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Google‘s recent decision to hide the raw reasoning tokens of its flagship model, Gemini 2.5 Pro, has sparked a fierce backlash from developers who have been relying on that transparency to build and debug applications.
The change, which echoes a similar move by OpenAI, replaces the model’s step-by-step reasoning with a simplified summary. The response highlights a critical tension between creating a polished user experience and providing the observable, trustworthy tools that enterprises need.
As businesses integrate large language models (LLMs) into more complex and mission-critical systems, the debate over how much of the model’s internal workings should be exposed is becoming a defining issue for the industry.
A ‘fundamental downgrade’ in AI transparency
