Trendslop
- Slop
- Practitioner slang
Trendslop is AI-written strategy, analysis, or advice that falls back on popular consensus instead of your particular situation. It sounds smart because it repeats what many people are already saying.
When a request supplies little case-specific evidence, a model can produce a familiar strategy pattern instead of reasoning from your situation. Adding details helps only if they constrain the recommendation; quoting them in the opening does not establish that they shaped the advice.
Where you’ll meet it
In a planning meeting, a colleague shares an AI-written growth plan that calls for a referral program with 10% off, LinkedIn posts three times a week, and a monthly webinar. Each step could start on Monday. None mentions your customers, your budget, or the two competitors that won accounts from you last quarter.
What to do
Before anyone starts on it, rerun the request with relevant customer evidence, budget constraints, and what you know about the accounts you lost. Ask how each option follows from those facts, what it gives up, and what evidence would make it unsuitable.
Easy to mix up
Workslop leaves its recipient hidden cleanup behind a finished-looking handoff. Trendslop gives advice that would read the same for anyone, because it follows popular opinion instead of your situation's evidence.
Check yourself
You give an AI your résumé and ask how to earn a promotion this year. It opens with your job title and your three years in it, then recommends networking, finding a mentor, and leading a visible project. What does this demonstrate about its use of your résumé?
Go deeperPreference training can reduce variety without settling whether advice fits
Preference training uses ratings to favor some kinds of answers. Robert Kirk and colleagues' 2023 experiments found lower output diversity than training on examples alone. A severe narrowing is called “mode collapse,” but one generic recommendation does not establish that this mechanism caused it.
Common advice can be useful when the evidence supports applying it to your case. Asking for bolder ideas does not establish that fit either: a contrarian answer can reverse the usual advice without engaging with your constraints.