Git for AI agents, not humans first
Entire is a new distributed Git infrastructure that mirrors GitHub repositories across regional cells so AI coding agents can clone, fetch, and push against local copies instead of hammering a single central Git server, promising lower latency, fewer rate limits, and higher reliability for agent-driven development workflows. That is the real story: Git itself has always been distributed, but our dominant hosting model is not. Centralized Git platforms were built for human-sized traffic patterns — a clone in the morning, a pull before lunch, a push at the end of the day. Agent fleets flip that pattern on its head, turning every repository into a high-frequency endpoint. Entire, founded by former GitHub CEO Thomas Dohmke, is the first serious attempt to redesign the network layer around those agents instead of squeezing them into human-era infrastructure.
Why GitHub’s architecture is cracking under agentic load
GitHub’s problem is not Git; it is centralization. Billions of combined agent and developer operations land on the same clusters, and the symptoms are now familiar: rate limits, latency spikes, and outright outages as coding agents explode in use. Agentic coding workflows stress repositories in ways human workflows never did. A single AI coding agent might clone, inspect, checkpoint, and push in tight loops; a swarm of them magnifies that pattern across many branches and experiments. GitHub has admitted that these agentic workflows accelerated sharply and forced it to plan for much higher scale, with recent incidents tied to reliability and cloud-capacity strain. The result is a platform designed as a social coding hub being pressed into service as high-frequency infrastructure. That mismatch opens a window for an agentic coding platform that treats Git hosting more like a distributed database than a social network.
Inside Entire’s distributed Git network for AI coding agents
Entire’s preview is deliberately modest on the surface: you authorize a GitHub app, create a mirror, and point humans or AI coding agents at an entire:// remote in a chosen region. Underneath, that mirror is backed by a Git-compatible repository network with a global control plane for identity and placement and regional data planes for Git object storage. Those regional cells serve clones, fetches, refs, commits, diffs, and other read-heavy paths close to where agents run, offloading the heaviest traffic from the GitHub origin while keeping GitHub as the upstream for mirrored branches. One quotable metric captures their bet: “Entire says its benchmarks have pushed the network to a sustained 570,000 clones an hour, 586 pushes a second, and roughly 470 combined clone-and-push operations a second.” This is Git hosting treated explicitly as a high-throughput Git network for AI agents, not a web app with a Git server tucked inside.
From GitHub helper to GitHub alternative for agents
In its current waitlisted preview, Entire is not a full GitHub alternative for agents. Pushes on ordinary mirrored branches still forward to GitHub, and existing branch protection, checks, and write policies remain in control at the origin. The immediate win is read offload and regional proximity, especially for fleets of Codex, Claude Code, Cursor, GitHub Copilot, and other AI coding agents that can now “build without rate limits” against local mirrors. But the roadmap points somewhere more radical. Entire plans native public and private repositories that do not need GitHub underneath, self-hosted nodes, an open-source Git backend, tamper-evident history, policy-as-code, CI/CD, and broader decentralized operation. At that point, it stops being a band-aid for GitHub strain and starts becoming a true GitHub alternative for agents — a place where the primary user is machine traffic, with humans reviewing the trail of code and agent sessions recorded alongside repository history.
The bigger shift: Git as infrastructure for agentic coding
The most important part of Entire is not any single benchmark; it is the mental shift it forces. Dohmke describes Git “as a database,” and Entire’s network makes that literal by storing not only code but also agent sessions, prompts, tool calls, checkpoints, and redacted transcripts as Git data in dedicated branches. This is what an agentic coding platform looks like: Git hosting that assumes non-stop, parallel, machine-driven change and treats collaboration as inspecting why the code changed, not only what changed. The common theme, shared by other emerging systems, is that AI agents make Git hosting less like occasional human collaboration and more like high-frequency distributed systems infrastructure. With USD 60 million (approx. RM276 million) in seed funding and a reported USD 300 million (approx. RM1.38 billion) valuation, Entire is a well-funded bet that the future of Git is a Git network AI agents call home first, with humans along for the ride.
