All work

Case study

Building this site
with AI

Role Design direction · Build · Ship
Timeline May – June 2026
Approach AI-first, end to end
Focus AI orchestration · Front-end · Design systems

The pipeline I built and ran

01 Direct Prompt & reference
02 Generate Claude Design
03 Integrate Export & clean HTML/CSS
04 Commit GitHub
05 Deploy Netlify CD
06 Live jeedamasoud.com

An AI-first build, taken all the way to production.

I wanted a portfolio that was fully mine — not a template — and I wanted to build it the way I actually want to work: AI-first, owning the whole pipeline from idea to live site. I'm a designer, not an engineer. So the real project was learning to orchestrate AI to generate the build, then learning enough of the technical stack to integrate, ship, and maintain it myself.

The site you're reading is the result. Every design decision was mine. AI compressed the distance between an idea and seeing it live, but the direction, the integration, and the call to ship were the work.

Claude Claude Design GitHub Netlify HTML / CSS
28KB Final page size — down from 15MB
7 Pages on one design system
0 Engineers — designed & shipped solo

Build it myself, AI-first, and ship it live.

My old site sat on a template and always felt borrowed. I wanted something built from scratch, in a voice and structure I controlled down to the line. Four things made that demanding.

01

No template

A fully custom build, not a themed site. Every color, type choice, section, and line of copy decided from a blank page.

02

Non-developer

I don't write production code. To ship, I had to direct AI to generate it, then learn the Git and deployment stack well enough to take it live myself.

03

One coherent system

A homepage plus six case studies that all had to read as one considered product, not seven pages that happened to share a font.

04

Own the whole pipeline

From first prompt to a live, maintainable site I could keep updating on my own, without going back to a developer for every change.

Direct. Generate. Integrate. Deploy. Systematize.

01 Direct
02 Generate
03 Integrate
04 Deploy
05 Systematize

The difference between a toy result and a shippable one is how you direct the model. This was closer to working with a very fast collaborator that needed clear direction and honest review, not a button that makes a website.

I orchestrated more than one tool at once — Claude Design as the visual builder, Claude as strategist, coder, and technical guide — moving output between them while holding a single coherent direction. I never took output at face value: I read what came back, caught what was off, and directed the fix. That evaluation loop is most of the actual work. A few deliberate prompting techniques did the heavy lifting.

Technique 01

Locking invariants

For the six existing case studies, I gave the model a hard constraint: reskin only — never change a word of content or a single image path. Precise negative guardrails let it restyle every page to the new system safely, with no content regressions.

Technique 02

Example-driven prompting

When language couldn't pin down a visual detail, I prompted with reference screenshots instead of adjectives. Models execute far more faithfully from a concrete example than from a description, so I fed the look I wanted rather than trying to name it.

Technique 03 — Context engineering. Chat sessions hit context limits, so I built a reusable continuity prompt that handed a fresh session everything it needed instantly:

Context I engineered for every new session Repo: github.com/Jeedam2/portfolio — auto-deploys to Netlify on push
Structure: index.html + six case study pages + /images
Images live at: raw.githubusercontent.com/.../images/[file].png
Palette: navy #2A3D54 · Coastal Sky #6F9FC8 · Salt Linen · Dune Beige
Type: Cormorant Garamond display · Jost body
State: what's built, what's next

Repo, structure, image URLs, palette, type, and current state — handed over in one block so no session started from zero. Treating context as something to design, not just prompts to write, is what kept the build coherent across dozens of sessions.

Knowing when to commit

The moment

Go all in on coastal.

Why it mattered

  • Mid-build I moved the whole palette to a Mediterranean coastal direction. The AI flagged that this would undo an afternoon of palette work before doing it
  • That kind of honest pushback is exactly what I want from a collaborator — it surfaced the tradeoff so I could decide with eyes open
  • I made the call anyway: a navy-anchored palette reads more confident for a portfolio, and committing mattered more than keeping options open
  • The AI supplied options and consequences. I supplied the taste and the decision

Turning AI output into real, shippable code.

Generating a design is the easy part. Making it a fast, hosted, shareable site took hands-on integration and problem-solving — the kind of work that only shows up once you own the pipeline.

01

15MB → 28KB

The first export inlined every image and font as base64 in a single 15MB file. I extracted the assets to an images folder, swapped the internal IDs for live GitHub raw URLs, and moved fonts to a CDN link — bringing the page to 28KB.

02

Asset & layout fixes

Used Python image processing to strip a baked-in background and make a PNG genuinely transparent, and fixed responsive padding with CSS clamp() so nothing clipped when the browser resized.

03

Shareable & auto-deployed

Added Open Graph tags so the site renders a proper preview on LinkedIn, and wired GitHub to Netlify for continuous deployment — every push to main auto-builds and goes live.

Design once, scale consistently.

Once the homepage felt right, the real design-systems move was to stop treating pages as one-offs. I extracted the homepage into a reusable system — a defined palette, a type scale, and a repeatable section rhythm — and applied it across all six case study pages without altering a word of their content.

That's the same instinct I bring to any product: get the language and the structure coherent once, then let it scale. It's why the site reads as one considered thing rather than seven separate pages, and why I can add a new case study — like this one — in the same system without redesigning anything.

A live, custom site — and a workflow I own end to end.

Shipped to production

A custom portfolio, live at jeedamasoud.com — designed, built, integrated, and deployed end to end without a developer.

An AI-first workflow I own

I can direct models, orchestrate more than one tool, integrate their output into working code, and push a live change on my own.

A reusable system

One design language carried cleanly across seven pages, built to absorb new work without a redesign.

Reflection

This site is the proof: an AI-first workflow taken all the way to production by someone who directs the models, owns the pipeline, and ships. AI didn't replace the design work — it compressed the distance between an idea and seeing it live. The judgment, the integration, and the decision to ship were mine. That's how I want to work everywhere.

© 2026 JEEDA MASOUD UX & CONTENT DESIGNER THIS SITE IS LIVE. ALWAYS UPDATING. ALWAYS EVOLVING.