Operations | Monitoring | ITSM | DevOps | Cloud

You see MTTR creeping up, but you don’t know why. You could ask your teams, but that means meetings, pulling people off projects, and waiting days for answers. What if you could just…ask? We’re excited to introduce the new strategic AI chief of staff for engineering leadership, powered by the Cortex MCP. By connecting your Engineering Intelligence data with your scorecards and standards, the MCP allows you to have a strategic conversation about your organization’s performance.

Building a catalog used to be a project. It meant months of tracking down owners, untangling dependencies, and manually piecing together a picture of your architecture. It was a tedious, thankless process that delayed the value of your Internal Developer Portal (IDP) before you even got started. Now, it’s a coffee break. We’re excited to introduce Magellan, our new AI-powered data engine designed to build your catalog and get your IDP live in minutes.

Here's a scenario every on-call engineer knows too well: a critical incident fires for a service you’ve never seen before. Your first ten minutes are a frantic scramble across wikis and Slack channels just to answer the most basic questions: Who owns this? What does it do? Where are the runbooks? By the time you’re oriented, the incident has escalated.

At Cribl, we’ve talked a lot about epochs. A moment in time when there was a before and after. AI, and specifically agentic AI, is an epoch. The way we work is going to forever change. There have been many such events in our lifetimes: the PC, the Internet, and the smartphone. AI will change how we work forever. Prior to the PC, there were people whose jobs were literally titled “computer”.

Enterprises are prioritizing digital transformation and agility, yet most lack the structural readiness for what's next. When 95% of financial services professionals believe there's little to no risk in delaying system modernization, even as the UK's FCA issued over £319 million in fines for non-compliance in just six months, it's clear many are mistaking surface upgrades for true adaptability.

From Microsoft Copilot to ChatGPT, AI applications are quickly becoming everyday workplace tools. But for many organizations, turning on these capabilities isn’t as simple as flipping a switch. Enterprise licenses for AI tools can cost millions, yet few companies can confidently say employees are using them effectively, or safely. The reality is that most AI rollouts start strong but stall fast.

Today, we’re excited to announce the launch of Mezmo’s AI-powered Site Reliability Engineering (SRE) agent for root cause analysis (RCA)—a transformative leap forward for engineering and operations teams facing the relentless complexity of modern cloud-native systems. ‍

I recently wrote about the impending SaaS crisis, driven by companies’ newfound ability to use AI to build software they used to have to buy. I predicted this phenomenon would make it even harder for SaaS vendors to drive growth, and that elite SaaS margins would fall from the mid-70s to the mid-60s as companies leaned more into their data and AI.

Transitioning LLM agents from intriguing prototypes to reliable, production-grade solutions introduces a unique and significant challenge: the inherent stochasticity of LLMs. Unlike conventional software, where inputs predictably yield precise outputs, an LLM’s response can exhibit variability even when presented with identical prompts. To ensure the dependability of your LLM agent, you will need a rigorous validation strategy.