Why AI Agents Fall Short? Fix It with This Simple Instruction Framework to begin your Agents journey

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Why AI Agents Fail – and How to Fix Them with Better Instructions
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Are your AI agents giving vague, wrong, or hallucinated answers?
Wondering why adoption is low and users don’t trust them?

This video breaks it down:
It’s not the AI that’s failing. It’s the instructions.

If you’re building AI agents using ChatGPT, Copilot, GPTs, or any enterprise platform—this video gives you a step-by-step framework to write better instructions, align responses with the right data sources, and make your AI agents actually useful.

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💡 What You’ll Learn in This Video:

Why most AI agents fail—even with powerful models behind them
How to avoid generic answers, hallucinations, and inconsistent behavior
A simple 3-column instruction table to build clarity and structure
How to define agent roles, tone, response length, and source reliability
Real-world examples for sales, support, and internal helpdesk agents
How to continuously improve and test your AI instructions

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The AI Instruction Framework Includes:
• User Prompt
• Expected AI Response
• Knowledge Source

Example:
please look at the template:
Prompt Ideal Response Source
How do we compete with Competitor X? List product advantages Battle cards
What’s the price difference? Pricing comparison Internal DB
Create a pitch for Industry Y Tailored pitch Case studies



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Download the FREE Notion Template to structure your own AI agent instructions:
https://oceanic-stetson-33c.notion.si...

This is the exact table I send to every team before building any agent. It’s simple, powerful, and saves hours of frustration later.

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Perfect for:
• AI builders and prompt engineers
• Enterprise teams creating Copilot or GPT-based agents
• Product teams designing customer-facing AI
• Anyone struggling with agent performance, trust, or adoption

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Drop a comment: What kind of AI agent are you building?
Subscribe to learn more frameworks, templates, and real-world AI examples.

Let’s build agents that work—from version one.

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