Selected work

Systems built,
results shipped.

Every project here started as a manual process. Each one now runs itself — in production at Wego, daily. Built with n8n, Claude, and a bias for what’s measurable.

AI Operations★ Flagship

Live-Blog WordPress Plugin

Built in a weekend during the US–Iran travel crisis — a custom GPT wrote the PRD, Claude wrote the plugin in one session. Three production live blogs run on it today; the MENA travel-disruption page held #1 on Wego EN and AR for 3+ months.

WordPressClaude AICustom GPTn8nEN + AR
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EN sessions846,000
combined EN + AR~1,000,000
rank held#1 · 3+ months
build timeone weekend
SEO & Growth

Organic Growth Sprint

Flat traffic, no signal on what to prioritise. Connected GSC + GA4 into a daily n8n pipeline surfacing high-impression / low-CTR pages, briefed by Claude — one cluster, one owner, no paid media.

+230%sessions21,100+weekly peak10 wkssprint
GSC APIGA4 APIClaude AIn8n
Read case study →
Content Automation

Bilingual CMS Pipeline

A Claude-driven publishing skill that drafts EN + AR variants from one brief and writes straight into Prismic’s slice schema — the real structured model, not a flat blob.

30+pages / runEN+ARone trigger0manual steps
n8nClaude AIPrismic CMS
Read case study →
AI Operations

Airline Bulk Update System

Updating schedules, routes and copy for 34 airlines used to be 1–2 hours of manual WordPress editing per cycle. Now: structured sheet → Python transform → parallel REST pushes, with error logging and a Slack digest.

34airlines / run~10 minwas 1–2 hrs0data-entry errors
Pythonn8nWordPress REST API
Localisation

App Store Screenshot Automation

One master Figma file as the single source of truth: Claude adapts tone and phrasing per market, Figma MCP writes localised copy back into each language frame, and the export pipeline delivers upload-ready assets for every store locale in one run.

1master fileeverystore locale1trigger
Figma MCPClaude AIElevenLabsn8n

Methodology

How I work.

Every automation follows the same four-step discipline — from finding the bottleneck to proving the outcome with a number.

01
Audit the bottleneck
Tasks taking 30+ minutes on a repeatable pattern. If a person does the same thing more than twice, there’s a system waiting to be built.
02
Architect the flow
Every step, API call and decision point mapped before a line is written. The n8n diagram comes first; implementation second.
03
Build and deploy
Everything runs in production. No demo environments. If it doesn’t run daily without supervision, it isn’t done.
04
Measure the delta
Before and after — sessions, publish times, error rates. The number is the proof, not the workflow screenshot.

Currently available

Open to AI automation lead, AI operations & content automation roles.

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