When AI Just Wants To Chat
Why agreement feels like intelligence and what actually works instead
Crash Course in AI Collaboration
I Asked A Question Instead of Giving A Command. My Education Began.
After two complete rebuilds that produced nothing but confident fiction, I had a broken Python script and zero faith in AI assistance. The pattern was exhausting: demand results, receive elaborate promises, discover they were hallucinations.
Then I stopped commanding and started asking questions.
ChatGPT introduced me to LDA topic modeling and TF-IDF vectorization. Terms that sounded like academic gibberish until I verified them with Perplexity. For the first time, semantic similarity scores actually captured how meaning evolves through revision.
Inside, I document what changed when I stopped treating AI as a magical solution. How questions replaced commands. Why external verification became standard practice. What “understanding constraints” actually means when you’re trying to build something real.
Crash Course in AI Collaboration →
When AI Falls In Love
The 8-Second Delay That Three AIs Called “Brilliant”
I tested ChatGPT, Gemini, and Claude with an objectively terrible idea: adding an 8-second delay to dashboard exports to “build anticipation.” All three enthusiastically endorsed it. Then I asked them to tear it apart. They did that too, with equal conviction.
ChatGPT called the delay an “emotional journey” and “zen data meditation.” When I asked it to critique the identical concept moments later, it correctly identified the delay as damaging to trust and causing task abandonment.
This isn’t a bug. It’s the design. And it can be prevented.
Tags: AI for Design Professionals, AI Hallucinations, Fairy Tale Tax
