Artificial Intelligence for Marketing Departments.
Most teams use ChatGPT as a faster writer. That is only one prompt. I build the rest: integrated AI workflows that connect research, creative, distribution, and measurement — so a lean marketing team can move like a larger one.
Meta Technology Partner · Technical Marketing Lead · Ex-Growth Lead for B2B SaaS · Shipped products in public since 2021.
What “integrated AI workflows” actually means
Read the playbook →ChatGPT is a single prompt. A marketing department needs a chain: ideas become copy, copy becomes campaigns, campaigns become data, and data becomes the next idea. I connect those steps with code.
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01 — Research that feeds strategy
AI-driven market mapping, competitor teardowns, and audience insight pipelines that turn scattered signals into briefs you can act on.
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02 — Creative at scale
From one brief to hundreds of variants: ads, landing copy, email sequences, and WhatsApp messages — all on-brand and grounded in customer language.
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03 — Distribution without manual work
Automated publishing, ad ops, CRM updates, and WhatsApp outbound that keep campaigns moving while the team sleeps.
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04 — Measurement that answers back
Dashboards and attribution models that report ROI, CAC, and funnel drop-off automatically — so budget decisions stop being guesses.
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Why this beats isolated AI tools
A copy generator gives you speed. An integrated workflow gives you compounding speed: every campaign teaches the next one, every report improves the next brief, and every channel reinforces the others. That is the difference between using AI and building an AI-powered marketing department.
Open Source
All projects →A self-hosted Streamlit dashboard that gives marketing teams real-time campaign visibility without waiting for BI team or expensive tools.
PythonStreamlitpandasplotlyPython scripts that replace 3 hours of manual weekly reporting with a 90-second automated process.
PythonpandasopenpyxlGoogle Sheets API
Writing
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WHYRANK: Why This Keyword Hit #1 on SERP — and Why That Is Not an Accident
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Technology Is Not the Business. Demand Is.
Why I stopped chasing AI tools and started chasing real demand — and what changed when I saw technology as a delivery layer, not a product.
About
More →I spent years running growth and performance marketing for B2B SaaS and marketplace startups — drowning in spreadsheets, manually stitching reports, and watching budget decisions happen without data. Then I learned Python. Not to become a software engineer, but to remove the manual work that was slowing the team down.
That led to a different way of running marketing: AI workflows that connect research, content, ads, CRM, and analytics — so a small department can plan, execute, and measure like a much larger one. I have shipped products in public since 2021, from an SEO automation tool to a WhatsApp-first CRM, and I write about the workflows I actually use.
Background: Sales & marketing operations, Indonesia. Comfortable across the full stack of a modern marketing department: strategy, paid media, data, automation, and AI product engineering. Building for marketing teams that want practical results, not theory.