Tissue.ai

Devpost · Code

Tissue.AI was built to help new developers overcome one of the biggest barriers to contributing to open-source projects: figuring out where to start. Facing large, unfamiliar codebases can feel daunting, and current LLM agents are still limited in their ability to solve real-world coding problems. By providing context, structured guidance, and step-by-step directions, Tissue.AI empowers newcomers to tackle GitHub issues with confidence. Users simply paste the link to an issue, and the system leverages Letta’s MemGPT technology to analyze the repository, gather relevant information, and present it in an interactive and approachable way. This enables developers—especially beginners—to better understand codebases and use the structured output alongside agentic coding tools like Cursor or Copilot.

Planned features include interactive chat, multi-repository support, and an IDE extension — further lowering the barrier to a first open-source contribution.

Built at UC Berkeley AI Hackathon 2025 alongside three other students in a span of 24 hours.

Tech stack: Nextjs, FastAPI, Python, Gemini, Claude, Letta, MCP