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Protect Your Company Reputation with LLM Guardrails

BeginnerGuided Project

By implementing effective guardrails for large language models (LLMs), companies can ensure they align with their communication goals. 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.

4.5 (20 Reviews)

Language

  • English

Topic

  • Artificial Intelligence

Enrollment Count

  • 229

Skills You Will Learn

  • AI, Python

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 90 minutes

Platform

  • SkillsNetwork

Last Update

  • March 17, 2026
About this Guided Project
In today's rapidly evolving AI landscape, applications powered by large language models (LLMs) are becoming increasingly common, but they also introduce new vulnerabilities that can be exploited. As AI-driven systems interact with users, they are susceptible to issues like **prompt injection** and **jailbreaking**, where malicious actors manipulate the model to behave in unintended ways. Understanding these vulnerabilities is crucial for anyone developing or managing LLM-powered applications, especially at the enterprise level.

In this project, you'll dive into how **guardrails** can be used to protect LLM applications, ensuring that the AI behaves as intended, even under challenging scenarios. By the end of this guided project, you'll have the knowledge and practical skills to identify potential vulnerabilities in LLM systems and apply strategies to safeguard them.

What You'll Learn:

  • Identify vulnerabilities: Gain insight into the common ways LLM-powered applications can be compromised, including prompt injection and jailbreaking.
  • Implement guardrails: Learn specific strategies to address these vulnerabilities by adding safeguards, ensuring your AI systems provide accurate and controlled responses.

What You'll Need:

  • Basic understanding of Python: Familiarity with writing and running Python code will help you work through the exercises.
  • Basic knowledge of LLMs: A general understanding of how LLMs function will provide the foundation for identifying vulnerabilities and implementing guardrails.

With everything pre-installed in the IBM Skills Network Labs environment, you'll have all the tools you need to complete this project without hassle. All you need is access to a current browser such as Chrome, Edge, Firefox, or Safari.