As an active user of OpenAI products, I have identified a systemic issue in newer model versions (particularly o4): the AI fails to accurately interpret user instructions, despite visible attempts to analyze queries. The generation process exhibits logical deviations — the model introduces content irrelevant to the task, suggesting the presence of a filter or interpreter that distorts the original input.
I propose implementing a strict compliance mode with the following features:
- The model must adhere to instructions verbatim, avoiding creative reinterpretation.
- Responses are automatically validated against query requirements (e.g., via an integrated validator).
- Non-compliant outputs are rewritten without retaining erroneous variants in the chat context.
The current problem escalates with chat length: deviations accumulate, reducing the practical utility of outputs. This is particularly critical in coding tasks, where minor deviations from specifications render results unusable. Competing solutions (e.g., Claude) demonstrate better instruction discipline but lack computational power. Optimizing text interpretation and introducing instruction prioritization mechanisms would resolve the key paradox: the model is technically capable of solving tasks but fails due to errors at the query decoding stage.