# New feature and change explainer copilot

**Summary:** Create a new feature and change explainer copilot that answers “what changed?” and “what does this mean for me?” in context. Use AI to help users understand product updates and regulatory changes without flooding support teams.

**In short:** Explain product updates and regulatory changes in context so users understand what changed and what they should do next.

**Published:** 2026-02-18

**Last updated:** 2026-02-27

*This recipe shows how to turn release notes into in-product explanations that users can access when they need them most.*

Release notes and policy updates are essential but rarely read end to end. Users encounter changes directly in the interface and want quick answers. A change explainer copilot sits next to updated features and responds to these questions.

Create an **AI Skill** in the Retention stage, bound to an Audience that hasn't seen the feature yet, and has the right user role to access it. The frontend can supply more information when the user is on a screen tagged as “recently changed.” The skill can then respond to open questions like “What changed here?” and “Do I need to act?” by pulling from structured release content.

Organize your inputs with flat **Topics** like `Release-notes`, `Regulatory-changes`, `Feature-guides`, and `Migration-steps`. Store concise descriptions and impact notes under these Topics so the AI has focused, authoritative material. This reduces the chance that it improvises reasons or invents non-existent behaviors.

For some changes, you may want to ask the user a quick clarifying question via the skill—for example, whether they want to use a specific module even if they don't have it yet. Capture these in variables like `change_viewpoint` to tailor explanations. The skill can then adapt the narrative without changing the underlying facts, and possibly offer an upsell.

Internally, the assistant can watch for negative sentiment or repeated confusion around a change. When many users ask similar follow-ups or appear stuck, the skill can create **tasks** for product and documentation owners, plus **notifications** with aggregated feedback. This helps you improve both the feature and its communication.

On the user side, **in-app notifications** are a good companion to this recipe. Use segmentation by Audiences to show small “What’s new” chips or banners that invite users to click through to the copilot. After a while, you can limit these prompts to users who have not yet acknowledged or used the new feature.

**Conclusion**  
A new feature and change explainer copilot connects release and policy updates directly to the moments when users encounter them. With an AI Skill grounded in release- and change-related Topics, plus internal tasks and notifications for problematic updates, you reduce confusion and release-related ticket spikes.