Hallucinations
Hallucinations
AI models sometimes generate information that sounds completely plausible but is factually wrong. This is called a hallucination.
It happens because the model is optimized to produce fluent, confident text. It is not optimized to check whether that text is true.
What hallucinations look like
- Citing a source that does not exist (a fake article, a non-existent website)
- Inventing a statistic or a number
- Describing a product feature that was never released
- Mixing up details between two similar things
The tricky part: hallucinations are delivered with the same confidence as correct information. The model does not flag its own mistakes.
How to spot one
Watch for these signals:
- Claude mentions a specific number, date, or name that you do not recognize and cannot verify
- A cited source sounds plausible but returns no results when you search for it
- The answer is exactly what you wanted to hear, with no caveats
- Details are broadly correct but something specific feels off
When in doubt, ask Claude directly:
“How confident are you in this? What sources are you drawing from?”
A well-designed model will honestly indicate what it is and is not certain about. Claude will typically say when it is working from general knowledge versus something specific.
Where this matters for Adam Bike
Hallucinations become a problem when you use AI output without checking it. Scenarios to watch:
- Product specifications — if you ask Claude to describe a Specialized Allez Sprint’s weight or geometry, verify the numbers on the brand’s official site before publishing
- Pricing — Claude does not know your current prices. Never publish AI-generated prices without checking
- Legal or warranty language — always have a human review anything that makes claims or promises
- Competitor information — Claude may confuse details between similar brands
For showroom content, social captions, and internal communication, hallucinations are low-risk. For anything customer-facing that involves facts or specs, verify first.
How to protect yourself
Verify critical facts. Especially numbers, dates, model names, and product specifications. A quick check on the brand’s website takes 30 seconds.
Ask for sources. If Claude cites something, check whether it actually exists.
Be suspicious of extreme certainty. If an answer sounds too perfect, double-check it.
Use AI as a starting point. Let Claude draft the structure and language. Then add the facts yourself from verified sources.
The good news
Hallucinations are becoming less common with each model generation. Claude is specifically designed to say “I’m not sure” rather than guess. It is more transparent about uncertainty than most AI tools.
And for the work Adam Bike does most often — writing captions, drafting emails, brainstorming content ideas — hallucinations are rarely a problem. You are providing the facts; Claude is providing the language.