Operations | Monitoring | ITSM | DevOps | Cloud

Get more value out of your Cortex catalog with our MCP prompt library

You've set up the Cortex MCP and connected it to your AI assistant and IDE. You ask about service ownership, check a Scorecard or two, and it works. You're impressed by how much faster this is than clicking through the web UI. Now you're wondering what else you can do with it. I'm willing to bet we've hit a nerve with that "hypothetical" scenario. The Cortex MCP works exactly as designed, but it's deceptively difficult to know which questions to ask and when to ask them.

Rethinking developer productivity in the age of AI

For decades, engineering leaders have struggled to measure the productivity of their developers. Metrics such as number of PRs merged, lines of code changed, hours worked, and tickets closed were always flawed. They incentivized the wrong behaviors and ignored code quality and best practices. Ultimately, they were the perfect formula to make Goodhart's Law a reality. Measures became targets, which meant they ceased being good measures.

AI Readiness

Discover how Cortex helps engineering organizations unlock AI excellence by building the strong, reliable foundation needed for safe and scalable AI adoption. Cortex goes beyond just giving developers access to AI tools; it ensures your teams are ready to use AI safely, reliably, and at scale. What You’ll Learn in This Video: With Cortex, teams gain visibility into engineering practices, track compliance across services, and create a repeatable framework for safe AI innovation. By automating accountability and enforcing standards, Cortex helps organizations adopt AI with confidence, not risk.

AI Governance

Discover how Cortex helps organizations unlock AI excellence by bringing structure, visibility, and governance to teams that are building AI and machine learning models. As companies scale their AI initiatives, Cortex becomes the single source of truth for all ML and AI assets, ensuring reliable versioning, ownership, compliance, and responsible AI practices. What you'll learn in this video.

Cortex Wrapped 2025: The Year of AI Excellence

Every December, Spotify launches its infamous Wrapped campaign, which sends millions of users into a frenzy about their listening habits. They become pseudo data scientists and analyze how frequently they listen to their guilty pleasures, their kids' terrible playlists, or the music they love that nobody else has heard of yet. We love this tradition, so we're bringing it to Cortex.

AI Maturity

Learn how Cortex helps engineering organizations unlock AI excellence by measuring, standardizing, and improving how teams adopt and use AI coding assistants like GitHub Copilot, Cursor, and Claude. Cortex enables organizations to mature their AI practices—not just adopt AI tools, but adopt them safely, consistently, and with measurable engineering impact. What you’ll learn in this video.

Cortex and Rootly partner to help teams turn incidents into continuous improvement

For many engineering teams, an incident is a chaotic, all-hands-on-deck event. Once the incident is resolved, everyone returns to their regular work and the valuable lessons from the incident are often lost. The result is a cycle of repeated failures and engineer burnout, where incidents are something to be survived, not learned from. At Cortex, our mission is to help engineering organizations build a culture of continuous improvement.

New Feature Friday: Cortex & AWS

Most teams treat AWS like a black box. Cortex turns the lights on. We now automatically ingest all your AWS resources—from Lambda to RDS—and map them to the services and teams that actually own them. Daily. Automatically. No spreadsheets. No guesswork. Scorecards help you enforce real standards (think: runtime upgrades, tagging hygiene, EOL migrations). Workflows help your engineers self-serve AWS resources without needing to be AWS experts.

10 platform engineering tools your devs will thank you for

Modern engineering teams are shipping more services, managing more complex infrastructure, and moving faster than ever. But this velocity often comes at a cost to the developer experience. Engineers are frequently bogged down by infrastructure complexity, inconsistent tooling, and a lack of clear standards, which leads to cognitive overload and slower cycle times.