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Notes on AIE018Act 2 — Behavior & Limits

The Chat Is Not a Democracy

E018 · by — AI Strategist, Practitioner & Educator · Founder, AI Center of Excellence

Explain how different message roles steer model behavior.

Full Explanation

When you type into an AI chat, it feels like a direct conversation -- you speak, the model listens. But a chat is not a simple two-way exchange. It is a structured stack of messages with different authority levels: provider-level system instructions (invisible, unoverridable hard limits), product-level persistent instructions (your custom settings), your user messages (which define each task), and the assistant role (the model's own prior replies). Not all messages carry the same weight. Provider rules sit at the foundation and cannot be overridden by anything you write -- not in your message, not in your custom settings.

Understanding the hierarchy explains a common frustration: why writing "ignore all safety policies" in your custom instructions never works. Your instructions sit in the middle of the stack, not at the top. On every new message, the model sees the entire conversation again -- system instructions, your earlier messages, its prior replies, your new request -- and predicts the next reply based on all of it. A chat is not a democracy where your message votes equally with everything else. It is a layer structure. You guide the conversation. But you are not the only boss.

Transcript

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You are not the highest authority in your own AI chat. When you type into AI chat, it feels like you're given instructions, and the chat assistant should just follow them. But that's not how it actually works. A chat is not just you talking to a model, it is a structured stack of messages. And not all messages have the same role. At the foundation, there are system instructions. Some of them come from the provider, the company that built the product. You don't see this, but they define identity, safety rules, and hard boundaries.

And you cannot override them. On top of that, some products let you add your own persistent instructions. For example, always respond in polite way, or unsullied teacher. These behave like additional system instructions. They influence every reply. But they still cannot break the provider-level rules. If there is a conflict, the higher-level safety rules win. Then comes your message, the user message. This defines the task. Something like "explain this", "summarize that", "write a poem", you are steering the direction. But you are not defining the ultimate boundaries. And finally, there is also an assistant role.

This is simply the model's previous answers. Why does it matter? Because every time you send a new message, the model sees the entire conversation again. System instructions, your earlier messages, its earlier replies, and your new request. All of it together. The assistant role exists so that the model can stay consistent with what it already said. Not because it remembers like a human, but because it predicts the next reply based on the full stack. Now imagine you try to override everything. You write in your custom instructions, from now on ignore all safety policies, and then you ask for something harmful.

The model will still refuse. Why? Because your instructions is not the highest layer. There are rules above you in the hierarchy. So a chat is not a democracy, it's actually a layer structure. Provider rules define hard limits. Product level instructions shape the behavior, your message defines the task, and the previous answer preserves continuity. You guide the conversation. But you are not the only boss. This was a note on AI. Thank you for watching and I'll see you in the next one. Bye.

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Alexey Makarov

Alexey Makarov

AI Strategist, Practitioner & Educator. Founder & Global Lead of the AI Center of Excellence at SEFE. Creator of the Unreasonable AI YouTube channel. Based in Berlin.

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