Most companies start their AI transformation with technology, not a business problem — and end up stuck in endless pilots instead of real results. In this talk, I’ll share practical principles shaped by building and delivering 20+ AI strategies and 50+ solutions across industries — from retail to pharma — in the US, Europe, and Ukraine. We’ll cover the most expensive mistakes, what actually drives ROI, and why some AI projects scale while others remain just slides. Who is this for: • CEOs, business owners, and leaders who are implementing or planning AI • Tech leads and ML engineers who want their AI solutions to deliver real business impact

As the team grows, products multiply, and the engineering organization evolves - the CTO role often shifts from a technical leader to a manager staring at spreadsheets and dashboards. And that’s when it becomes truly challenging: to stay in the technical loop, remain close to the architecture and systems, and keep a real sense of what’s happening on the ground. In this talk, I’ll share my experience on how to stay a Hands-on CTO - maintaining deep technical understanding, influencing architecture, and scaling the company at the same time, without losing touch with the code and core systems. Key topics we’ll cover: - How the CTO role evolves as the company grows - from coder to system-level leader. - The most common traps: loss of architectural memory, disconnect between business and engineering, dependency on a few key people. - Healthy habits that help keep technical context: code reviews, architecture stand-ups, "walk the code" sessions, CTO R&D sprints. - Decision-making systems: how ADRs and RFCs help maintain clarity and traceability. - Communication with tech leads: building effective 1:1s, technical syncs, and knowledge-sharing loops. - Tools and platforms that preserve context - dashboards, monitoring systems, and architecture reviews.

In his presentation, Vadym will cover: - Goals of the strategy process - Forecasting and goal setting (Foresight, Top-Down + Bottom-Up) - Lean A3: structuring problems and metrics - Strategy implementation and cascading goals - Tracking results (time cycles, OKRs, monitoring, adaptation) - Practical A3 examples