Design AI Products

In this lecture, you’ll walk through a clear framework for taking an AI idea from concept to shipped feature.

In this lecture, you’ll learn how to spot high-value problems that genuinely benefit from intelligence rather than automation.

In this lecture, you’ll explore lightweight methods for assessing feasibility, usefulness, and user need before investing in development.

In this lesson, you’ll learn how to craft better prompts that give AI the structure and tone it needs to generate usable content.

In this lesson, you’ll explore real-world prompt templates you can reuse for writing text, building UIs, and visual assets.

In this lesson, you’ll apply your prompt skills in guided exercises to generate headlines, CTAs, and feature blurbs.

In this lesson you learn how tokens, embeddings, and attention define how AI interprets text.

We’ll break down parameters like temperature, max tokens, and top-p — and how they impact the model’s tone, style, and predictability.

We’ll introduce PromptOps as a systematic approach to working with prompts — treating them as a repeatable process rather than random one-off requests.

You’ll learn that not all prompts are equal — some are disposable, some reusable, some dynamic with variables, and some become the core "brain" of an AI agent.

In this lesson, we’ll introduce a practical framework that helps you design prompts with clarity and intention.

Here, we’ll address the limitations that every professional must understand. You’ll explore why models hallucinate, why they sound confident even when wrong, and how hidden biases appear in outputs.

In this lecture, you’ll learn how research insights translate into data requirements that shape your AI feature’s behavior.

In this lecture, you’ll examine how bias emerges in data and how designers can prevent harmful outcomes.

In this lecture, you’ll understand how to work effectively with data scientists and ML engineers during early-stage exploration.

In this lesson, you’ll learn what a design system is and why it’s an essential part of professional product design.

In this lesson, you'll earn how to create and manage color variables to keep your design consistent and efficient.

In this lesson, you’ll discover how Modes expand the power of variables in Figma.

In this lesson, you'll discover how text variables can help you manage typography at scale.

In this lecture, you’ll learn how to standardize spacing values using variables. We’ll go through how to set up and apply consistent margins, paddings, and gaps in your layouts.

In this lesson, you’ll learn what Boolean variables are and how they can be used to control visibility in your designs.

Understand the fundamentals of creating reusable UI components in Figma. You’ll learn how to build buttons, cards, and navigation elements that stay consistent while remaining flexible.

In this lesson, you’ll discover why clear naming conventions are crucial for collaboration and scaling your work.

In this lesson, we’ll walk through where AI lives inside Figma, from the command bar to built-in shortcuts.

In this lesson, you’ll watch how to build a complete landing page from scratch using Figma’s AI tools.

In this lesson, you’ll explore three new Figma formats that let you generate layouts, slides, and social content with AI.

In this lesson, we’ll use tools like Tidy Up, Auto Layout, and Layer Rename to clean and align our designs faster.

In this lesson, you’ll discover what prototyping really means in the context of UX and UI design.

You’ll learn how Figma’s prototyping tools help you simulate user flows, demonstrate interactions, and communicate design intent — all without writing a single line of code.

In this lesson, we’ll move from theory to hands-on practice.

You’ll learn how to link frames, create transitions, add overlays, and simulate real app behavior.

In this lecture, you’ll dive into motion design and learn how to use Figma’s animation features to create smooth, realistic transitions.

In this lesson, we’ll compare two major stages of prototyping — low-fidelity and high-fidelity.

You’ll understand the purpose, strengths, and limitations of each, and learn how to choose the right fidelity depending on the project’s goals and stage.

In this lecture, you’ll learn how to represent different AI states and outputs to simulate real model behavior in prototypes.

In this lecture, you’ll understand how user behavior influences future AI responses and how to reflect that in your designs.

In this lecture, you’ll explore modern tools that allow designers to test AI logic, model variability, and interactions without coding.

In this lecture, you’ll explore methods for communicating AI reasoning, confidence, and limitations through the UI.

In this lecture, you’ll learn how to design experiences that gracefully manage uncertain, inconsistent, or unexpected AI responses.

In this lecture, you’ll discover how to measure AI usefulness, accuracy, trust, and performance in a way that aligns with user needs.

In this lecture, you’ll learn how to run user tests with real model behavior to observe understanding, trust, and interaction patterns.

In this lecture, you’ll explore how AI systems evolve over time and how to design for updates, retraining, and long-term adaptation.