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Is Entire’s Agent-Native Platform the Blueprint for Software Development?

Is Entire's Agent-Native Platform the Blueprint for Software Development

Analyst(s): Mitch Ashley
Publication Date: February 12, 2026

Entire emerged from stealth with $60M in seed funding and a vision to rethink software development for the AI agent era. Former GitHub CEO Thomas Dohmke’s platform starts with open-source infrastructure that captures agent context in Git, but its strategic ambition extends further: replacing human-centric developer workflows with systems architected for AI-native software creation. The launch signals that incremental AI assistance won’t scale. Development itself must be rebuilt.

What is Covered in this Article:

  • Entire was launched from stealth with $60M seed funding led by Felicis, founded by former GitHub CEO Thomas Dohmke
  • Entire’s architecture includes a git-compatible database, a semantic reasoning layer for multi-agent coordination, and an AI-native SDLC vision
  • Launch targets fundamental redesign of software development workflows beyond human-centric tooling paradigms
  • The open source Entire CLI introduces Checkpoints open source that versions agent session context (prompts, reasoning, tool usage) directly in Git repositories
  • Platform currently supports Anthropic Claude Code and Google Gemini CLI, with plans for Codex, Cursor CLI, and other agent systems

The News: Entire, founded by former GitHub CEO Thomas Dohmke, announced its public launch alongside a $60 million seed investment led by Felicis, with participation from Madrona, M12 (Microsoft’s venture fund), Basis Set Ventures, and others. Notable individual investors include Olivier Pomel (Datadog CEO), Garry Tan (Y Combinator CEO), and Gergely Orosz (The Pragmatic Engineer).

The company introduced the open source Entire CLI, which enables developers to capture agent session context—including prompts, reasoning chains, and tool usage—directly in Git repositories as versioned Checkpoints. The CLI currently supports Anthropic’s Claude Code and Google Gemini CLI, with planned integration for OpenAI Codex, Cursor CLI, and other agent platforms.

Entire’s platform vision extends beyond context capture to include a git-compatible database, a semantic reasoning layer for multi-agent coordination, and a reimagined software development lifecycle built for AI agents. The company positions this not as incremental tooling improvement but as foundational infrastructure for rethinking how software is created when agents perform the development work.

Entire intends to address a structural mismatch: traditional developer workflows and tools like Git were designed for human-authored code and cannot adequately track, govern, or audit the provenance and intent behind machine-generated outputs.

Is Entire’s Agent-Native Platform the Blueprint for Software Development?

Analyst Take: When constraints in systems shift fundamentally, the dynamics change. When constraints are removed entirely, existing systems evolve or die, and new systems are built around new models, creating disruption and massive opportunities.

Cloud computing eliminated hardware provisioning constraints and spawned AWS, Azure, and the SaaS economy. DevOps removed the wall between development and operations, creating CI/CD platforms, infrastructure-as-code, and modern deployment velocity. Software automation eliminated manual testing bottlenecks, enabling continuous delivery at scale. Entire’s launch signals we are at that inflection point for software development itself.

Entire’s launch signals we are at that inflection point for software development itself.

The Current Developer Model Is Temporary

The current generation of developer tools, including IDEs, Git workflows, pull request reviews, and CI/CD pipelines, was architected for humans writing code. They capture what changed, but not why, how the agent reasoned, or what constraints informed decisions.

This model worked when developers authored every line. It breaks when agents generate tens or hundreds of thousands of lines across parallel sessions, when context lives in ephemeral conversations, and when handoffs between humans and machines require reconstructing intent from scratch.

These tools will not scale gracefully to agent-driven development. They will be replaced by systems designed from the ground up for AI-native workflows. Entire is building a replacement foundation, starting with the structural problem: making agent reasoning and context persistent, versionable, and governable.

Entire’s Offerings: Plumbing for Rethinking Development

What Entire has disclosed and made available are components of plumbing that require a fundamental rethink of software development. Checkpoints versions agent reasoning, not just output. The git-compatible database creates a shared substrate for multi-agent coordination. The semantic reasoning layer positions Entire as an orchestration control plane rather than just a context store.

This infrastructure enables directing, governing, and informing AI agents tackling significantly more complex problems and larger codebases. Without it, agent-driven development remains limited to isolated tasks with heavy human intervention. With it, agents can operate across codebases with persistent context, coordinated workflows, and auditable decision trails.

Case-In-Point: Anthropic’s C Compiler Experience

The practical limitation Entire targets showed up clearly in Anthropic’s recent work creating a C compiler using Claude agent teams. As covered in Truth or Dare: What Can Claude Agent Teams And Developers Create Today?, the amount of human direction and intervention required was substantial. Agents generated code, but humans orchestrated workflow, debugged failures, and provided context at every handoff.

The bottleneck was not agent capability. The bottleneck was contextual infrastructure: no shared context layer, no persistent reasoning trace, no semantic coordination across agent sessions. Entire’s platform is designed to remove that constraint by making agent context a first-class artifact in the development lifecycle. This is not an incremental improvement. These is the early steps of rethinking the development substrate to operate at the level of agent reasoning rather than human keystrokes.

Competitive Positioning: Open Infrastructure vs. Disconnected Silos

Entire enters a fragmented ecosystem where GitHub, Cursor, Anthropic, and OpenAI each control pieces of the agent development stack but lack a unified context layer. GitHub’s Copilot integrates AI assistance but remains human-centric. Cursor’s Composer orchestrates agents but keeps context ephemeral. Anthropic and OpenAI build powerful agents, but do not persist session reasoning outside their platforms.

Dohmke’s entrepreneurial pedigree, a $60M seed round, and a coalition of strategic investors signal credible backing for this vision of rethinking development workflows from first principles. Entire’s open source, agent-agnostic approach positions it as a connective infrastructure across these silos. If developers adopt Checkpoints broadly, Entire becomes an early de facto standard for agent context management, analogous to Git’s role in the last platform shift.

The execution risk: convincing developers to adopt new tooling before the pain of agent provenance gaps becomes unbearable. The opportunity: establishing platform authority in the AI-native SDLC before incumbents lock down proprietary alternatives.

What to Watch:

  • Adoption velocity of Entire CLI and Checkpoints among teams using Claude Code, Gemini CLI, Cursor, and other agentic coding platforms
  • Emergence of multi-agent coordination patterns and governance models built on Entire’s semantic reasoning infrastructure
  • Community contributions and ecosystem development around the open source Entire CLI, signaling broader developer acceptance of agent-native workflows
  • Integration depth with enterprise DevOps pipelines, governance frameworks, and compliance tooling for regulated industries
  • Competitive responses from GitHub, Anthropic, OpenAI, and Cursor to Entire’s agent context management layer

See the “Hello Entire World” blog post by Thomas Dohmke on the Entire website and Entire’s GitHub repository for more information.

Disclosure: Futurum is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.

Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of Futurum as a whole.

Other insights from Futurum:

Google Adds Deeper Context and Control for Agentic Developer Workflows

Truth or Dare: What Can Claude Agent Teams And Developers Create Today?

OpenAI Frontier: Close the Enterprise AI Opportunity Gap—or Widen It?

Agent-Driven Development – Two Paths, One Future

AI Reaches 97% of Software Development Organizations

Author Information

Mitch Ashley

Mitch Ashley is VP and Practice Lead of Software Lifecycle Engineering for The Futurum Group. Mitch has over 30+ years of experience as an entrepreneur, industry analyst, product development, and IT leader, with expertise in software engineering, cybersecurity, DevOps, DevSecOps, cloud, and AI. As an entrepreneur, CTO, CIO, and head of engineering, Mitch led the creation of award-winning cybersecurity products utilized in the private and public sectors, including the U.S. Department of Defense and all military branches. Mitch also led managed PKI services for broadband, Wi-Fi, IoT, energy management and 5G industries, product certification test labs, an online SaaS (93m transactions annually), and the development of video-on-demand and Internet cable services, and a national broadband network.

Mitch shares his experiences as an analyst, keynote and conference speaker, panelist, host, moderator, and expert interviewer discussing CIO/CTO leadership, product and software development, DevOps, DevSecOps, containerization, container orchestration, AI/ML/GenAI, platform engineering, SRE, and cybersecurity. He publishes his research on futurumgroup.com and TechstrongResearch.com/resources. He hosts multiple award-winning video and podcast series, including DevOps Unbound, CISO Talk, and Techstrong Gang.

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