Chaos engineering is essential for building resilient systems, but scaling its practices often requires specialized expertise that can create bottlenecks within organizations. To address this, Harness has introduced the AI Reliability Agent, an experimental feature designed to automate chaos engineering processes using artificial intelligence. This agent provides experiment recommendations, remediation guidance, and is accessible to teams at any skill level, specifically working with Kubernetes infrastructures. By automating decision-making processes, the AI Reliability Agent helps overcome the challenges associated with expanding chaos engineering practices, making it easier for teams to perform effective experiments and implement fixes. It integrates seamlessly into existing Harness workflows and provides intelligent guidance based on environment monitoring data to recommend new chaos experiments with pre-tuned parameters. Although automation capabilities are powerful, it is crucial to validate AI-generated fix recommendations with human experts to ensure they align with specific systems and business requirements. The integration of AI into chaos engineering workflows without requiring new tools or processes makes it easier for teams to adopt resilience testing, offering a practical path for organizations to scale their resilience practices effectively.