Power pointed out that incremental fine-tuning within the same generation (such as the upgrade from GPT-5.1 to GPT-5.2) relies on specific training data and helps teams achieve rapid iteration, but is considered a short-term investment internally; real performance breakthroughs always come from the release of new base models, and each major version jump will prompt the team to recalibrate their short-term focus.

Regarding the evolution of product interaction, Power emphasized that the core challenge of current AI assistants lies in guiding users to understand and unlock the potential of the technology, rather than just model quality.

