Marketing

Teaching AI with feedback to improve creative ideas

AI logs approvals, rejections, and reasons in a feedback database so future ad concepts get smarter over time and reflect what has worked before.

Why the human is still essential here

The system only improves because Ole explains why past ads won, what context mattered, and which new ideas feel too gimmicky or off-brand.

How people use this

Approved vs rejected concept log

Teams record which ad ideas were accepted or rejected and why, giving AI a structured memory of brand preferences and past learnings.

Airtable / Notion AI

Brand-taste custom assistant

A custom AI workspace is loaded with examples of winning ads, failed concepts, and review notes so future brainstorming better matches the brand.

ChatGPT Custom GPTs / Claude Projects

Automated review feedback capture

AI workflow automation pushes meeting notes and creative review comments into a feedback database that updates future prompting and ideation.

Zapier / Airtable + OpenAI

Need Help Implementing AI in Your Organization?

I help companies navigate AI adoption -- from strategy to production. Whether you are building your first LLM-powered feature or scaling an agentic system, I can help you get it right.

LLM Orchestration

Design and build LLM-powered products and agentic systems

AI Strategy

Go from idea to production with a clear implementation roadmap

Compliance & Safety

Build AI with human-in-the-loop in regulated environments

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Community stories (1)

YouTube

How I Use AI for Better Ad Concepts (Without Losing the Human Touch)

And in this video, I'm going to show you an amazing system that I've implemented to be able to do a lot of the heavy work and the heavy mental load that is required to come up with great ad ideas. Outsource that part to AI, but leave the one part where is actually required that I have my human input, my human taste to actually turn all the research and all the data into good ideas.

Ole StrandFounder of a boutique Meta Ads agency

Apr 7, 2026