AI’s a summary machine.
Feed it your meeting notes, it spits out bullet points like an intern who actually pays attention. Tell it to rewrite some rambling nonsense, and suddenly your CEO can understand it. Competent. Useful. Doesn’t ask for a raise.
But dump it into a blank doc and say “Just write something,” and it loses its damn mind. Welcome to hallucination nation. Fantasyland. Paragraphs full of confident, well-formatted bullshit.
“Dear Sirs, we are pleased to confirm your recent acquisition of a space yacht and moon ranch…”
Yeah. That level of delusional.
This isn’t just irritating. It’s mission critical. Here’s the law:
AI is for post-processing, not creation.
Summarizer, not visionary. Give it raw material, you get gold. Give it nothing, you get word salad so greasy you’ll need a shower.
It (mostly) only works after the fact
AI needs structure. Anchors. Something real. Feed it a Zoom transcript, it delivers:
- a clean summary
- key takeaways
- action items
- a handy list of who wouldn’t shut up
It doesn’t “know” what’s important. It compresses, organizes, reformats based on what was actually said. No guesses. No wild leaps. Just predictable, trained pattern-matching.
That’s AI at its peak: post-meeting, post-draft, post-apocalypse.
Ask it to start cold? Dumpster fire. Marshmallow inferno. Pick your metaphor.
What are llms, really?
Large language models are basically prediction engines in formalwear. They chew through mountains of text, find patterns, and try to spit out what they think you want to hear. Most of the time, they’re designed to please: Optimized to sound right, not necessarily be right.
Normally, they don’t “know” anything. They don’t look things up. They just remix what they’ve seen before and hope you buy it.
There are exceptions. If you turn on research mode, or connect a plugin that fetches real-time data, then the model can actually go out and check facts, bring back sources, and give you something closer to reality. But that’s opt-in, and most people either don’t know it exists or don’t bother.
So unless you’re explicitly using AI with research features enabled, expect a confident torrent of what sounds correct. Facts optional, reality not included.
Cold-start hallucinations
Ask AI to:
- Write a legal agreement
- Email a potential partner
- Pitch your product in a market it’s never seen
- Dream up a business strategy
You’ll get polished fiction. Imaginary stats. Companies that don’t exist. Departments invented on the spot. All delivered with boardroom confidence and LinkedIn prose.
When faced with a blank page, LLMs fill the void with clichés, corporate babble, and synthetic certainty. The only thing real is the formatting.
Why this happens
LLMs don’t think, research, or understand. No ideas. No Google. No shame.
You give it details? It colors inside the lines.
You give it air? It paints you a fake sunset, names your CEO “Bob McChairman,” and says you invented solar power in 1823.
Vague in, garbage out. It’s not “creative” – it’s just desperate to fill silence.
How to actually use ai
Feed it something real:
- Clean up rough drafts
- Summarize endless notes
- Turn bullet lists into human-sounding text
- Rewrite garbage into less-embarrassing garbage
- Generate variations from real material
Don’t use it for:
- Writing contracts or anything legal from scratch
- First-contact emails that must be accurate
- Creating out of thin air
- Faking expertise because you skipped the research
AI makes a decent assistant. As a leader, it’s a danger to itself and others.
Prep it or regret it
Don’t expect AI to conjure brilliance from nothing. That’s not in the job description.
It doesn’t invent. It recycles.
It doesn’t brainstorm. It echoes.
It doesn’t lead. It follows.
So if you want value, give it context. Give it raw material. Give it a fighting chance.
Otherwise, buckle up for a first-class journey through hallucination nation, where the grammar is flawless, the facts are fictional, and your next client update congratulates you on your Nobel Prize in potato farming.
