Human leadership becomes essential for operating AI agents in businesses
1–2 minutes
The link between people management and AI programming
Daytona CEO Ivan Burazin has found that professionals with prior experience in people management achieve significantly better results when working with artificial intelligence tools. He explains that instructing a digital agent requires a clear definition of expected inputs and outputs, a task that leaders accustomed to managing teams perform more effectively than technicians without leadership experience.
How Daytona puts this idea into practice
At the company’s New York headquarters, each of the 16 engineers manages an average of five digital agents, eliminating the need to write code from scratch. However, engineers without leadership experience struggle when interacting with automated systems, often assuming the machine will understand their intentions without detailed instructions.
Clear communication drives productivity
Burazin stresses that the key skill is aligning expectations before execution begins. Anyone who has led a team knows that creating clear, objective instructions is essential for achieving the desired outcome.
Explicit definition of the expected outcome
Detailed explanation of execution steps
Reduction of ambiguities in instructions
Continuous monitoring of results
We’ve found that people who manage others and understand how to communicate what they want—in terms of inputs versus outputs—are much better at operating agents, said Ivan Burazin.
Implications for organizational structure
This approach allows companies to maintain lean teams without sacrificing project agility. By amplifying each employee’s capabilities through automation, hiring new staff becomes more selective. A study by consulting firm Gartner confirms that clear process alignment is critical for the success of autonomous technologies, reducing rework. As a result, the evolution of AI agents transforms management skills into a key asset for corporate productivity.
