Operations | Monitoring | ITSM | DevOps | Cloud

AI-first observability addresses two of the most pressing troubleshooting challenges: complex IT environments and AI-generated code. But understanding how to implement AI in a way that brings ROI, requires cutting through the hype and maintaining realistic expectations, while keeping a forward-thinking vision. In this blog post, we bring practical tips for including AI in your next observability RFP. The article is based on a webinar held with Logz.io founders, CEO Tomer Levy and CTO Asaf Yigal.

AI adoption is reshaping how organizations innovate. It’s also driving cloud costs higher. CloudZero’s State Of AI Costs In 2025 report finds that for mature FinOps and engineering leaders, visibility into AI costs is a critical first step, but it’s not enough. To enable fast, responsible AI and machine learning innovation at scale, teams need pragmatic, flexible guardrails. They don’t need rigid budgets or knee-jerk shutdowns that slow progress or push teams into shadow ML.

The cautious optimism business leaders held towards AI agents has evolved into more widespread enthusiasm. In our last survey from April 2025, just over half (51%) of companies had deployed AI agents in their organization. Six months later, 75% of companies are deploying more than one agent, according to PagerDuty’s latest research.

This could’ve been prevented. This should have been prevented. This too. We all hate getting tagged in PRs. The time, the blame for when you inevitably miss something, and constant “I wouldn’t have written it that way” feeling is just hard to shake. LLMs promised this would get easier. Promised they would do it for us. But as we’ve seen, we’re not there yet. But this is what Sentry does for a living. We catch bugs… in prod.

Artificial intelligence is everywhere: in keynotes, press releases, product announcements, and quarterly roadmaps. From help desk chatbots to predictive analytics, AI is being positioned as the silver bullet for almost every IT challenge. But under the surface, most IT leaders are asking a much more practical question: What’s actually real?

We are thrilled to announce that the Cortex Model Context Protocol (MCP) is now available in the Devin marketplace. This integration connects the world’s first AI software engineer with the real-time context of your entire engineering ecosystem, as managed and measured by Cortex. The rise of AI software engineers like Devin fundamentally changes how organizations tackle their biggest technical challenges.

We’re excited to announce that we are starting a phased rollout of Rovo Chat in Bitbucket Cloud today! It will be available to 100% of users by September 30th, 2025. To check if it’s available on your account, look for the Rovo Chat button in your top navigation. Rovo is Atlassian’s AI-powered teammate that helps you find what matters, learn faster, and take action right in your workflow.

Agentic AI is the next evolution in network management, moving beyond simple automation to intelligent systems that can reason, plan, and act autonomously. Justin Ryburn, Kentik Field CTO, highlights how this shift automates expertise, enables proactive problem-solving, and empowers human engineers for strategic innovation.