Over the past two years, the corporate market has plunged into a true state of enchantment with generative artificial intelligence. Tools like vibe-code and other agent-based solutions promised to revolutionize the way software is produced, drastically reduce teams, and boost productivity. For many companies, it seemed like the “perfect shortcut”: replacing entire teams with AI assistants capable of generating code, analyzing data, and even structuring entire workflows.
At the peak of the hype, several business models were redesigned. Lean startups, reconfigured departments, and even industry giants began experimenting with the idea of an “augmented developer,” capable of delivering double or triple the output with AI support.
The reality check: limits and costs
However, the 2025 landscape tells a different story. What once seemed unlimited now reveals the restrictions imposed by the very business models of AI platforms. A clear example is found in plugins that use agents: while they initially offered 25,000 tokens per session, today, in premium plans, they provide only 3,500 tokens.
This shortening of “computational breathing space” drastically changes the cost–benefit equation. What was once seen as a cheap substitute for larger teams now reveals itself as a strategic and limited service. In other words, companies must balance their expectations: AI is not an infinite production machine but a costly, finite resource that must be optimized.
Balance and a new perspective
This adjustment is likely to push the market out of the enchantment phase and into a stage of rational use of AI. The reduction in token limits means that projects will need to be better planned, demands more focused, and internal processes more optimized.
Instead of mass layoffs, a reskilling movement may emerge: using AI as support, accelerating stages, and enabling smaller teams to be more creative and strategic. The view that “AI will replace everything” begins to give way to a more mature perspective: “AI amplifies, but it doesn’t solve everything on its own.”
And the future of developers?
For the IT market, the impact is ambiguous. On one hand, professionals who relied solely on repetitive tasks risk losing ground. On the other, new opportunities arise for developers who master both coding and the intelligent orchestration of AI — knowing when to use it, how to break problems down into smaller prompts, and how to combine human and automated tools.
The near future is likely to increasingly value the hybrid professional: not only those who know how to code but also those who know how to direct AI to deliver real value within technical and financial constraints.
Conclusion
From the initial enchantment to the current disenchantment, what is unfolding is a collective learning curve. Companies and professionals are realizing that artificial intelligence is not a panacea but a sophisticated and expensive resource that must be managed carefully.
In the end, the greatest legacy of this phase may be the sector’s maturation: less euphoria, more strategy. And for developers, a clear message emerges — the market hasn’t ended, it has simply changed form.
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