Code of Leadership 2. Episode 1 Evaluation of the effectiveness of AI implementation with Avenir Voronov(AI column)

Out. first The second season of my Code of Leadership podcast. This time the guest was Avenir Voronov, Director of implementation from the company veai.ru, which makes AI solutions for corporate development. And we talked about a topic that seems to me one of the most practical in AI-native development: how not just to give engineers an AI tool, but to understand what its implementation really gave the team and business.

In short, the conversation turned around one key question: what measurement language is needed for AI implementation. We discussed why pilots often run enthusiasts without baseline and success criteria, how IDE telemetry and copilot tool dialogs can collect scenarios and evaluate time and money, why look not only at adoption, but also at quality countermetrics, and why engineers’ emotional background and types of interaction with AI also give important signals.

Separately, it was interesting to talk about how the development model itself is changing. AI shifts work up a stack of abstractions: from writing lines to formulating intent, constraints, rules, and tests. This means that not only are tools changing, but roles, processes and the very understanding of what constitutes a successful implementation. I was particularly struck by the idea that successful AI adoption is almost never measured by a single digit. For one customer, ROI is important, for another - the calmness of the team and the quality of work, for the third - the speed of the path from idea to release. So real use and growing adoption are just as important as the beautiful numbers on the dashboard.

In general, this issue is not about the magical growth of productivity, but about a more adult conversation: how to measure AI implementation without marketing noise and not lose touch with the real pain of an engineering organization.

The issue is available at different venues: Youtube, VK, Podster, Ya Music.

#AI #Engineering #Management #DevEx #Productivity #Leadership #Software