This wasn’t a talk. It was a live breakdown of how AI can be influenced, shaped, and quietly manipulated.
I pulled back the curtain on how Large Language Models actually “think”:
where they get their data, how they prioritize information, and how repetition, structure, and authority signals can bend their outputs.
We explored:
→ How to inject new information into AI ecosystems
→ How to modify or overwrite existing narratives
→ How to make AI repeat what you want
→ The hidden impact of backlinks, content distribution, and data footprints
→ Why most people misunderstand how LLMs process truth
No theory. Only case studies.
Real experiments, reproducible methods, and insights you can test yourself.
From reshaping facts… to pushing completely new concepts like Aquaponey into AI responses — this session showed one thing: