A useful AI feature helps someone complete a clear task while keeping their choices visible. This practical guide explains how to design inputs, previews, feedback, and recovery paths for an AI-assisted product.
PRODUCT DESIGN NOTES
Intent → Preview → Review → Apply
A suggested interaction pattern for an AI writing assistant.
1. Define the job before adding a chat box
Start with a sentence: “People need help doing ___ because ___.” For example, a small business owner might need to shorten a product description without losing its delivery details. That is a clearer problem than adding a chatbot everywhere. Decide what a successful outcome looks like and whether a familiar form or editor already solves it.
2. Combine instructions with simple controls
A blank prompt can leave people wondering what to ask. Offer an editable example and useful controls such as audience, length, and tone. Keep free-text instructions available for exceptions. In a writing tool, “Shorten this description” beside a length selector gives people a starting point without forcing them to learn a special prompting style.
3. Explain what information the feature uses
Before generation, show which document or selected text will be used. If a person attaches material, make removing it straightforward. Avoid implying that the tool has checked a database, browsed the web, or verified a fact unless that actually happened. Clear boundaries help people decide when the output needs further checking.
4. Preview changes before applying them
Keep the original beside the proposed revision, or highlight the changes. Label actions precisely: “Replace selected paragraph” communicates more than “Continue.” For consequential actions, show the destination and effect before asking for approval. Generating a draft and sending it should be visibly separate steps.
5. Design useful waiting and failure states
Tell people that work is in progress and let them cancel where the product supports cancellation. Preserve their input if generation fails. An error message should say what remains safe and what they can do next: “Your original text is unchanged. Try again or edit it manually.” Avoid fake progress percentages when actual progress is unknown.
6. Make correction and undo easy
People should be able to edit output directly, retry a selected part, or return to the original. Regeneration should not silently remove earlier work. In a prototype, include at least one unsatisfactory result so you can observe how participants recover. A polished success screen alone will miss much of the experience.
7. Test the whole task
Give someone a realistic goal and watch whether they understand the input, inspect the result, and complete the next step. Record confusion and recovery effort alongside completion time. Ask what they believe the system did; their answer can reveal misleading labels even when they reached the finish.
A compact review checklist
- Is the task clear without a long explanation?
- Can users see and change the input?
- Are generated suggestions distinguishable from verified information?
- Can they review the effect before applying it?
- Can they cancel, edit, and recover without losing their work?
This is a proposed design workflow, not a report of measured client results. Start with one narrow task, test the difficult states, and improve the interaction before expanding the feature.
Further reading
Nielsen Norman Group’s guide to designing AI products and features collects research on AI interaction patterns, user needs, and usability.
Want to map a clearer product flow? Discuss your app or dashboard, or explore the design journal.
