Almost every AI tool you try as a designer falls short. You ask for a hero section and get generic Tailwind templates. You need your button component but get random CSS. Nothing looks like your brand. Nothing follows your design system.
Why does this keep happening? Because these tools don't have context. They don't know about your 8px spacing grid. They don't know you use Inter for headings. They don't know your primary button has three specific states. They're guessing when they should be knowing.
But you already have the cheat code in front of you. Every Figma component you've made. Every design token you've defined. Every pattern you've established. These are more than just design artifacts. They're the exact context AI needs to build things your way.
In this article, you'll learn how to give AI the proper context so your next design review could be a pull request.
Context engineering is the art of providing AI with all the background information it needs to build things correctly. Your designs, your component library, your existing codebase and your code patterns help AI understand not just what you want, but how you want it built using your specific system.
As a designer, you create context every time you make design decisions. Your Figma components with their three variants. Your color tokens like color-primary. Your 8px spacing grid and Inter font choice. Your established visual patterns. All of these become context that tells AI how to build things your way.
Even the code your developers write becomes context that helps you as a designer. The React components they've built that you can reuse. The styling solution they've chosen like Tailwind or styled-components. The file structure and naming patterns they've established. The way similar features are already implemented in your product.
When you provide both types of context, AI understands:
- Your visual design system and how to apply it
- Your existing codebase and how to build within it
- Your patterns, both design and development
- Your constraints and preferences from both sides
Context is the key to building ideas. But how do you actually provide all this context to AI? Let me show you with a real tool.
For this post, I’ll use Fusion, our visual development platform at Builder.io.
We built Fusion because we wanted designers to have a tool that truly understands their complete context, not just their prompts.
Want to follow along? You can sign up for Fusion for free and connect your own repository.
Now let's explore how each type of context changes everything about working with AI.
Your Figma files spell out your exact spacing, colors, layout, everything.
Without context engineering:
You tell AI "Create a settings page" and it gives you some generic form layout with random inputs and misaligned labels. Nothing like what you designed. You're stuck prompting for hours trying to make it match.
With context engineering in Fusion:
You share your Figma design and say "Implement this settings page". Fusion looks at your design, finds your existing code and layout patterns in the codebase, and uses those. It keeps your spacing tokens, your typography, everything. What you designed is what you get.
Sometimes you see a layout online and think "I want something like that for our site."
Without context engineering: You try explaining it. Perhaps, "Make it like Stripe's pricing page but with our colors." AI has no clue what Stripe's page looks like. You end up describing every little detail and it still misses the point.
With context engineering in Fusion: You use the Chrome extension to grab a specific section from the page, then tell Fusion "Add this to our site." It captures the structure and layout you liked but rebuilds it using your components, your design tokens, your brand. You get the best parts of the inspiration perfectly adapted to your system.
Your PRDs, design specs, and documentation are context too. Every requirement your PM wrote, every state you need to design for.
Without context engineering:
You copy-paste bits from a 20-page PRD into your AI prompts, trying to capture all the important parts. But the AI misses requirements you didn't explicitly mention. You get designs missing error states, empty states, or responsive behaviors. Your PM asks "but what about this requirement?" and you're back to re-prompting with more details.
With context engineering in Fusion:
You attach the PRD and say, "Update the CRM dashboard to add the new sales pipeline section from the requirements." Fusion reads the requirements, understands the pipeline stages, the metrics to display, how it should integrate with the existing dashboard layout, and creates the complete section. Nothing gets missed because the context is all there. Your PM's requirements become your implemented design.
Every team has design rules. Use this font. Follow the 8px grid. Make it accessible.
Without context engineering:
You repeat these rules in every single prompt. Sometimes you forget one. The output is inconsistent. Your design system becomes a suggestion instead of a standard.
With context engineering in Fusion:
You set your rules once. "Always use Inter font, 8px spacing grid, ensure keyboard navigation." Done. Every future prompt follows these rules automatically. Your standards actually stay standard.
Your existing codebase contains patterns, components, and conventions that your developers have already built. Leverage them.
Without context engineering:
You say "Add a carousel" and AI builds everything from scratch. New CSS, new structure, doesn't match anything else on your site. Your developers have to rebuild it.
With context engineering in Fusion:
You attach you designs, type "Add a carousel using DaisyUI components". Fusion understands your components, how they work, and creates a carousel that matches. Same patterns, same code style, fits right in. Zero rework for developers.
Sometimes you just need to tweak one thing on a page.
Without context engineering:
You say "Add more color options to the product page" but AI doesn't know which element you mean. It might add colors to the wrong section, create a completely new color picker, or break your existing product layout trying to figure it out.
With context engineering in Fusion:
You select the "Choose your color" palette in the visual editor and say "Add sunflower yellow, zombie green, and fire engine red options." Fusion modifies only the selected color picker, adds the three new colors while preserving the existing palette design and functionality. You get a surgical update exactly where needed.
Lorem ipsum is fine, but real content often breaks lorem ipsum designs.
Without context engineering:
You design a beautiful newsletter form or product reviews section. They look perfect but don't actually work. Your developers have to wire up the backend, handle data fetching, add validation.
With context engineering in Fusion:
You connect your database MCP server and say "Create a newsletter signup that saves to our database." Fusion builds the form, creates the necessary tables if they don't exist, and connects everything directly to Supabase. Real submissions, real data storage, real validation. Or pull actual product reviews with real ratings and user data straight from your database. Your UI is functional from day one.
Here's the thing about context that makes it so powerful. It compounds. Each piece of context you provide doesn't just add to the pile. They work together to give AI a complete understanding of what you're trying to build.
Let's say you're building a CRM dashboard. You import your Figma dashboard design as your first layer of context. Your codebase already has established component patterns and layouts. Your custom instructions include your chart color palette and accessibility requirements. Your PRD attachment specifies the new sales pipeline section requirements. An MCP server provides real user data from your database.
Now when you say "Build this dashboard" you get a production-ready dashboard that looks exactly right, uses your existing components correctly, includes all the requirements from your PM, and displays actual data. All from a simple prompt, because you provided the right context upfront.
The more context you provide, the better your results. But you don't need everything at once.
Try Fusion for free and connect your repository. Import one of your Figma designs. See what happens when AI has full context about your design system.
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