AI Agents vs Managers: How to Build a Team That Attracts Strategic Investment

Who would you give $10 million to: 20 experienced managers, or 1 entrepreneur commanding a swarm of 100 AI agents? This choice is coming sooner than most people expect. At TechWeek, Andrei Kushnarev, Director of the New Digital Products and Solutions Department, broke down why simply adopting neural networks doesn’t speed up product releases on its own — and how teams need to restructure their architecture to attract strategic investment.

The Real Bottleneck: Managerial Attention in the Age of AI Agents

We live in a world of people, not tokens. An LLM can generate brilliant ideas within an hour, but human processes — meetings, approvals, and revisions — still stretch a launch out to weeks. The limiting factor in business is no longer the number of hands on deck, but the number of decisions being made.

AI Agents Answer “How” — Managers Answer “Why”

Algorithms absorb the middle layer of the process: data analysis, content generation, code. But the spark of genuine insight still belongs to humans. Only people can form a vision, find motivation, show empathy, and bring projects to life on the ground.

Speed of Finding PMF: The New Benchmark for Investors Evaluating AI Teams

The laws of the market haven’t changed — Product-Market Fit remains the primary goal. But the focus has shifted to the speed of adaptation. Projects with the right human + AI architecture are the ones that win. The key principle: a person should stay where they create an advantage, and step back where they create delays.

What Strategic Investors Are Looking for in AI-Driven Startups

These are exactly the kinds of projects being selected for the AI Solutions Accelerator. Teams that have found the right balance between human decision-making and AI execution — where managers set direction and agents handle execution — represent the new competitive standard. Building that architecture isn’t just good operations. It’s what makes a startup fundable.