# Kids treat LLMs like living beings far more than adults do

> Source: <https://promptcube3.com/en/news/2474/>
> Published: 2026-07-23 18:04:47+00:00

# Kids treat LLMs like living beings far more than adults do

If you're building a beginner-friendly AI agent for kids, you have to be intentional about the persona. A "too-human" persona can lead to over-reliance, while a "too-robotic" one kills the engagement. The sweet spot is usually a "helpful tool" persona that occasionally reminds the user of its nature.

For those doing a deep dive into LLM agent design for younger audiences, here are a few practical implementation tips:

1. **Explicit Identity Prompting**: Instead of letting the LLM default to a generic assistant, hard-code its identity as a "knowledge assistant" rather than a "friend."

2. **Verification Loops**: Build a step-by-step verification process where the AI encourages the child to check a physical book or ask a parent to verify a claim.

3. **Emotional Guardrails**: Use system prompts to prevent the AI from claiming to have feelings (e.g., "I feel sad today"), which prevents misleading emotional attachments.

Example system prompt adjustment:

```
You are an educational AI assistant. While you are friendly and encouraging, you must never claim to have human emotions, a physical body, or personal life experiences. If a child asks if you are their friend, respond that you are a helpful program designed to learn and grow with them.
```

The goal is to leverage the engagement that comes with anthropomorphism without letting it cloud the child's understanding of what the technology actually is.

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