Your AI is Missing This😬
You can't just give your AI instructions without proving the right layers of context.
Don't act surprised when your output doesn't sound like you or it's not the quality you expected.
Most business owners think "context" means writing a longer prompt or uploading one big document once. That's not a context layer, that's a one-time info dump that goes stale in a week. Real context is layered and it accumulates.
Here are a few things to consider when preparing context for your AI:
✅ Identity/standing context — your business, principles, who you are, your brand voice, your goals and misson, frameworks, your non-negotiables. This rarely changes. It's the foundation layer.
✅Operational context — what's happening right now. Active projects, current clients, this week's priorities. This decays fast and needs refreshing constantly, which is exactly the "conversational history" problem the report is describing.
✅ Decision history — the "why" behind past calls. Why you priced something a certain way, why you said no to a client type, what you tried before that didn't work. This is the layer almost nobody builds, and it's the one that stops an agent from re-suggesting something you already killed six months ago.
✅ Relationship/permission context — who's allowed to see what, who this agent is acting on behalf of.
This week, pick one AI tool you're relying on. Ask yourself what it actually knows about your business versus what it's guessing.
Are you giving your AI enough context and examples we're talking to it?👇🏿
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Nicole McCain AI
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Your AI is Missing This😬
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