Why This Infographic Matters
Working with large language models (LLMs) can be powerful — but also risky. Smooth, polished answers often sound right but aren’t accurate. Fake citations, subtle math errors, hidden biases, or code that isn’t production-ready can slip through unnoticed. That’s why we created the LLM Quality Control Checklist, a professional infographic that highlights the 8 most common pitfalls when working with AI and shows you how to avoid them.
The LLM Quality Control Infographic
This infographic covers:
- Fact vs. Fluency – Why confident wording can hide errors.
- Citation Mirage – How to spot fake authors and references.
- The Flattery Trap – Don’t confuse praise with accuracy.
- Storytelling Drift – Avoid long chats turning into fiction.
- Math Isn’t Their Superpower – Why you must re-check calculations.
- Not a Licensed Expert – Treat AI as educational, not professional advice.
- Bias Behind the Curtain – Recognize hidden dataset bias.
- AI Code Not Production-Ready – Always analyze, test, and review C#/.NET code before using it.
At the end, you’ll also find a field card you can print or save — a quick-reference guide to keep your AI work reliable.
How to Use This Checklist
- Treat AI like an intern, not an oracle — verify before trusting.
- Reset often when conversations drift or feel too “story-like.”
- Cross-check math and citations using trusted tools and databases.
- Test AI-generated code with Visual Studio analyzers, unit tests, and reviews before moving to production.
- Always seek multiple perspectives to balance out hidden bias.
Download and Share
This infographic is designed for developers, analysts, and business leaders who use LLMs and want to avoid costly mistakes. But feel free to share with family, friends, and coworkers.
Whether you’re building AI-powered apps in .NET and C# or simply experimenting with generative tools, the LLM Quality Control Checklist will help you stay grounded, accurate, and professional.
Download “Prompting 201: Smarter Use of LLMs” PROMPTING-201_08202025.pdf – Downloaded 12 times – 3.28 MBIf you find it useful, share this resource with your team or colleagues — and help promote responsible, effective AI adoption.