Best Use of Entire

Entire is the Git forge for agent-human collaboration. From syncing your sessions and prompts to your Git history, to hosting code and replacing the Pull Request with Trails, Entire are reimagining code hosting and collaboration for the agent era.

Ready to build faster with AI without burning through tokens or losing context? This challenge is all about building smarter AI workflows. To qualify, your project should leverage as many of Entire’s core capabilities (Sessions, Graph, and/or Brain) as possible.

Your project should lean on Sessions for context and memory and entire-graph for codebase mapping:

Sessions (Shared Memory): Save your AI agent sessions as instant checkpoints and push them to your team. Teammates or other agents can jump in instantly and pick up right where you left off with zero context loss. Graph (Codebase Mapping): Generate a visual map of how your codebase fits together. Using entire graph search instead of letting agents blindly search files to cut token usage by up to 71%! Brain (Persistent Reasoning): Combine your session data and Graph insights into persistent project knowledge. Agents can query past decisions and architectural lessons through the CLI or MCP so they don’t repeat mistakes or undo working code. Trails (Code review): Assign you or a teammate’s agent a task via Trail (Entire’s issue/PR combo primitive), the agent works on it, and then let your agent review the code change: does the code change match the intent? Should it merge? Let Entire Trails help you decide! We’re looking for teams that use Entire to create seamless human-AI collaboration, maintain clean code history, and show measurable token efficiency. Build something awesome, keep your agents on track, and show us how Entire powers your workflow!

Claim your code at https://mlh.link/junction-26 and check how to build with Entire at https://mlh.link/entire