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What happens when AI changes more than coding speed?
Chris Merrick, Co Founder and CTO at Omni, explains how his engineering team is adapting around AI, autonomy, product ownership, and a lighter operating model.
Omni has about 25 engineers working in groups as small as one to three people. Engineers are expected to make product decisions, move without waiting for detailed specifications, and show unfinished work during a weekly company demo day.
Those demos are also posted publicly. Customers watch them, join betas, and see features often move into production soon after.
Chris also shares how Claude Code changed development across the team. Commits to main increased roughly two to three times without comparable team growth, but the added output created another constraint: code review.
Takeaways
• Small teams can operate with less process when engineers have real ownership.
• Public demos create feedback loops between engineers, customers, and the rest of the company.
• AI can increase engineering output while moving the bottleneck somewhere else.
• Token costs still matter when AI usage scales across products and engineering teams.
Key Moments
01:15 Building AI into the engineering workflow
03:38 Why Omni works in teams of one to three engineers
06:48 The weekly demo day that replaces heavier process
10:29 Why Omni publishes unfinished product demos publicly
17:14 Measuring AI engineering productivity through commits to main
19:52 When token economics start affecting engineering decisions
One Line That Stuck
“I’m not married to the process. I’m married to the outcomes.”
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