Daytona co-founder and CEO Ivan Burazin says employees who know how to manage people are often better equipped to manage AI agents. As companies hand more coding and product-development work to autonomous tools, the ability to assign tasks, review results and shape collaboration is becoming an operational issue for startups seeking to improve productivity without expanding their organizations too quickly.
Daytona currently has about 30 employees across the United States and Europe. Over the past several months, the company has encouraged staff to increase their use of AI agents. Its 16 engineers now run an average of five agents each, and the team no longer writes code entirely by hand.
Daytona engineers run several AI agents at once
Burazin says employees who have previously managed other people tend to give AI agents clearer instructions. They are generally more comfortable separating the required inputs from the expected outputs, defining the result they want and explaining how the work should be completed.
Engineers with strong technical skills but no experience managing people may continue to approach the work as individual contributors. They can assume that colleagues—and AI agents—will infer requirements that have not been stated explicitly. When the result falls short, they may feel frustrated without breaking the assignment down further into its objective, process and delivery standards.
In Burazin’s view, instructing an AI agent is still a management task. The user must set out the goal, constraints and expected deliverable rather than issuing a broad request and leaving the details implicit.
Burazin does not advocate relying only on traditional managers
Burazin does not regard management experience as a substitute for technical expertise. Managers without sufficient technical knowledge, whether in marketing or engineering, may struggle to provide practical support to their teams. Employees still need to participate in the underlying work rather than simply assign tasks and monitor progress.
Burazin founded Daytona in 2023 with Vedran Jukić and Goran Draganić. The company provides secure sandbox infrastructure that businesses can use to run AI agents and AI-generated code in isolated environments. Daytona recently completed a $48 million Series B funding round.
AI agents are reshaping technology-company structures
Burazin’s view comes as technology companies reconsider the role of management. Meta, Amazon and Google have previously reduced layers of middle management to streamline their organizations and improve efficiency. As AI tools move deeper into software-development workflows, more technology executives are also taking part in coding and product development alongside employee management.
For Daytona, allowing one engineer to operate several AI agents helps the company maintain a relatively small human workforce. Burazin says hiring is moving “very slowly” because each additional employee creates new communication links and adds management complexity.
He argues that AI agents can allow companies to complete more work with smaller teams. Fewer employees can shorten communication chains, helping businesses limit organizational complexity while maintaining execution speed.
Daytona’s approach suggests that the effect of AI agents extends beyond reducing repetitive coding. The tools are also changing the management skills expected of employees. For businesses, the ability to state objectives clearly, divide work into manageable tasks and assess the final output may determine whether AI software produces measurable gains in day-to-day operations.