A screenshots-first tour of how our own team — SRE, platform, developers, QA and the CEO — actually uses RunWhen Agents day to day. Daily newsletters instead of alerts, Slack root-cause answers, FinOps in minutes, and release readiness before standup.
Production troubleshooting is where agents get handed a haystack. Let code do the searching, and spend the model on judgment — with reviewed, shared skills instead of code improvised at runtime.
A TLS and false-positive alert story. Grafana provisioned datasources won’t reload a rotated cert until you nudge the YAML version integer forward. We forgot. A misleading alert led us back to it.
Joining a shared workspace mid-stream means walking into a room already full of context. /onboard-me is the tailored onboarding command our team wrote to give whoever just opened it the lay of the land — workspace identity, the services that matter, the conventions already in play, and a clear invitation to ask the next question.
You were out for a few days. A deploy went out, SHAs moved, a couple of things shipped. What actually changed? /dev-whats-changed answers the catching-up question with three ordered layers — code that’s live, commits since the last release, and only then a deeper dive — so the story leads with cause, not with infra alerts.
We built 22 slash commands for our own workspace. This series walks through the ones we use most, starting with how we decide whether to ship a release.
We run /mgr-release-readiness before every release. Here is what it checks, how it works, and what it told us today — with live results from our actual environment.
Drop into the same workspace our team uses every day. Real clusters, real agents, real remediations. No sandbox. About 45 minutes.
The RunWhen Platform MCP server connects your AI coding agent to your team’s workspace — locally over stdio or via RunWhen-hosted remote MCP on beta (Bearer token or OAuth browser sign-in where your client supports it) — so you can investigate infrastructure, create rules and commands, and author automation without leaving your editor.
This article shows how to improve alerting (dramatically) using Agentic AI and Automation.
David Tippett and Kyle Forster discuss AI assisted Search and it’s impact on development.
Explore how RunWhen’s AI Digital Assistants reduce costs and improve the outcome of application modernization projects.
See how Cautious Cathy, a RunWhen Digital Assistant, responds to a request to determine why a deployment will not roll out.
This blog post looks at some of the challenges with Kubernetes resource management, while highlighting some zero-cost approaches to reducing the frustration of resource management.
Read this short guide on best practices engaging the RunWhen team for a proof-of-concept.
Tackling the hidden costs of Kubernetes and how to decrease the impact of app modernization on your team.
Explore how RunWhen’s AI Digital Assistants redefine remote troubleshooting, enabling collaboration and problem-solving from anywhere.
Highlighting the impact of Modern AI and how it can redefine remote troubleshooting, enabling collaboration and problem-solving from anywhere.
Learn how RunWhen’s Digital Assistants can execute complex tech stack queries, empowering engineers to troubleshoot more efficiently.
RunWhen’s AI Digital Assistants empower developers with instant troubleshooting sequences, revolutionizing the tech support landscape.
