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Former GitHub CEO Thomas Dohmke launches Entire, an agent-native Git platform

Entire, a startup founded by former GitHub CEO Thomas Dohmke, has launched a Git-compatible development platform designed specifically for AI agent-human collaboration.

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Source-provided image accompanying Former GitHub CEO Thomas Dohmke launches Entire, an agent-native Git platform
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itpro.com
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Linked source — primary-source status has not been established.
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Key terms

Memory (Agent Memory)
Stored context an AI agent uses across steps or sessions to improve continuity.
AI Agent
A software system that can observe, reason, and take actions to achieve a goal, often using tools and memory.
Feature
An input variable used by a model to make predictions.
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What happened

Entire has launched a new Git-compatible development platform designed to replace traditional Git forges like GitHub by prioritizing workflows. The platform introduces a distributed source control architecture where each developer operates on a dedicated server, which the company claims results in push speeds significantly faster than GitHub and Cursor’s Origin. Key features include 'Trails,' a heads-up display for code reviews that replaces traditional pull requests with automated agent-led evaluations, and 'continuous memory,' which allows agents to store and query previous sessions and prompts via a codebase graph.

Entire, founded by former GitHub CEO Thomas Dohmke, has officially launched its Git-compatible platform. The system is built on a distributed source control architecture, providing each developer with a dedicated server. The company claims this infrastructure enables push speeds up to 89 times faster than GitHub and six times faster than Cursor’s Origin.

The platform replaces the standard pull request model with 'Trails,' a described as a heads-up display for code reviews. This system uses multiple AI agents to perform rolling, customized evaluations on code pushes. Once these automated evals are satisfied, the platform allows for code merging without requiring manual human review of the underlying code.

To support agentic workflows, Entire utilizes 'continuous memory,' which stores previous agent sessions and prompts. This is powered by a codebase graph designed to help agents retrieve information faster while reducing token consumption. The startup has also secured partnerships with Buildkite and Depot to allow users to migrate existing CI/CD workflows from GitHub Actions.

Entire previously raised $60 million in a seed round at a $300 million valuation, led by Felic with participation from Madrona, M12, 20VC, and Cherry Ventures.

Source details: itpro.com

Why it matters

As AI agents increasingly handle the bulk of software development, traditional platforms built around human-centric pull requests are facing friction. Entire’s architecture attempts to treat agent traces and session outcomes as first-class artifacts, potentially reducing the manual oversight required for code reviews. By integrating automated evaluation loops, the platform aims to allow developers to merge code based on agent-verified progress rather than manual inspection. This shift reflects a broader industry trend toward 'agent-native' infrastructure, where the platform is optimized for machine-to-machine interaction rather than just human-to-human collaboration.

The shift toward agent-native development platforms addresses the reality that AI agents are now responsible for a significant portion of code generation. According to the source, JetBrains data indicates that 90% of developers use AI coding agents weekly, with 68% using them daily.

By treating agent traces and session outcomes as first-class artifacts, Entire aims to streamline the development lifecycle. This approach moves away from the traditional 'diff and patch' model, which was designed for human-to-human collaboration, toward a model that accommodates the speed and complexity of AI-generated code.

The platform's focus on automated evaluation loops is intended to increase developer confidence in merging code, potentially reducing the bottleneck of manual code reviews in high-velocity environments.

Interactive Mechanism

Interactive Mechanism: How It Actually Works

Explore the underlying technology behind this development interactively.

Agent Lifecycle Stage:
1
User Intent & Planning: "Audit customer refund request #4092 and settle payment."
2
Tool Calling: Emits structured JSON call crm_get_transaction(id='4092').
3
Guardrail & Verification:Paused: High-value action requires human operator sign-off.
4
Final Settlement: Refund recorded, email receipt dispatched, and audit log stored.
Core takeaway: An AI agent is not just a language model—it is a closed loop of planning, tool invocation, and environment feedback. Production systems require self-healing retries and strict human approval guardrails.
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What to watch next

The platform's ability to successfully migrate users from established ecosystems like GitHub Actions remains a significant hurdle. While Entire has partnered with Buildkite and Depot to facilitate workflow transitions, the long-term adoption will depend on whether its 'agent-native' primitives provide enough efficiency gains to justify moving away from the deeply entrenched GitHub ecosystem. Additionally, the competitive landscape is intensifying, with other startups like Cursor also building agent-focused alternatives, making the market for developer tools increasingly crowded.

The primary challenge for Entire is market penetration against established incumbents like GitHub. The company must prove that its 'fundamentally new primitives' offer a tangible productivity advantage that outweighs the cost and friction of migrating existing repositories and workflows.

The competitive landscape is evolving rapidly, with Cursor's Origin also targeting the same 'agent-native' market. The success of these platforms will likely depend on their ability to build robust ecosystems and maintain compatibility with existing developer tools.

Pricing and specific access conditions for the platform were not disclosed in the announcement. Potential users should monitor for updates regarding enterprise-tier features and public availability.

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