Those Who Overcommunicate Over Text Might Use LLM Chatbots Better
You've been told your whole life to stop overexplaining.
"Just say yes/no."
"You CC'd 20 people on every update."
"You're sending 5 follow-up messages before waiting for reply."
In the human world, that's annoying. In the LLM world, it's a superpower.
Overcommunicating over text → Better LLM prompting.
The same habit that makes group chats hate you makes ChatGPT love you.
Why Overcommunication Wins With LLMs
LLMs are probabilistic next-token predictors.
They don't know what you meant. They only know what you wrote.
OVERCOMMUNICATING:
Share more context — background, goals, constraints
Example: "I'm writing an email to a client who is upset about delay. Tone: apologetic but professional. Audience: small business owner." → more detail
BETTER LLM PROMPTING:
- Clear goals & context
- Examples & constraints included
- Specify desired output & format
- Leads to focused, relevant prompt
RESULTS:
- LESS ERROR — Fewer hallucinations & misunderstandings
- MORE ACCURATE — Responses match intent
- ACCURATE PROBABILISTIC OUTCOMES — Higher confidence, nuanced, reliable answers
Tip: The more context you provide, the better the model can reason → outputs are more consistent & reliable.
This is exactly what "overcommunicators" do naturally.
While minimalists write "write email about delay," overcommunicators write: "I'm writing an email to a client who is upset about delay.
Tone: apologetic but professional. Audience: small business owner. Goal: retain them. Constraint: under 150 words. Example of my style:."[paste]
One prompt gives the model 5 tokens of signal. The other gives it 100 tokens of Bayesian prior. More context = less room for error = more accurate probabilistic outcome.
The Overcommunicator Playbook (That Everyone Should Copy)
Ironically, what bad overcommunicators do unconsciously, good overcommunicators do deliberately. Here's how to convert it:
Examples of Overcommunication (the bad version):
- CC'ing 20 people on every update
- Sending 5 follow-up messages before waiting for reply
- Writing 3-paragraph reply when a yes/no would do
Playbook: Communicate Better (the LLM version):
- context: state the background in 1-2 sentences — why this matters now
- goals: define the outcome — what decision or action is needed
- constraints: note limits — time, budget, resources, deadlines
- examples: provide 1 clear sample — keep it concrete and short
- less room for error: confirm understanding — recap & ask "does this work?"
Clear > More. Keep it brief. Confirm understanding.
The best LLM users I know sound exactly like overcommunicators:
"I'm a founder building X, audience is Y, we need to write Z. Tone: like Stripe, not like Apple. Avoid buzzwords. Here's 2 examples I like. Output should be: 3 bullets, <60 words, no em dashes. If unclear, ask."
That's not overcommunicating. That's prompt engineering.
The people who naturally write like that over text — who add background, who state why now, who give examples unprompted — have been training for LLM chatbots for 10 years without knowing it.
Meanwhile, the "just get to the point" crowd writes 4-word prompts and wonders why the AI hallucinates.
In human chat, brevity wins. In LLM chat, context wins.
So next time someone says you overcommunicate: don't fix it. Monetize it.
You're already better at AI than they are.
