How To Improve Your Agent Using Grafana GCX & Agent Observability

In this video, Jack shows how to improve your Agent using GCX and Agent Observability. For this demo, he uses a simple Agent to help improve his fantasy premiere league team. Discover how using Agent Observability provides a valuable breakdown and insight, comparing Experiment runs of Haiku, Sonnet, and Opus in terms of their strengths and weaknesses as well as suggested improvements. This demo showcases how powerful GCX can be when developing an Agent. Timestamps: 00:00 - Intro 00:18 - FPL Agent example 00:48 - Agent Observability Conversations 01:20 - GCX 02:10 - Using a Coding Agent to use GCX and stack to pull latest conversations 03:00 - How to set up a cross analysis of performance results across various Models 04:30 - Pulling Experiments using read only commands from personal stack 05:22 - Agent results Links/resources: Learn about Grafana Agent Observability: https://grafana.com/products/cloud/agent-observability/ Learn about AI-Powered Observability in Grafana Cloud: https://grafana.com/products/cloud/ai-observability/ Docs – AI Observability Overview: https://grafana.com/docs/grafana-cloud/machine-learning/ai-observability/ Docs – Introduction: https://grafana.com/docs/grafana-cloud/machine-learning/ai-observability/introduction/ Get started with the Grafana Cloud forever-free tier: https://grafana.com/g/cloud Have a question? Ask Grot, your AI helper: https://grafana.com/grot/ Reach out in our community forums: https://gra.fan/communityyf --- Thanks for watching! 👍 Was this video helpful? Like and subscribe to our channel for more videos. Connect with Grafana Labs: X: (https://www.twitter.com/grafana) LinkedIn: (https://www.linkedin.com/company/grafana-labs/) Facebook: (https://www.facebook.com/grafana) #Grafana #Observability #aiagents #observabilitysystems #AIObservability #LLMObservability #AI #LLM