Operations | Monitoring | ITSM | DevOps | Cloud

AI is already good at writing SQL, which is why people keep asking whether AI agents will replace database IDEs. But letting an agent work on a production database is still a much bigger leap. In tests reported by BIRD, a text-to-SQL benchmark built from 95 real databases across 37 professional domains, human experts reached 92.96% execution accuracy. The best single-model entry reached 80.04% in June 2026. The model failed roughly one task in five; the humans, about one in fourteen.

Private cloud and on-premises infrastructure are different. I know this. I used the terms interchangeably anyway because I was trying to compress a pattern into one sentence. That was sloppy, but the underlying pattern still matters. Banks run Kubernetes differently from most other organizations. Not because every bank makes the same choices, but because similar constraints can produce a similar pattern.

The dashboards are red, the alerts are firing, and Slack has officially become a war room. Someone has asked, “Anyone else seeing this?” and 14 people have immediately responded with screenshots. Welcome to another day in distributed systems. The recent GitHub outage is a great reminder of how complicated modern applications have become. Services talk to services, infrastructure scales up and down, retries multiply traffic, and dependencies behave in ways nobody expected.

Top Tips is a weekly column where we explore practical ways to navigate the technology shaping our everyday lives. This week, we're tackling a common feeling: the fear of not being “tech-savvy” enough, and sharing simple habits to help you become more confident, curious, and comfortable with the technology you use every day. Ever felt like you’re the only person in the room who doesn’t understand what everyone is talking about? That little fear of looking clueless?

We’ve recently shown how Mobot, Sumo Logic’s AI assistant, has evolved from a search assistant into a true thinking partner, introducing natural language to log analysis and monitors. Today, we’re bringing that same conversational reasoning to one of the most powerful parts of the platform: playbooks in Automation Service. Historically, playbook authoring has been a highly manual process that required deep organizational and Sumo Logic platform knowledge.

Perplexity was a big name a few years ago. But, we haven’t heard much out of them lately. There are plenty of posts on social media criticizing Perplexity to that effect. One thing that the posts miss is that Perplexity is still the king of AI search. Google is giving it a run for its money with the AI previews on Google search, but Perplexity still wins out in several measurable ways.

During your last major outage, several monitoring tools raised alerts and every one of them was correct. What none of them could say was which alert explained the others, so the opening stretch of the incident went on assembling a picture the systems already held between them. That time shows up in your availability numbers, your SLA credits, and your board report. AIOps platforms close that gap by grouping the alerts caused by the same failure and handing your team one incident with context attached.