Windsurf Tab v2: 25-75% more accepted code with Variable Aggression

One year after the initial launch of the predictive code tool Tab, the Windsurf team has introduced Tab 2.0, featuring significant improvements in its underlying model and context engineering pipeline, resulting in a 54% increase in characters per prediction while maintaining acceptance rates. Understanding that users have diverse preferences for autocomplete behavior, Windsurf tailored the tool to allow users to adjust the "aggression" level of predictions, balancing the risk of more extensive code suggestions with the likelihood of acceptance. This customization emerged from extensive testing and user feedback, revealing differing opinions on prediction boldness. By refining the context engineering and data pipeline, the team reduced the system prompt prefix by 76%, enhancing performance and efficiency. Tab 2.0 aims to optimize the amount of code generated per call, prioritizing user efficiency over merely achieving high acceptance rates, and represents a step forward in AI-assisted coding by catering to individual user preferences.