AI Engineer & Architect. I designed the personalization architecture for the world's largest jewelry company and automated claims handling for the leading insurance company in the Nordics
This playbook demonstrates how to build a modern Python data pipeline that extracts Meta Ads data to BigQuery, eliminating CSV exports and creating the warehouse foundation needed to reconcile platform-reported conversions with actual revenue across Meta, GA4, and sales data from a CRM.
This playbook extends the Meta Ads automation with AI image composition. We'll add a single LangGraph node that transforms product photos into marketing creatives using Gemini's vision model, then feeds these composed images into the existing campaign workflow.
This playbook demonstrates how to identify ecommerce products (SKUs) that correlate with higher customer lifetime value using statistical models, and then utilize that data to optimize acquisition campaigns with mathematically justified bid adjustments.
In this playbook, we'll build a landing page performance analyzer that converts GA4 event data into conversion optimization strategies through intelligent SQL generation and AI-driven page-level insights
This playbook shows how to use LangGraph workflows to generate campaign configs from simple inputs. We'll build a system that transforms product descriptions into complete campaign strategies with audience segments and ad variations, while preserving human approval before execution.
This playbook shows how to use configuration-driven campaign matrices to automate Meta Ads at scale. We'll build a system that transforms campaign configs into complete ad variations with targeting, budgets, and creatives, eliminating manual setup across dozens of ads.
