Search Your Project Website Library with an AI Coding Agent

Contents

• [Start with a design question, not a site name](#start-with-a-design-question-not-a-site-name)
• [Turn the shortlist into a build decision](#turn-the-shortlist-into-a-build-decision)
• [Search beyond screenshots](#search-beyond-screenshots)
• [A simple workflow for your project](#a-simple-workflow-for-your-project)
• [Use this in your AI agent](#use-this-in-your-ai-agent)

An AI coding agent can search your project website library by describing the pattern you need, such as a dark SaaS hero, oversized proof section, or compact feature grid. The useful result is a shortlist of saved references plus concrete details your agent can compare before it writes code.

Start with a design question, not a site name

Use a search request that describes the outcome or visual pattern:

• "Find saved references with a dark grid, restrained CTA, and strong visual composition."
• "Show landing pages with oversized proof, generous whitespace, and a clear headline."
• "Find examples where the product itself is the hero through a live code-and-render demo."
• "Search for compact feature grids with concise install commands."

This is more useful than searching only for a company or domain because it gives your agent a design direction to compare. You can narrow the request by page type, section, viewport, typography, color, or interaction.

Open the examples below and compare the first screen before borrowing a pattern. The saved references include Vercel AI, Braintrust, json-render, and AI SDK, with notes about the visual choices they illustrate.

Turn the shortlist into a build decision

For each reference, check four things:

1. Job: What does the section help the visitor understand or do?
2. Hierarchy: What gets attention first, and what supports that message?
3. Evidence: Does the page use product UI, proof, code, imagery, or a feature list?
4. Cost: What would be expensive or distracting to copy in your own product?

For example, a dark grid may create a strong technical mood, but it should not replace a clear product explanation. Oversized proof can make a landing page feel confident, but it needs evidence that matches your product. A live demo can explain a technical tool quickly, while a compact feature grid may work better when visitors already understand the category.

Ask your agent to summarize these tradeoffs instead of copying a page wholesale. A good request might be: "Compare the top five saved references for a developer product homepage. Recommend one hero structure and one proof structure. Explain what to borrow and what to avoid."

Search beyond screenshots

A saved reference is more useful when your agent can inspect the details behind the visual impression. Search for typography families, font weights, line heights, color roles, contrast, spacing, borders, radii, shadows, gradients, and component styles when those details matter to the decision.

You can also ask for page structure and viewport behavior. For example:

• "Find references with a sticky navigation and a product demo visible near the top."
• "Compare the spacing and heading scale in these saved SaaS references."
• "Find pages that use a muted background with one high-contrast CTA color."
• "Review the mobile structure of the saved examples and list likely layout changes."

Treat these as observations to test, not rules to reproduce. The goal is to give your agent enough context to make a deliberate implementation choice.

A simple workflow for your project

Use this five-step loop:

1. Save strong references as you encounter them through the browser extension.
2. Label each one with the job it helps solve, such as hero, pricing, proof, or navigation.
3. Ask your AI coding agent for a description-based shortlist.
4. Compare two or three references against your product goal and audience.
5. Ask the agent to turn the selected direction into a small implementation plan before changing code.

Keep the shortlist small. Three relevant references are usually easier to compare than twenty loosely related pages. If the result is too broad, add constraints such as "B2B developer tool," "mobile-first," "no photography," or "show the product above the fold."

Use this in your AI agent

> Search my saved project website references for examples of [describe the page or section]. Return the five closest matches, explain the observed layout, typography, colors, spacing, and interaction patterns, then recommend one direction for my product. Separate observations from your implementation suggestions, and do not copy any site's branding or content.

Install Fudge for your AI agent to search and compare saved website references while you build.

Give the search enough context to distinguish a developer tool from a general SaaS page. Include the audience, the main action, and the visual constraint you care about.

Try:

> Find saved website references for a developer tool landing page aimed at engineers. Prioritize a clear product demo, technical credibility, restrained color, readable code or interface examples, and a strong sign-up path. Return separate matches for the hero, proof section, and feature explanation.

Then ask for a comparison rather than accepting the first match:

> Compare the three best references. For each one, list the section order, headline scale, product-demo placement, CTA treatment, and mobile risks. Recommend the simplest structure that would help a new visitor understand my product in ten seconds.

If the results are too broad, add phrases such as "API product," "documentation-led," "dark interface," "live preview," or "no decorative illustrations." If they are too narrow, remove one visual constraint and search again.

Ask your agent to extract decisions, not markup. The plan should explain what the page needs to communicate, which pattern supports each message, and which details should be adapted to your product.

Use a request like:

> Using the saved references as inspiration, write an implementation plan for my landing page. Keep my brand, content, and product behavior original. Specify the section order, purpose of each section, responsive behavior, heading hierarchy, CTA placement, and the minimum product UI needed for the demo. Call out any pattern that would be hard to maintain or could distract from the main action.

Before coding, check that every proposed section answers a visitor question. The hero should explain the product and next step. The proof section should reduce doubt. The feature section should connect capabilities to jobs. Remove any element that exists only because it looked impressive in a reference.

Related questions

• Search Your Saved Website References with an AI Coding Agent
• Search Your Design Inspiration Collection With an AI Coding Agent
• Use Your Captured Website Designs in Claude Code
• Save Websites to a Website Mood Board