Yandex's head of developer relations: AI in code is an exoskeleton, not an autopilot

Sergey Berezhnoy, director of developer relations at Yandex and an expert for ITMO's online master's program "Frontend, Backend Development and AI Solutions" in partnership with Yandex Practicum, has published a column on Habr about why creativity and the ability to think have become a developer's key skills in the era of generated code.

Why AI is an exoskeleton, not an autopilot

The column's central thesis: AI in development should be seen as an exoskeleton that amplifies human capabilities, not as an autopilot that can replace human decisions. An exoskeleton requires the person to keep choosing the direction and judging the result. The model only speeds up and eases execution; it does not relieve the developer of responsibility for architectural and product decisions.

Why a developer who uses AI is already a team lead

Berezhnoy makes another argument: a developer who uses AI in development is already effectively playing the role of a team lead. Working with a code-generating model takes the same skills as managing a team: you set the task, check the result, find errors in someone else's work (even if it is generated), and decide what to keep and what to rewrite. The author stresses that this is exactly why creativity and critical thinking become more important, not less, as the model takes over routine code writing.

• Author: Sergey Berezhnoy, director of developer relations at Yandex
• Expert for ITMO and Yandex Practicum's online master's program "Frontend, Backend Development and AI Solutions"
• Key thesis: AI in development is an exoskeleton, not an autopilot
• Using AI in code effectively turns the developer into a team lead for the model

What this changes in the developer's profession

If a developer's value used to be measured mainly by the speed and care of writing code, then as code-generating models spread, other qualities come to the fore: the ability to phrase a task so the model understands it correctly, the ability to quickly judge the quality of a generated solution, and the willingness to take responsibility for the final result, even if the code was not written by a human hand.

What this means

As code generation becomes a routine task for AI models, the developer's role shifts from executor to task-setter and quality controller. In effect, that is a team lead's role, even if formally no one reports to them.