Code Compass is an AI agent that helps engineers determine the best task to work on next, given the codebase context from the engineer’s current task.

- Code Compass indexes a GitHub repo with AST parsing, enabling agents to understand where developers are developing codebase context [1]

- Given a current linear ticket, Code Compass's agent provides context about the relevant codebase locations, implementation patterns, and starting points needed to complete the task and feeds those instructions directly to your coding agent [2]

- Given a current ticket, Code Compass’ agent identifies the next ticket to work on that will maintain as much of the engineer's existing codebase context as possible [3]

Why we built it

As engineers, we often struggled with deciding what to pick up next, especially when deep in a particular section of the codebase. Each context switch slows us down, and a lot of valuable attention can be lost when switching too often between unrelated tasks. Context switching is also expensive for AI models: each switch requires re-ingesting the same files for reindexing, driving up token costs and more importantly wasting time. We built Code Compass to help engineers seamlessly flow from one meaningful task to the next, maintaining momentum and minimizing friction, and to save both humans and models from unnecessary context resets.

Tech implementation details

- Code Compass indexes your entire GitHub repo using AST parsing to capture the code structure and developer context.

- It also syncs with your Linear workspace, mapping tickets to relevant code areas based on historical changes.

- Our agent combines this insight, leveraging up-to-date context to ensure suggestions always build on your current work.

- We utilize modern LLM architectures and lightweight vector databases to enable real-time, context-aware recommendations.

- Use Cursor command tools and manage branches and create PRs with each linear ticket.

Challenges we overcame

Visualizing code graphs proved much trickier than we thought. Representing complex dependencies in a meaningful way for both the AI and human user took multiple iterations. We took inspiration from projects like GitHub Next's repository visualization (https://githubnext.com/projects/repo-visualization/), eventually building a visualization layer that helps users quickly see project hot spots and context flows.

Potential Extensions

- Codebase + Developer understanding - Find who has expertise and triage tickets accordingly.

- Project planning - Architect new projects with developer and codebase understanding

- Expanding integration to include additional issue tracking systems (such as Jira and Trello), further streamlining workflows for a wider range of teams.

- Other languages (currently only supports typescript)

Try it yourself

You can sign up at https://codecompass.sh. We truly welcome your feedback and are eager to see how engineers use it to streamline their workflows.

[1] https://youtu.be/0EJl8b3fWYg

[2] https://youtu.be/hpxFagxHqu0

[3] https://youtu.be/fGLIlh3q1-k

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