---
title: Designing for Agentic AI
source: https://www.linkedin.com/pulse/designing-agentic-ai-yuri-pessa-ztcmf/?trackingId=gSoKslBrTP6VWNCDJSd7ZA%3D%3D
author: shenwei
published: 2001-02-27
created: 2025-03-02
description:
tags: []
---


The world of AI is constantly evolving, and with it, the way we interact with technology. You might have heard of Generative AI (GenAI), but what about Agentic AI? Let's explore the differences and the exciting implications for product designers.

## GenAI vs. Agentic AI: What's the Difference?

GenAI excels at creating new content, like text, images, or music. Think of it as a creative assistant that can generate ideas or translate languages. Agentic AI, on the other hand, is all about action. It can interact with its environment, make decisions, and even anticipate user needs. It's like having a personal agent working for you 24/7.

Example:

- GenAI: You ask it to write a poem about a cat, and it generates a beautiful piece of verse.
- Agentic AI: You ask it to schedule a meeting with a colleague, and it not only finds a time that works for both of you but also considers your preferred meeting locations and automatically sends out calendar invites.

## Designing for Feedback

Agentic AI is pushing us to reimagine product design. For years, we've focused on interfaces that react to direct user input—clicks, swipes, and edits. But agentic AI introduces a new dimension: proactive agents that anticipate needs and act autonomously.

This doesn't mean users become passive. Observing the AI's decision-making process, understanding its "thinking," is a form of interaction in itself. The user may not be clicking buttons, but they're still engaged, evaluating, and potentially intervening.

This shift requires a new design metaphor. Instead of just reacting to user actions, we're crafting experiences that provide live feedback as the AI operates. The focus is on transparency, allowing users to understand and respond to what's happening in real-time.

## Best Practices for Designing Agentic AI Experiences

Here are some best practices for designing agentic AI experiences:

- **Transparency:** Users should be able to understand how the AI is making decisions. This can be achieved by visualizing the AI's progress in completing a task and providing users with a summary of the AI's reasoning process.
- **Control:** Users should always feel in control of the AI. This can be achieved by providing users with a clear way to stop the AI from performing a task or to undo an action that the AI has taken, as well as allowing users to set preferences for how the AI should behave.
- **Personalization:** Agentic AI should adapt to individual user needs and preferences. This can be achieved by using the user's past behavior to predict their future needs and offer relevant suggestions, as well as allowing users to provide feedback on the AI's performance.
- **Conversation:** Design for natural, intuitive conversations between users and the AI. This can be achieved by using a conversational interface that allows users to interact with the AI using natural language and providing users with feedback on how the AI is interpreting their input.
- **Anticipation:** Agentic AI should be able to anticipate user needs and proactively offer assistance. However, users should also have the ability to control the level of autonomy they want to give to the AI. This can be achieved by providing users with clear controls to adjust the AI's level of autonomy, as well as providing feedback on the AI's anticipated actions.

By considering all five of these best practices, designers can create agentic AI experiences that provide the high level of real-time feedback that users will expect. This will help to ensure that users feel in control of the AI and that they understand how it is making decisions.

We're just scratching the surface of what's possible with agentic AI. What are your thoughts on designing for this new paradigm? Share your best practices or any other implications you foresee in the comments below!