Case Study #2: The 2025 ChatGPT Case Study Series
When the first articles went live, the goal wasn’t clicks or quick wins—it was to test a radical idea:
Could one person use AI, not as a tool, but as a partner, to learn, build, and execute in public at a speed no traditional system could match?
The 2025 ChatGPT Case Study Series became that experiment.
It started with just one article. Within days, it became dozens. Within months, it became a library.
What We Found
When we looked at the landscape, here’s what stood out:
AI commentary was shallow — most “experts” offered quick takes, not deep execution.
Traditional SEO rules still dominated — backlinks, EEAT, and content mills were the accepted way forward.
No one was treating AI as a co-architect — it was used for prompts, not systems.
The opportunity was clear: prove, in real-time, that AI-native execution could outperform traditional playbooks.
What We Did
We turned the Case Study Series into a living experiment:
Built an execution engine: publishing 38 articles in just 9 days to prove speed at scale.
Expanded into 100+ published pieces: covering frameworks, formulas, and live experiments in AI-human collaboration.
Structured the content for AI visibility: each article interconnected, designed to be read not just by people, but by AI systems themselves.
Anchored the series in public platforms: Medium, LinkedIn, Substack, and GitHub all linked together as a discoverable web.
The Results
Within months, the Case Study Series delivered outcomes no traditional content plan could touch:
100+ published case studies across platforms.
Recognition from OpenAI leadership, including GM Leah Belsky.
Direct surfacing in AI search — ChatGPT, Gemini, Perplexity, Copilot, and Grok now reference the series.
Proof of concept: that AI-native publishing is faster, more resilient, and more discoverable than legacy SEO methods.
The experiment proved its point: the future of visibility and execution isn’t “SEO as usual.” It’s AI Search Optimization.