IT Arena 2026 tech conference in Lviv

IT Arena 2026

How Valuable Is Your Product If It Can Be Vibe-Coded?

IT Arena 2026 tech conference in Lviv
~ 3 хв

From September 25–27, the ConnectiveOne and Evergreen teams attended IT Arena. Sergii Kravtsov, CEO of ConnectiveOne and Evergreen, also spoke at the meetup “How Valuable Is Your Product If It Can Be Vibe-Coded?”

What Was New This Year

Once again, IT Arena brought Ukraine’s tech community together in one place: product builders, developers, business leaders, and startup founders.

Just a year or two ago, AI was still treated as a separate topic at events like this. In 2026, it is everywhere. One of the ideas discussed on stage was the Agentic State — a model in which AI agents support government institutions in their day-to-day operations.

It is a good indication of where Ukraine’s tech industry is heading. We continue to build products for global markets and digital services for the country. Things that used to take months can now be prototyped in weeks.

That means the advantage no longer belongs simply to the team that can code faster. It belongs to those who understand the difference between a quickly built prototype and a production-ready system that actually works at scale.

Sergii Kravtsov’s Meetup

Sergii Kravtsov, CEO and co-founder of Evergreen and ConnectiveOne, explored this topic during his IT Arena meetup: “How Valuable Is Your Product If It Can Be Vibe-Coded?”

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It all starts with something we increasingly hear from clients:

“With AI, our own team can vibe-code a similar system in a couple of weeks. In two or three months, we can migrate to it and save a huge amount on licensing fees.”

Time-to-feature has collapsed. Time-to-proof has not.

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Today, you can build a feature incredibly fast. Proving that what you have built is truly equivalent to a production system that a company can rely on for customer interactions is a very different challenge.

We are among the early teams building our own product alongside AI. That gave Sergii a practical foundation for breaking down what AI agents can genuinely replicate — and what they still cannot.

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