The experienced developer shared insights: in a few months of working with AI assistants, he created more prototypes than in the previous three years. Functions that used to be weekend functions are now implemented within hours, and "mutory" tasks have become almost time-free. The paradox, however, is that this acceleration has hardly affected the main point: finding a real problem, understanding users, and building distribution channels remains difficult. The code was no longer a bottleneck - but the barrier of demand remained unchanged.

The AI tools have made the development process more honest: there are no more excuses like "too hard to implement." If a product is not released, the reason is more often not technical limitations but lack of confidence that someone needs it. The community jokes that 2026 will be remembered as a year when code was hurled at an untold speed into every task in a row, still figuring out which ones are worth solving at all.

But the developer remains a "soft niche": AI is no substitute for strategic thinking, complexity management, and communication skills. Virtual showcases are littered with clones and superthin products that don’t solve real problems - and drawing attention to even a quality solution is becoming more expensive than ever. The acceleration also had a side effect: the raw app is now quickly going to market and just as quickly fading, leaving no time for fantasies about future success.