For nearly three years, the Tech and Design community has been asking itself the same question regarding artificial intelligence: "Is the model capable of doing it?"

Translating a complex UI component into clean code, maintaining the consistency of a Design System via a terminal, or iterating in real time on screen architectures… All of this was either science fiction or required heavy manual corrections.

By 2026, with cutting-edge models like Claude Fable 5 and integration tools like Claude Code, this capacity barrier has fallen. The rendering is surgical. AI knows how to do it.

But just when we thought we were entering the golden age of infinite productivity, we have hit a whole new wall. A radically different constraint: the token economy.

The truth on the ground: The day my "Max" plan lasted for 5 requests

The experience our teams had this week is a textbook case. While working intensively on generating and integrating UI components directly via the terminal with Claude Code, an absurd observation was made: a full Max package (the 5-hour quota) was completely consumed in just 5 requests , representing 15% of the overall weekly quota.

How did we get here ?

The tool reanalyzes your entire project context (tree structure, configuration files, existing components, session history) with each command to ensure consistency. In this configuration, Prompt Caching becomes ineffective: you re-enter the entire context with each interaction.

Beyond the technical challenge, a strategic impression emerges: the feeling that publishers are adjusting their consumption models to encourage intensive users to abandon fixed plans for usage-based billing, which is more profitable for them.

The paradigm shift: From performance to arbitration

For Product Managers or Design Leads, this shift completely changes the rules of project management. We're moving away from a purely performance-driven approach and towards a contextual budget- driven one . The key skill for a designer or builder is no longer knowing how to prompt, but knowing how to make informed decisions.

Using a top-of-the-line model for a routine task or minor cleaning has become the economic equivalent of taking a private jet to buy bread. It's operational nonsense.

Teams need to adopt new habits:

• Plan intensive but rationed AI sessions.

• Educate everyone about the "cost of the token".

• Implement a multi-model governance to delegate simple tasks to lighter and less expensive models.

Conclusion: Token budgeting, a new indicator of success

AI has delivered on its promise: the boundary between design and code is broken. But this fluidity comes at a measurable cost in context tokens.

For design teams, maturity will no longer be measured by the number of AI-generated features, but by our ability to orchestrate these tools with sound economic judgment . The role of the Designer or PM becomes that of a conductor, vigilant about their AI attention budget.

Philippe Elovenko, Product designer at UX-Republic