Devplan co-founders Chris Bee, CEO, left, and Anton Safonov, CTO. (Devplan Photo)
Devplan, a Seattle startup trying to automate away the meetings and status reports that eat up a product team’s week, is coming out of stealth Thursday with $2.5 million in seed funding.
The company, founded by two industry veterans with experience at companies such as Uber, Amazon, Snap and Meta, is also expanding availability of its software for coordinating work across product and engineering teams, after testing it quietly with a small group of customers.
Devplan traces its roots to a youth soccer pitch, of all places, where co-founder Anton Safonov coached the daughter of his future business partner, Chris Bee. They had kids at the same school, and discovered they shared a frustration from running engineering teams: too much of the work didn’t have anything to do with building the product.
Bee calls it an invisible tax.
“With AI fundamentally changing the way we do software development, we’ve seen this huge acceleration in coding and in engineering work,” he said in an interview. “But the rest of the coordination work, the rest of that tax — that ‘work about work’ — hasn’t changed very much, frankly.”
They co-founded Devplan in 2025, with Bee as CEO and Safonov CTO.
How it works: Devplan’s core product, Weaver, connects to commonly used tools including GitHub, Jira, Slack and meeting note-takers. A user can query Weaver through a built-in chat function, a Slack bot, or through a direct link into AI coding tools like Claude Code, asking about product status, features, or who’s responsible for which aspects of the project, for example.
Weaver also works in the background, generating a daily digest for each person and tracking projects on its own, flagging risks and progress without anyone filing an update.
The idea is to avoid scheduling a meeting or creating a status report.
Bee said queries run faster and cheaper through Weaver than pointing an AI tool at the raw data each time, because Devplan processes the information in advance and stores it in a knowledge graph rather than scanning code and documents on every request. He said queries run roughly twice as fast and more than three times cheaper on token costs in internal testing.
Funding: The company’s $2.5 million seed round was led by AI2 Incubator, with participation from Acequia Capital, Mighty Capital, Grand Ventures and eLab Ventures.
Based at AI House on Seattle’s Pier 70, Devplan employs six people, with a seventh hire in the works. The seed money is going toward engineering hires and deeper integrations, Bee said.
Founder backgrounds: Bee was previously CTO of Lessen, where he helped grow the property-services company from a $20 million startup to a $2 billion valuation, and earlier led product and engineering teams at Zillow, Uber and Amazon.
Safonov spent seven years as a principal software engineer at Snap, where he was a lead engineer on the company’s infrastructure team, and earlier worked on systems at Meta that handled realtime traffic for Messenger, Facebook and Instagram. He also built systems at LinkedIn.
“Chris and Anton have lived this problem at scale, and they have the technical depth to solve it,” said Yifan Zhang, managing director at AI2 Incubator, in a statement.
Competitive landscape: Devplan’s bet is that a tool built specifically for product and engineering teams will outperform the general-purpose AI assistants.
Glean, the enterprise AI search company, may be the closest comparison, Bee said, but it works more broadly across all of a company’s information while Devplan goes deeper on software development specifically. Devplan integrates with Linear, the project-management tool, making it more of a partner than a rival, he said.
Increasingly, given the capabilities of AI coding assistants, the competition also includes companies deciding to build a coordination tool in-house rather than buy one.
Current status: Devplan has dozens of paying business customers on annual contracts, plus hundreds of users who have tried it so far. Pricing is consumption-based, with companies quoted a flat rate based on team size and expected usage.
What’s next: The company is focusing on enterprise customers for now, with plans to eventually open the product to individuals on a pay-as-you-go basis.
