Transforming AI: Proactive Assistance Over Reactive Chat Interfaces

Let's challenge the status quo in AI product design: it's time to stop slapping on chat interfaces and start building proactive AI that understands user context, asks the right questions, and helps create better work.

1. Arthur is a product designer at Evil Marty, focusing on AI tools.
2. Many companies are adding chatbots to their products as an easy solution, but this may not be helpful.
3. When working on Tigon, an AI issue tracker, Arthur decided to do the opposite of what others were doing, and it worked.
4. The idea of using AI to help users proactively came fromClippy, a much-maligned feature from Microsoft Office.
5. Clippy had the right idea but poor execution and timing; now, with advancements in technology, implementing this concept is more feasible.
6. Tigon's AI monitors user input in real-time and provides contextual questions or suggestions, which they call "Suggestion Mode."
7. Instead of waiting for user input, the AI can identify when an issue can be split into sub-issues and provide a better way to organize the work (called "Action Mode").
8. Proactive AI assists users without interrupting their workflow, asking relevant questions, and providing helpful suggestions within the natural flow of work.
9. Users maintain control and can easily revert changes if needed.
10. Three rules guide the development of proactive AI: (1) supplement user agency, not replace it; (2) offer recommendations, never force them; (3) be part of the natural workflow, not an interruption
11. Proactive AI can identify common pitfalls and provide improvements in various fields, such as suggesting accessible design in real-time for those learning new tools.
12. Communication tools could prepare context or find relevant documents before meetings or calls.
13. To incorporate proactive AI, look for friction points where users must stop their work to ask for help.
14. Identify patterns in user behavior and questions to determine automation opportunities.
15. Consider the context to understand where AI can assist most effectively.
16. While AI interface design is still taking shape, simply copying and pasting chat interfaces isn't the answer.
17. Encourage experimentation with proactive AI solutions in products.
18. Challenge the status quo and propose unconventional UI solutions.
19. Opportunities for proactive AI include identifying friction points, understanding user behavior patterns, and considering context.
20. Proactive AI can provide assistance without interrupting workflow, helping users create better work more efficiently.
21. Companies should look beyond chatbots to harness the potential of AI in their products.
22. Proactive AI offers tailored support by understanding user needs and habits.
23. The three rules for proactive AI ensure that it complements user agency, offers optional recommendations, and integrates seamlessly into workflows.
24. By following these principles, developers can create powerful tools that enhance productivity and user experience.

Source: AI Engineer via YouTube

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