Entire, the developer platform founded by former GitHub chief executive Thomas Dohmke, has appointed Karthik Rameshkumar as its field chief technology officer, marking the company’s first formal leadership appointment focused on India.
Rameshkumar will be responsible for carrying developer and enterprise feedback from the region back into Entire’s product and engineering teams.
Entire came out of stealth in February with a $60 million seed round led by Felicis, with participation from Madrona, Basis Set and M12, Microsoft’s venture arm. The company described it as the largest seed raise for a developer tools startup, valuing it at $300 million.
Dohmke left GitHub in August 2025, after four years as chief executive and a decade at Microsoft, to build Entire.
The company’s aim is to build a developer platform designed for an era in which AI agents, rather than only humans, produce numerous codes.
Its architecture rests on three layers—a Git-compatible database meant to unify code, intent, and reasoning; a semantic reasoning layer intended to enable multiple agents to coordinate; and a user interface built around agent-to-human collaboration.
Its first released product, an open-source command-line tool called Checkpoints, records the prompts and reasoning behind AI-generated commits alongside the code itself. It currently supports third-party coding tools.
Being remote-first, the company has nearly tripled its headcount to 40 since their launch.
Rameshkumar joins Entire after leading GitHub’s field engineering effort in Asia Pacific, where he served as Field CTO, APAC, directing solutions engineers and cloud solutions architects across the region.
Before GitHub, he built Twilio’s global support delivery centre for cloud-based communications in Bengaluru. He also worked at DigitalOcean and led customer experience at Hevo Data.
His role at Entire, Rameshkumar says, is to bridge developers, enterprise customers and the company’s engineering teams, feeding product feedback directly into the company’s roadmap.
India Is More Than a GTM Market
The early-India bet hinges on the size and growth of the country’s developer base and its weight in open source, rather than a later-stage GTM decision that many startups make.
“India has always been a very exciting developer market,” he tells AIM. Rameshkumar says Entire is on a spree to find the best developers in the world, and the company believes India is the ideal destination. “We [India] have an amazing talent pool that’s second to none.”
According to GitHub, India is now the second-largest developer market, only behind the United States. The country has 27 million developers on the platform and is projected to become GitHub's largest developer community by 2030.
Entire’s India push also places it among a growing cohort of AI startups, including OpenAI, Anthropic, ElevenLabs and Wispr, that have recently expanded their leadership, hiring or go-to-market presence in the country, reflecting India’s growing importance as both a developer ecosystem and enterprise AI market
Building for the AI Agent Era
Entire’s strategy also explains why Rameshkumar and several others left an established platform like GitHub to build something new. They believe the next generation of developer infrastructure cannot simply be layered onto tools built for human-first software development.
Unlike a synchronous assistant that only responds to prompts, an agent can work asynchronously on tasks assigned by a user. That, he argued, makes agents a fundamentally different category, not just a more advanced assistant.
Rameshkumar also argues that version control, issue trackers and pull requests were built around how humans record and hand off work to one another. This breaks down once AI agents start doing large parts of that work themselves.
“With agents being treated as equal citizens in the software teams, infrastructure has to be built with agents at the center of the experience,” he says.
For example, Checkpoints is designed to preserve provenance in an AI-first development workflow, allowing teams to trace how code was created.
On the future roadmap, he says, Entire will provide a unified way to access all the features required throughout their development lifecycle rather than reaching for a new tool at every stage.
Lessons From GitHub
Working with developers at Github, Dohmke and Rameshkumar have seen AI-assisted coding evolve from an emerging technology into daily workflows, giving them an edge over many newer AI coding startups.
Several members of the Entire team, including Rameshkumar, continue to contribute to open-source projects. The company runs an active Discord where the team responds directly to developer feedback instead of through support.
The proximity to developers also underpins how Entire treats the line between consumer tooling and enterprise software, which Rameshkumar sees as largely artificial.
“The developer who turns up to a community meetup on a Saturday evening is the same person who shows up to an enterprise event the following Tuesday, carrying the same feedback into both rooms,” says Rameshkumar.
Rather than separating consumer and enterprise efforts, Entire builds for developers once, then adds governance, analytics, and controls so organisations can scale deployments without sacrificing developer appeal.
The company joins a new class of AI-native software engineering startups, such as Poolside, Factory, and Magic, that are rebuilding the software development stack around AI agents rather than traditional developer workflows.
It will now need to win over developers who have built their preferred toolset and habits to integrate Entire’s products into their stack, a challenging task.
Developers, Rameshkumar says, are creatures of habit, a pattern observed throughout his career across cloud infrastructure, CPaaS, and AI-assisted coding. Moving them from a trusted workflow is harder than building new technology.
Developers now more readily embrace tools that expand their capabilities and act quickly through feedback, issues, or pull requests.
He points to Entire’s own CLI tool as evidence, noting that it has drawn over 4,600 stars on GitHub and an active base of outside contributors within five months. He read that as a sign that developers will cross the habit barrier once a tool visibly solves a problem they already have, rather than being asked to adopt something on faith.
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