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Bring observability into Slack with Grafana AI
Resolve issues faster without leaving Slack. This video shows how Grafana Assistant delivers real-time insights, automates troubleshooting, and helps you investigate and act on incidents directly where your team already works. Thanks for watching!
Troubleshoot and monitor services with Grafana AI
Quickly diagnose issues and understand your systems with context-aware analysis. This video shows how Grafana Assistant helps you troubleshoot services, analyze dashboards, and generate new ones, all from simple prompts. Thanks for watching!
Turn knowledge into team-wide automation with Grafana AI
Make Grafana Assistant work your way by adding rules that capture your team’s context and best practices. This video shows how to customize behavior, improve efficiency, and turn tribal knowledge into repeatable workflows. Thanks for watching!
Building Agent-Friendly CLIs - What we learned at Checkly
Building Agent-Friendly CLIs: Why Your AI Agent Already Loves the Checkly CLI Stefan explains why products, docs, and CLIs must be AI-ready as coding agents rapidly become primary users of the Checkly CLI. He outlines key CLI features for agent workflows: Stefan demos how an agent initializes project-tailored Checkly setup from scratch without any human intervention and also shows how agents can entirely automate the incident life cylce from resolution to status page communication.
Seer Agent: Find Answers. Fast.
Use Sentry's Seer Agent to ask anything you need to know about your application. Use Seer Agent to: Email seer@sentry.io for access.
How AI-Powered Phishing Is Changing What 'Suspicious Email' Looks Like
For years, spotting a phishing email was almost a checklist exercise. Look for typos, watch for broken grammar, be suspicious of generic greetings like "Dear user," and check if the sender's address looks strange. That mental model worked because phishing emails actually looked bad. Which is no longer true. With the rise of AI, attackers can generate emails that are grammatically perfect, context-aware, and indistinguishable from legitimate business communication. The obvious red flags are gone. What used to look suspicious now looks completely normal.
Offline evaluation for AI agents: Best practices
If you’re building LLM-powered applications and agents, you’ve probably asked yourself: “How do I know if my changes actually made things better?” You can tweak prompts, adjust temperature settings, or try different models, but it’s not always easy to validate whether version B’s response is better than version A’s. Most teams fly blind in preproduction and rely on user feedback to see how well their application works in the real world.
Stopping Kubernetes cloud waste: agentic automation for enterprise fleets
Agentic Kubernetes resource reclamation is the practice of using an autonomous control plane to continuously identify, suspend, and delete idle infrastructure across a multi-cloud Kubernetes fleet. It replaces manual cleanup and reactive autoscaling with intent-based policies that act on business state, eliminating the configuration drift and cloud waste typical of unmanaged fleets.
How Agentic AI is Powering Autonomous IT Teams in Enterprises
AI has rapidly evolved from an experimental technology into a foundational capability for modern enterprises. Today, organizations are no longer asking whether AI should be adopted but how quickly it can deliver measurable operational value.