Figma to Code AI-Assisted Research Prompt Engineering Design Critique Workflow Experiments Component Generation UX Research Synthesis Rapid Prototyping Figma to Code AI-Assisted Research Prompt Engineering Design Critique Workflow Experiments Component Generation UX Research Synthesis Rapid Prototyping

AI Workflow Lab

Real work,
honest process.

A living record of building a product with AI — from strategy to code. Each entry documents what was attempted, how Claude was used, what worked, and what didn't.

04 Entries logged
Ongoing Cadence
2026 Started

About this lab

Purpose

I used Claude to brainstorm and shape a product strategy from scratch — then started building. This page documents that process as it happens: the decisions made, the tools used, what AI got right, and where human judgment had to step in.

What you'll find here

Real prompts, real outputs, real critique. Each entry captures what was being built, the approach taken, key prompt strategies, and a candid reflection on outcomes and surprises.

Why it matters

AI fluency is becoming a core design skill — not a shortcut, but a new kind of craft. Every build feeds directly into Terra, a product I'm designing in parallel. This log is how I build that fluency intentionally, not accidentally.

Tools in rotation

Claude for reasoning, critique, and code generation. Claude Code in VS Code for building components and pages. Figma for design decisions and visual logic — connected to Claude Code via MCP. Other tools introduced deliberately — only when a specific gap appears.

My approach

How the process works

01 —

Define the brief

One design problem, one focused constraint. Write the brief before opening any tool. Vague inputs produce vague outputs — specificity is the skill.

02 —

Strategise with Claude

Use Claude to brainstorm, critique, and shape the approach before building anything. Product direction, IA, component logic — thinking happens here first.

03 —

Build with Claude Code

Build the component or page directly in Claude Code (VS Code). Ship working HTML/CSS first. Document the real prompts used, not polished ones.

04 —

Extract the insight

One honest takeaway: a prompt pattern worth keeping, a workflow adjustment, or where AI didn't help. Log it. That's the point of this page.

Build log

Newest first
Workflow Claude Claude Code Skills Tooling

Teaching Claude to remember — setting up Project Instructions and Claude Code skills

This session covered setting up Project Instructions in Claude.ai — a persistent system prompt that carries context across every conversation — and writing four Claude Code skill files that load design system rules, accessibility standards, UX practices, and a security audit checklist directly into the build environment.

Tools used

Claude, Claude Code

Type

Workflow setup

Time

~2 hours

Outcome

Project Instructions now hold full context: design system spec, tool stack, workflow split between Claude.ai and Claude Code, friction rules, and a running build log. Claude Code has four skill files in a dedicated skills/ folder, each with YAML frontmatter that defines when it should trigger. The result is a session that starts informed rather than blank — no re-establishing ground rules, no re-pasting the design system.

Key insights & challenges

The two memory systems work completely differently and that distinction matters. Project Instructions in Claude.ai are conversational — Claude reads them silently and applies them throughout the chat. Claude Code skills are more like reference documents you explicitly invoke at the start of a session. Neither is automatic in the way you'd want: Project Instructions still drift in long sessions, and Claude Code skills still need to be called by name. The real insight is that these tools shift the burden from memory to discipline — you still have to write the rules clearly and invoke them consistently. The upfront investment is worth it, but it doesn't eliminate the need for human oversight in every session.

Strategy Terra Claude Product Thinking

From blank slate to product strategy — user research, competitive analysis, JTBD, and MVP scope

Using Claude as a strategic thinking partner, I ran a full PM workstream: defined positioning, conducted competitive analysis across an existing product category, synthesised qualitative user research from five interviews, mapped Jobs To Be Done across core use cases, and locked MVP scope. The goal was to build the right thing before building fast.

Tools used

Claude

Type

Strategy / Product Thinking

Time

~3 sessions across multiple days

Outcome

The core product decisions — MVP scope, login strategy, and overall flow — came from my own judgment, with Claude helping pressure-test and articulate the thinking. Where Claude added most value was in the research synthesis: two participants independently described the same failure pattern in different contexts, which became a hard content rule; one participant had deleted a comparable app for low utility, which sharpened the first-session brief considerably.

Key insights & challenges

The most unexpected insight came from a bias Claude introduced without flagging — it assumed gender for participants whose pronouns were never stated in the transcripts. When caught, the same assumption had been made across multiple users. For a product designed to be non-judgmental and inclusive, it was a useful reminder: AI makes demographic assumptions quietly and confidently, and human oversight isn't just a quality check — it's an inclusivity check.

Iteration AI Lab Figma Claude Code Tooling

Iterating on the AI Lab page — design system, Figma MCP, and where Claude falls short visually

A full refinement session on the AI Lab page — typography scale, spacing, copy tone, responsive layout, entry structure, and collapsible log entries. The session also established the full workflow going forward: Claude Code in VS Code reads Figma designs via MCP, generates components, and those components get integrated into the live page. The gap between that ideal and reality surfaced quickly.

Tools used

Claude, Figma, html.to.design, Claude Code

Type

Iteration / Tooling

Time

~3 hours

Outcome

The page now accurately reflects the real process. Entry format split into separate Outcome and Key Insights blocks. Tools section updated to reflect the actual stack. Copy cleaned of references to workflows not in use. Figma MCP connected to VS Code via remote server — Claude Code can now read Figma frames directly and generate code from them.

Key insights & challenges

Claude lacks visual design judgment. The expand/collapse functionality it generated was structurally correct but visually wrong — the interaction felt broken and the collapsed state unpolished. I had to open Figma and draft how I actually wanted it to look. To bring the HTML into Figma I tried two tools: Magic Patterns (did not import files or add autolayout) and html.to.design plugin (converted the HTML into a proper Figma file with styles, components, and autolayout — this worked). Claude is strong at structure and logic, weak at visual feel. Figma remains the right place to make visual decisions, even when working code-first.

Infrastructure Terra Next.js Vercel Claude Code

Migrating Terra to Next.js — proper infrastructure, live in 1.5 hours

The single HTML file had served its purpose — validate the design before investing in infrastructure. This session migrated the Terra signup flow into a proper Next.js app: structured folders, React components, CSS modules, and design tokens extracted to a shared file. Connected to GitHub, configured Vercel, promoted to production.

Tools used

Next.js, Claude Code, GitHub, Vercel

Type

Infrastructure / Migration

Time

~1.5 hours

Outcome

Terra is live at terra-beige-mu.vercel.app/signup — Next.js, proper folder structure, design tokens in a single tokens.css, image assets in public/images. Claude made Next.js accessible without deep technical knowledge — setup that would normally require long documentation happened conversationally, with each error explained and fixed in context.

Key insights & challenges

The hardest part was the tooling. Git branch mismatch (master vs main), wrong Vercel framework preset causing 404s that looked like code errors, CSS module imports that work differently in Next.js, file management without terminal knowledge, image format mismatches (.jpg vs .png). Each a 2-minute fix once diagnosed — the hard part is knowing where to look. Structure first pays off immediately: tokens in one place, components in their own files is already cleaner than a single HTML approach.

Infrastructure GitHub Vercel

Setting up Terra's repo and shipping the first live deploy

Before building features, the foundation needed to exist. This session covered getting the GitHub repo live, connecting it to Vercel, and establishing the deploy workflow. No terminal — everything done through the browser and GitHub Desktop. The goal was simple: a real URL that works on any phone, today.

Tools used

GitHub + Vercel

Type

Infrastructure / DevOps

Time

~45 minutes

Outcome

Terra is live at terra-beige-mu.vercel.app, deployed from a private GitHub repo via Vercel's automatic deploy on push. The setup was intentionally quick — validate the design before investing in infrastructure. It worked.

Key insights & challenges

Shipping something live — even bare minimum — changes how seriously you take the next step. Prototype first, then migrate. Validate the design before investing in infrastructure.

Workflow Claude Portfolio Friction

Building the AI lab page — and hitting the limits of Claude in the same session

Starting point: a brief description of intent and a link to my existing portfolio. Goal was to ship a visually cohesive, production-ready page that matches my existing aesthetic while solving a real information architecture problem — without opening Figma first. What followed was also an early lesson in how Claude handles instructions over a long session.

Tool used

Claude Sonnet

Type

Page design & IA

Time to first draft

~15 minutes

Outcome

Claude could not reliably extract exact color values or design tokens from the portfolio URL — the page had the right structure but colors were off. Once I defined a proper design system spec and fed it to Claude, alignment improved significantly. Later in the same session, instruction drift became a real problem: earlier rules quietly reverted as the conversation grew longer, creating a repetitive correction loop.

Key insights & challenges

Two lessons from one session. First: Claude approximates visual styles from URLs — define your design system as an explicit spec before asking it to match anything. Second: Claude has no persistent memory within long sessions. The fix is Project Instructions — a persistent system prompt that eliminates re-establishing ground rules each time. Every instruction needs to be written as if it might be the only one Claude ever reads.

Tools in rotation

Introduced only when needed

Reasoning + Critique

Claude

Design critique, research synthesis, prompt strategy, content generation, and planning. The thinking layer for every session.

Building + Code

Claude Code

Component and page generation in VS Code. The build step comes before Figma — code first, canvas second. Skills taught here compound across every future session.

Hosting + Deploy

Vercel

Every session ends with a live deploy. Vercel connects to GitHub and ships in seconds — no build step, no friction between building and seeing it live.

Design Intervention

Figma

Everything starts in Claude. When Claude falls short on visual decisions — layout, interaction, feel — Figma is where I step in, draft what I actually want, and hand it back via MCP.

UI Iteration — Queued

Magic Patterns

Will be introduced for variant exploration when the design system has a stable enough foundation to stress-test against alternatives.

Analytics — Queued

Amplitude

Will be introduced once there's a live product to measure. Analytics without a product is noise.