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Designing AI-First Systems for Customer Access
Former GitHub CEO Thomas Dohmeke has raised $60 million at a $300 million valuation for his startup Entire, an open-source tool aimed at helping developers manage code written by AI agents.
The funding is reportedly the largest-ever seed round for a dev tool startup, according to lead backer Felicis. Other investors included Madrona, M12, Basis Set, 20VC, Cherry Ventures, Picus Capital and Global Founders Capital, along with other international investors like founder and CEO of Ping Labs Theo Browne and former CEO of Yahoo! Jerry Yang.
Table of Contents
What Is Entire?
We still rely on a software development lifecycle built before the era of the cloud, inherently designed for human-to-human collaboration, Dohmeke wrote.
"The truth is: the entire software ecosystem is being bottlenecked by a manual system of production that was never designed for the era of AI in the first place. A system that cannot be retrofitted for what's ahead."
That's the purpose of his new company, said Dohmeke. "To build the world's next developer platform where agents and humans can collaborate, learn and ship together." The platform will be open, scalable and independent for every developer, no matter the agent or model used.
Entire is based on three components:
- A git-compatible database that unifies code, intent, constraints and reasoning in a single version-controlled system
- A universal semantic reasoning layer that enables multi-agent coordination through the context graph
- An AI-native software development lifecycle to reinvent the software development lifecycle for agent-to-human collaboration
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Entire's First Product Release: Checkpoints
The decisions, constraints and iteration that produce code within AI tools disappears the moment you close the season, noted Dohmeke. Entire's first ship, Checkpoints, is designed to make that missing context durable.
"Checkpoints are a new primitive that automatically captures agent context as first-class, versioned data in Git," Dohmeke explained. "When you commit code generated by an agent, Checkpoints capture the full session alongside the commit: the transcript, prompts, files touched, token usage, tool calls and more. This context becomes the foundational write-path of our semantic reasoning layer. You can browse checkpoints by branch, drill into individual sessions and trace how your codebase evolved through human-and-agent collaboration commit by commit."
Checkpoints run as a Git-aware CLI. On every commit generated by an agent, it writes a structured checkpoint object and associates it with the commit SHA. The code stays the same, said Dohmeke — the tool just adds context as first-class metadata.
Checkpoints are useful for:
- Traceability: Inspect the reasoning behind any agent-generated change.
- Faster Reviews: Review intent and constraints, not just diffs.
- Better Handoffs: Resume work without replayinig prompts or sessions.
- Less Token Waste: Agents stop repeating mistakes that you corrected in past sessions.
- Multi-Session and Agent Support: Support for concurring agentic sessions.
Related Article: Why Agent UX Is the New Frontier of Governance
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A Universal Semantic Reasoning Layer
Checkpoints is Entire's first move toward building a universal semantic reasoning layer for agents, according to Dohmeke.
"Today, it gives you traceability and history. Tomorrow, it will become the shared memory that allows agents to coordinate, hand off context and build together without collision or loss of understanding."
Additionally, Dohmeke added that they're releasing the Entire CLI open source project, claiming it should be portable, independent and available for every single agent or model. "And because we know, we are better with contributions of the interconnected community of open-source developers."