Big AI Theory: Squeeze Model Capabilities by Adjusting Reasoning Levels in Three Stages

The author proposes a "Big AI Theory," using three-stage conversations to maximize model capabilities. Step one maximizes reasoning and selects plan mode, using voice, images, and video without filtering to dump ideas and organize them into a plan; step two switches to medium reasoning for quick execution, provided the requirement description is detailed enough—the author cites Terminal Bench 3.0 to show that detailed requirements with medium reasoning yield higher quality than vague requirements with high-end reasoning; step three adjusts reasoning back to high-end for the AI to review the medium-reasoning results, claiming it can identify about 20% of issues, with review time taking about one-third of generating from scratch.