Most DM bots feel generic. Learn how to train brand voice, set guardrails, and write prompts that keep replies natural and on-brand.
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TL;DR
TL;DR
To make an AI chatbot for Instagram DMs sound human, you do not need more keywords. You need a brand voice spec the AI can follow every time:
If you set those once, your replies stop feeling generic fast.
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It almost always comes from one of these:
The AI writes paragraphs because nobody told it to keep messages short.
Without examples, the AI defaults to neutral customer-support voice.
It guesses, over-explains, or handles sensitive topics poorly.
It answers “price?” with a long intro instead of a direct, relevant response.
This is why “brand voice training” is not fluff. It’s operational.
Use these as a starting point, then tweak.
Pick 3 adjectives that describe how you speak in DMs:
Example rule
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This is the biggest lever.
Best default
Decide this once and you remove randomness.
These phrases instantly signal automation. Ban them.
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This keeps replies human and moving forward.
Template
“Got you. Quick question so I send the right thing: ___? Then I’ll ___.”
This alone makes keyword automation feel like a conversation.
These are written to be tool-agnostic. If you use Inrō, you can select these into your AI Agent instructions and add examples in the custom instructions and knowledge section.
Prompt
You are replying in Instagram DMs for [BRAND NAME].
Voice: [3 adjectives].
Rules:
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Prompt
Your goal is to move the conversation to the next step:
Prompt
Hand off to a human when:
When handing off:
Bad
“Thanks for reaching out. Our pricing options are available on our website…”
Good
“Yep. Quick question so I send the right option: are you looking for DIY or help implementing?”
Bad
“Here is the link below. Let me know if you have any questions.”
Good
“Sending it. Is this for you or for a client?”
Bad
“Please provide your order number and we will assist you further.”
Good
“Got it. What’s your order number or the email used at checkout?”
This is where brand risk lives, so write these once.
“Not 100% sure I got you. Do you mean A or B?”
“I don’t want to guess. Can you tell me which product / link / post you mean?”
“I’m sorry about that. I’m flagging this for our team now. What’s your order number so we can fix it fast?”
“I can’t help with that. If you need help with [supported topic], tell me what you’re looking for.”
The goal is not AI everywhere. It’s AI where it helps, humans where it matters.
AI handles
Humans handle
With Inrō, this is straightforward because you can run automations for inbound DMs and comment triggers, then use handoff to a human when the conversation hits a boundary.
This process beats endlessly tweaking keywords.
Keep messages short, ask one question, ban corporate phrases, and train with examples. Add safe fallbacks so the AI does not guess.
Use a written voice spec (tone, length, emoji policy), a do-not-say list, and 15–30 example replies. Review outputs weekly and update examples.
1 to 2 short sentences, one question max. If you need more, send multiple short messages.
Use AI for qualification and FAQs. Use humans for objections, negotiation, and emotional conversations.
Yes. Let keywords catch clear intents (“price”, “link”), and let AI handle variations and follow-ups. The voice rules and examples keep it natural.
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