Over 15 years in software development and IT strategy, I’ve seen one thing: companies dive headfirst into technology — building platforms, launching solutions, implementing trendy tools.
But six months later, KPIs don’t grow, users don’t come, and the budget’s gone.
Why?

It’s simple — because most startups and corporations begin with technology, not with the problem.
They come in saying: “We need AI,” “We want blockchain,” “Make us a Web3 version.”
And then it turns out that:

  1. there’s no data for machine learning, or it’s garbage,

  2. smart contracts don’t solve the task any faster than regular automation,

  3. users don’t understand why they need tokens.

But it should be the other way around.
Technology is a consequence, not a reason.

My company, DarinX, and I build custom solutions — from complex web platforms to extensions and mobile apps.
And there’s one idea I want to convey:
A successful project always starts with deep diagnostics.
Not with code. Not with the interface. But with the question:
What’s really stopping the business from growing?

Here’s an example:
One client wanted to launch AI for user engagement. Ambitious. But we dove into analysis.
We interviewed departments, studied the data, looked at user flows.
And realized: the issue wasn’t engagement — it was that the communication inside the product was falling apart.
People weren’t getting the right information at the right time.
In the end, instead of a complex AI module, we built a predictive notification logic — simple, fast, and results came within 3 weeks after launch.

Another case — we were building an MVP.
Instead of diving into code right away, we invested in the Discovery stage: analyzed processes, mapped out features, tested with real users.
The MVP brought +20% revenue in the first few months.
Not because it was “innovative,” but because it solved a real pain.

AI, Web3, blockchain, automation — all of these make sense when they know their place.

AI:

  • helps forecast demand, if you have historical data;

  • automates internal processes — from invoicing to security;

  • boosts personalization and increases retention.

Web3:

-cuts costs on international transfers and identity verification;

  • ensures transparency — e.g., for freelancer payments via smart contracts;
  • opens new ownership models — through NFTs and access tokenization.

But all this only works if you start with the problem, not the hype.
If you have validated hypotheses and understand how exactly it will improve your key metrics.

I’m a firm believer in always starting with a mini-version — a prototype, proof of concept, focus group test.
It reduces risk, reveals weaknesses, and doesn’t burn the budget if the hypothesis fails.

And one more thing:
Success is not just “launching the product.”
It’s maintaining it, scaling it, adapting it.
AI needs to be retrained.
Web3 needs legal and technical support.
Teams need training, users need engagement.
Whoever doesn’t do this — loses everything, even after a strong launch.

Conclusion?
AI won’t save your business. Neither will blockchain.
Only a clear understanding of your pain points and goals will.
Everything else is just a tool. Not the goal — the path.

Konstantin Bondar, CEO of DarinX