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Strategy: AI-Powered Web Design Process (5-Layer System)

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Decision WiderWings

AI-Powered Web Design Process

Strategy for WiderWings products (MedSchools.ai, CollegeDojo, Hedge, etc.)

Created: 2026-03-02
Source: Two YouTube videos on AI-based web design (transcripts in Second Brain)


The Problem

Our current process: Henry or Bob describes what to build → agent writes code → we eyeball it → iterate via chat. This is slow, inconsistent, and produces generic "AI vibe-coded" output.

The Solution: 5-Layer Design System

Combining insights from both videos, here's our new process:


Layer 1: Project DNA File (CLAUDE.md / AGENTS.md)

What: A per-project design config file that every agent reads before touching frontend code.

Why: Video 1's biggest insight — a .claude.md file acts as a persistent system prompt. Without it, every agent starts from zero and makes different design choices.

Our Implementation:
Every product repo gets a DESIGN.md that includes:

  • Brand colors (exact hex values)
  • Typography (font families, sizes, weights)
  • Component library preference (shadcn/ui, etc.)
  • Tone/voice for copy
  • Screenshot workflow rules
  • Link to brand assets folder

Action: Create DESIGN.md templates for MedSchools.ai and Hedge immediately. Any agent touching frontend code MUST read this first.


Layer 2: Frontend Design Skill (Mandatory)

What: The frontend-design-ultimate skill we already have installed.

Why: Video 1 showed a dramatic quality jump just from invoking this skill — transforms generic output into professional, modern designs. We already have this skill but we're not consistently using it.

Our Rule:

Every frontend task spawned to any agent MUST include: "Invoke the frontend-design-ultimate skill before writing any frontend code."

This goes in the task description template, not just memory. Non-negotiable.


Layer 3: Screenshot Review Loop

What: Automated visual QA where the agent screenshots what it built, compares to the target, and self-corrects.

Why: Video 1 showed this closing the gap from ~60% to ~90% quality. The agent literally uses its eyes to check its own work.

Our Implementation:

  • Use Puppeteer (already available) or Playwright (already installed for MedSchools QA)
  • Agent takes screenshot after building → compares to reference → fixes mismatches → repeat 2x
  • Exception: Skip screenshot loop for animated/dynamic elements (they cause infinite correction loops)
  • Store screenshots in /tmp/design-screenshots/ (auto-cleanup)

Config for DESIGN.md:

## Screenshot Workflow
- After building any page/component, take a full-page screenshot
- Compare against reference (if provided) or evaluate against brand guidelines
- Do 2 rounds of screenshot-review-fix
- Skip screenshot loop for animations/dynamic backgrounds
- Store in /tmp/design-screenshots/ (will be cleaned up)

Layer 4: Reference-Driven Design (Clone → Customize)

What: Instead of describing what we want from scratch, we give the agent a reference website screenshot + its CSS/styles, then tell it to clone and rebrand.

Why: This is the single highest-leverage hack from Video 1. Starting from "build me a landing page" = mediocre. Starting from "clone this specific page, then apply our brand" = professional.

Our Process:

  1. Find inspiration on Dribbble, Godly.website, Awwwards, or competitors
  2. Full-page screenshot (F12 → Ctrl+Shift+P → "Capture full size screenshot")
  3. Copy the CSS/styles from the reference site
  4. Give agent: screenshot + styles + our brand assets → "Clone this, then apply our branding"
  5. Screenshot loop kicks in to ensure fidelity

Inspiration Sources:

Source URL Best For
Dribbble dribbble.com UI components, dashboards
Godly godly.website Full landing pages
Awwwards awwwards.com Premium/award-winning sites
21st.dev 21st.dev Individual components (buttons, backgrounds, animations)
Competitors Direct URLs Industry-specific patterns

When to Use:

  • New product launches (find 2-3 reference sites first)
  • Redesigns (screenshot the "before" + the "target")
  • New features (find best-in-class examples of that feature)

Layer 5: Component-Level Polish (21st.dev)

What: After the page is 80% done, swap in premium individual components from 21st.dev or similar libraries.

Why: Video 1's "final hack" — full-page cloning gets you the layout and structure, but individual component swaps (buttons, backgrounds, card effects, animations) add the polish that makes it feel custom, not templated.

Our Process:

  1. Build the full page first (Layers 1-4)
  2. Identify 2-3 components that could be elevated (hero CTA button, background, card hover effects)
  3. Go to 21st.dev → find the component → copy the prompt/code
  4. Tell agent: "Replace the hero button with this component: [paste code]"
  5. Important: For animated components, tell agent to skip screenshot comparison

Rule of Thumb: Don't overdo it. 2-3 premium components per page max. More than that = visual noise.


Agent Architecture (from Video 2)

Video 2 covered three patterns we should apply to our design workflow:

Single Agent (Current)

What we do now — one agent handles everything. Works for small tweaks but unreliable for complex pages.

Sequential Agent (Recommended for Design)

Our design pipeline should be sequential:

Agent 1: Design Researcher
  → Finds reference sites, takes screenshots, extracts styles
  → Output: Reference package (screenshots + CSS + brand assets)

Agent 2: Builder  
  → Takes reference package → clones and customizes
  → Uses frontend-design-ultimate skill + screenshot loop
  → Output: Working page on localhost

Agent 3: Polish Agent
  → Takes working page → adds premium components from 21st.dev
  → Handles animations, micro-interactions, responsive tweaks
  → Output: Production-ready page

Agent 4: QA Agent
  → Screenshots final result on mobile + desktop
  → Checks brand consistency, accessibility, performance
  → Output: QA report + final approval or revision notes

Each agent's output feeds into the next. Predictable, reliable, high quality.

Parallel Agent (For Multi-Page Projects)

When building multiple pages (e.g., MedSchools.ai has landing, dashboard, blog, directory):

  • Spawn one builder agent per page (parallel)
  • All agents share the same DESIGN.md and brand assets
  • Final aggregator agent ensures consistency across pages

Deployment Pipeline

From Video 1's GitHub → Vercel flow (we already use this):

Claude Code (local dev) → GitHub (version control) → Vercel (auto-deploy)

Key Rules:

  1. Always test on localhost first
  2. Never auto-push to GitHub — agent must ask permission
  3. Vercel auto-deploys from GitHub (already configured for our projects)
  4. Keep sensitive info out of repo (use .env, .gitignore)

Implementation Checklist

Immediate (This Week)

  • Create DESIGN.md for MedSchools.ai repo with brand colors, typography, component rules
  • Create DESIGN.md for Hedge repo
  • Create brand_assets/ folder in each repo with logos + brand guidelines
  • Update task templates to include "Use frontend-design-ultimate skill" requirement
  • Set up Puppeteer screenshot workflow in both projects

Short-Term (This Month)

  • Build a reference library: Screenshot 5 competitor/inspiration sites for MedSchools.ai
  • Build a reference library: Screenshot 5 trading platform references for Hedge
  • Create a 21st.dev component shortlist (best buttons, backgrounds, cards for our use cases)
  • Test sequential agent pipeline on one MedSchools.ai page redesign

Ongoing

  • Every new page starts with a reference screenshot (no more "build me a page" from scratch)
  • Every design task includes DESIGN.md in context
  • Screenshot QA loop on every frontend change
  • Monthly review of design quality across products

Key Takeaways

  1. Never build from scratch — always start with a reference site clone
  2. Brand assets are non-negotiable — logo + guidelines in every repo
  3. The frontend-design skill transforms output quality — always invoke it
  4. Screenshot loops close the quality gap — but skip them for animations
  5. Component-level polish is the final 10% — 21st.dev for premium feel
  6. Sequential agents > single agent for design work — predictable pipeline
  7. Test locally, deploy deliberately — never auto-push to production

Created: Mon, Mar 2, 2026, 8:39 PM by bob

Updated: Mon, Mar 2, 2026, 8:39 PM

Last accessed: Wed, Apr 1, 2026, 11:57 PM

ID: 192bce1d-4ae4-48f3-acfe-f7431a543f6c