Prevent Failures and Stay On-Message with LLM Guardrails
Implement effective guardrails for large language models (LLMs) to ensure they align with your company's communication goals in this hands-on lab. You'll learn how to establish mechanisms that keep AI interactions relevant and on-topic, prevent the generation of inappropriate content, and uphold the professional and ethical standards of your organization. By mastering these strategies, you can enhance your company's reputation by maintaining control over AI-generated content.

Language
- English
Topic
- Artificial Intelligence
Enrollment Count
- 58
Skills You Will Learn
- Artificial Intelligence, LLM, Agentic AI, AI Agents, AI Governance, AI Alignment
Offered By
- IBMSkillsNetwork
Estimated Effort
- 90 minutes
Platform
- SkillsNetwork
Last Update
- November 12, 2025
This project is designed to help you take control of how AI communicates on behalf of your organization. You will learn how to guide and shape the output of language models so that it stays relevant, professional, and aligned with your communication goals. Whether you are a data scientist, product owner, or content strategist, this project will give you the tools to ensure that AI-generated content reflects your brand’s voice and standards.
A Look at the Project Ahead
- Create and apply strategies that ensure AI-generated content remains consistent with your company’s communication goals and professional tone.
- Implement safeguards that detect and prevent the generation of content that is off-topic or inappropriate, helping to protect your organization’s reputation and uphold ethical standards.
What You'll Need

Language
- English
Topic
- Artificial Intelligence
Enrollment Count
- 58
Skills You Will Learn
- Artificial Intelligence, LLM, Agentic AI, AI Agents, AI Governance, AI Alignment
Offered By
- IBMSkillsNetwork
Estimated Effort
- 90 minutes
Platform
- SkillsNetwork
Last Update
- November 12, 2025
Instructors
Wojciech "Victor" Fulmyk
Data Scientist at IBM
Wojciech "Victor" Fulmyk is a Data Scientist and AI Engineer on IBM’s Skills Network team, where he focuses on helping learners build expertise in data science, artificial intelligence, and machine learning. He is also a Kaggle competition expert, currently ranked in the top 3% globally among competition participants. An economist by training, he applies his knowledge of statistics and econometrics to bring a distinctive perspective to AI and ML—one that considers both technical depth and broader socioeconomic implications.
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