Github competitor Entire is live now – how the agent-first platform works
Now that agents are writing so much code, Entire is trying to reinvent the coding platform itself.
GitHub rival Entire has launched, presenting an agent-first platform to address the evolving demands of coding in the AI era. Founded by former GitHub CEO Thomas Dohmke, Entire leverages a decentralized Git network to handle the surge in AI-powered coding activity that has strained GitHub services. The platform introduces Trails, a novel approach to code review that replaces traditional pull requests with a heads-up display offering customized evaluations scored by agents after each code push.
Unlike the conventional Pull Request model, Trails enable developers to receive real-time feedback similar to an airline pilot's display. All data is accessible not only via Entire's web interface but also through an open-source command-line interface (CLI), allowing coding agents to act on feedback in real-time while developers validate progress. When the evaluations are satisfied, developers can merge the code without scrutinizing every line of code.
Entire's agents are highly customizable, and each trail (a trail of evaluation) provides insight into how the agents are utilizing tokens. By treating the idea, agent trace, and outcome as first-class artifacts for review, Entire empowers developers to merge code confidently without examining every line of the diff.
The platform boasts Git hosting speeds up to 89 times faster than GitHub and six times faster than Cursor origin, thanks to its decentralized network. Developers can create, migrate, and host private repositories across multiple global locations, initially in the US, India, Australia, and the EU.
A key feature of Entire is Continuous Memory, which stores developer session logs alongside the codebase in the repository. Agents can draw from this information to search for answers, potentially reducing token usage by up to 71%. This memory system combines a codebase graph and an "agentic brain" that learns from previous sessions and prompts, preventing agents from repeating errors. Entire is now available for developers to explore.
Written by urgent.news from ZDNet's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
