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Hear how Kentik uses AI to validate AI and catch 90%+ of bad networking answers before users ever see them.

Welcome to Hector’s 2026 Spring Update! This new release takes your trusted platform for inventory management to the next level — improving speed, flexibility and visibility on Hector’s web and mobile applications. For more information, explore our release notes or contact us at sales@hectorassetmanager.com. Thank you for watching, and enjoy exploring all the new features in Hector! Join our community on LinkedIn to never miss an update:/ hectorasset.

Bitbucket Pipelines lets you invoke child pipelines from a parent step, but until now there was no way to pass information between them. Variable sharing changes that. You can define variables in a parent step and pass them directly to child pipelines as custom pipeline variables. With dynamic step conditions, those child pipelines can make decisions at runtime based on the values they receive, like skipping a deployment when a security scan detects critical vulnerabilities.

Grafana Assistant is going places you might not expect — including healthcare. Golden Grot winner Oren Lion from TeleTracking reveals how Grafana Cloud supports their systems that help keep patient care moving — and how Assistant enables teams to get from “what happened?” to “here’s why” faster. From moon landings to patient care, Grafana is everywhere. Congratulations to Oren, Chris Johnson, Mark Munson, and the entire TeleTracking team on winning this year's Golden Grot Award for Pioneering AI in Observability!

MCP vs CLI: which one should your AI agent actually use? We get into it with Grafana's cloud and OSS MCP servers and gcx.

Context Offloading is a pipeline solution for managing Observability with AI Agents. If you are building AI Agents that work with real data, the context window can very easily get filled with bloated context that the Agent does not really need. Sven demonstrates "Context Offloading", a solution that stores the JSON result and sends only the summary of the JSON blob, making the LLM loop performance much quicker and keeping your context window small.

Grafana AI Observability is our new database and platform for observing AI Agents. Over the past year at Grafana Labs, we built Agents and we needed a way to understand how they are performing, what are the costs associated with them, what's the error rate or time to the first token as well as how they are behaving. Grafana Staff Engineer, Ivana Hučková provides a deep dive demo on how Grafana AI Observability connects our experience building Agents with our experience building observability systems.

Learn how to create and customize dashboards on Uptime.com, including setting up the General and Display Settings tabs, configuring check cards, filtering by state, setting sort orders, displaying metrics, managing alerts, and creating multiple dashboards.

Say hello to AI Chat Detection! And learn how to receive alerts about potentially risky conversations in your child's ChatGPT, Gemini, and Character.AI.

AI coding agents write code faster than your pipeline can catch mistakes. What if the agent could validate against CI before you ever push? In this 5-minute demo, we set up CircleCI's Chunk CLI and run a microbuild using Chunk sidecars, secure Linux microVMs that spin up in ~1 second in your CircleCI account, mirror your working directory (no git push required), and give your agent CI-grade feedback while it's still in context.