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The AI coding revolution has found its next major player as Thomas Dohmke, former GitHub CEO, announces the launch of Entire, a startup that has already secured $60 million in seed funding at a $300 million valuation. The venture represents a significant bet on a future where artificial intelligence agents handle the majority of software development tasks.
Dohmke's departure from Microsoft-owned GitHub in August, citing entrepreneurial ambitions, now makes strategic sense. His new company addresses what he sees as a fundamental mismatch between current development tools and the emerging reality of AI-dominated coding workflows. "Entire is a new platform for developers in this era where agents write most of the code," Dohmke explained to Axios.
The funding round demonstrates strong investor confidence in this vision. Felicis led the investment, with participation from established firms including Madrona, Microsoft's M12, and Basis Set. The individual investor list reads like a who's who of tech leadership, including developer advocate Gergely Orosz, former Yahoo CEO Jerry Yang, and Y Combinator's Garry Tan. This combination of institutional and individual backing provides both capital and industry credibility.
Entire's inaugural product, Checkpoints, tackles a critical challenge in AI-assisted development. The tool captures and preserves the context behind AI-written code, including the original prompts, reasoning processes, and decision-making logic used by AI agents. This addresses a growing problem as AI-generated code becomes more prevalent but often lacks the contextual understanding that human developers traditionally maintain.
The company's strategic positioning is notably collaborative rather than competitive. While the AI coding market has become increasingly crowded with startups building their own models and agents alongside tech giants like OpenAI, Anthropic, Google, and Microsoft, Entire takes a different approach. "We are not training models or building agents, we are integrating with them," Dohmke stated.
This integration strategy extends to working with existing popular tools. Dohmke specifically mentioned compatibility with Claude Code, Cursor, and Codex, positioning Entire as a platform that enhances rather than replaces current developer workflows. "Our platform will be open-source, independent, and scalable for every developer and agent to host their code and agent context," he explained.
The open-source approach could prove strategically advantageous. By avoiding direct competition with established AI coding tools and instead providing infrastructure that benefits all players, Entire positions itself as a neutral platform that could become essential to the ecosystem.
Dohmke's vision extends well beyond current development practices. He predicts a fundamental shift where developers will no longer review code line-by-line, as AI agents will produce far more code than humans can effectively oversee. "Soon, developers won't look at the code anymore, as agents will write way more than humans can review," he told Axios.
This prediction implies a complete reimagining of software development workflows. Traditional practices assume human oversight and control at every stage, but Dohmke argues for "an agent assembly line for software development" that operates with minimal human intervention while maintaining quality and context.
The market timing appears strategic. Automated coding has emerged as one of generative AI's most successful applications, with tools like GitHub Copilot, Claude Code, and Cursor gaining significant developer adoption. However, as these tools become more sophisticated and autonomous, the need for better management and context preservation systems becomes more apparent.
Entire's success will largely depend on whether the industry evolves as Dohmke predicts. If AI agents do indeed become the primary code authors, infrastructure for managing, contextualizing, and coordinating their work will become essential. Dohmke's GitHub experience provides valuable insight into developer needs and workflows, potentially giving Entire an advantage in building tools that developers will actually adopt.
The startup enters a competitive landscape but with a differentiated approach. Rather than building another AI coding assistant, Entire focuses on the infrastructure needed to support an AI-first development environment. This positioning could prove prescient if the industry continues its rapid evolution toward agent-driven development.
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$60 million
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Note: This analysis was compiled by AI Power Rankings based on publicly available information. Metrics and insights are extracted to provide quantitative context for tracking AI tool developments.