generation.
Product Demo