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Overview
This learning path is designed for developers who want to ensure that AI agents are reliable, transparent, and production-ready. It focuses on observability and evaluation strategies to monitor performance, debug issues, and build trust in agentic workflows on watsonx Orchestrate.
With this learning path, you are able to:
- Learn how to instrument AI agents on watsonx Orchestrate with Langfuse and IBM Telemetry to capture prompts, responses, latency, token usage, and success/failure rates for complete visibility and continuous monitoring.
- Understand how AgentOps principles apply to AI workflows, enabling real-time dashboards, A/B testing, and compliance monitoring for enterprise-grade deployments.
- Gain skills to set up structured evaluation frameworks that test and benchmark AI agents under real-world conditions and unpredictable scenarios.
- Explore techniques for measuring accuracy, tool selection correctness, and output reliability to improve agent performance over time.
- Learn how to record and analyze user interactions, or business-generated or synthesized user stories for continuous improvement and trust-building.
- Build end-to-end observability and evaluation pipelines that transform prototypes into dependable, production-ready AI assistants.
To get hands-on experience with watsonx Orchestrate and complete the step-by-step tutorials in this learning path, sign up for the free 30-day trial and install the watsonx Orchestrate Developer Edition.