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What you are probably seeing
You notice your API bill rising each time you accept a suggested answer because each refinement adds hidden context to the request history.
Your output quality improves slightly, but you spend more time reviewing these suggestions and managing the extra prompts that appear after every interaction.
Why it happens
The model now includes a feedback mechanism that flags a shift toward usage-based pricing, where every micro-interaction incurs a cost.
Suggested answers are designed to burn through more tokens to ensure high performance, which drains your budget faster than manual coding tasks would.
You must weigh the quality of the session against the financial impact of these automatic, high-token interactions on your monthly expenses.
What changed recently
Step by step
1. Monitor your dashboard to track the token cost associated with accepting each suggested answer during a typical session.
2. Experiment with manually typing commands instead of using suggestions to compare the efficiency and cost difference between the two methods.
3. Review the session logs to determine if the quality of the code actually justifies the additional token expenditure from the feedback loop.
4. Set a specific token budget limit for your daily work to prevent the automatic suggestions from causing unexpected overages.
5. Document your workflow adjustments so you can clearly see whether the new feature improves your productivity or just drains your resources.
Ways to go further
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