Operations | Monitoring | ITSM | DevOps | Cloud

AT&T is permanently shutting down its email-to-text and text-to-email gateway, which means alerts sent to @txt.att.net or @mms.att.net no longer reach phones. For IT teams, MSPs, facilities teams, building management, utilities and incident response teams in general, this creates a serious gap. Critical alerts from monitoring tools, ITSM platforms, building systems, IoT devices, and other operational systems still need to reach the right person quickly, especially after hours.

A new Google white paper suggests that as AI writes the majority of our code, the role of a software engineer is shifting from writing applications to performing rigorous validation and QA.

Is your teen talking to AI chatbots in private? Kids aren’t only spending time on social media anymore — they’re also turning to AI chatbots for advice, stories, and emotional support. Our new Social Content Detection feature now supports AI apps like Character.AI, Gemini and ChatGPT, allowing you to monitor risky keywords and see context screenshots when something feels off. In this video, we'll cover.

Compliance work that lives outside the build pipeline becomes developer friction – and friction kills adoption. The simpler fix is to make SBOM generation a standard pipeline step via a reusable template, with output routed automatically to central storage and surfaced to the teams who need it. When developers can see their own license issues and vulnerability exposure without filing a ticket, compliance stops being a tax and starts being a byproduct of shipping.

Small language models are cheaper, run privately on your own hardware, and often beat the big models on focused tasks like sorting emails or summarizing transcripts — and they're perfect for checking a large model's work. The key is knowing when to use which.

AI adoption is easy to report. Business impact is harder to prove. Engineering leaders are under pressure to show what AI is actually changing — not just who is using it, but whether it is improving delivery, quality, developer experience, and business outcomes. This discussion between 3 engineering leaders explores how to move beyond vanity metrics, build a practical measurement approach, and communicate AI’s value to executives and CFOs with more credibility and less hype.

PagerDuty’s slack experience is evolving to help your teams organize better and resolve incidents faster. Use Triage Channels to collect telemetry and updates from your systems. Create dedicated Incident Channels for coordination and resolution. Give stakeholders the updates they need in Announcements Channels. Everyone in your organization can get the information they need easily.

Zendesk replaced 15 years of homegrown incident tooling and PagerDuty by migrating 1,200 engineers across 150 teams onto incident.io in just 10 weeks, cutting mean time to triage by 32%, saving $500k+ in year one, and eliminating 800+ hours of annual toil, with zero incidents on go-live day. Tom Monaghan (VP of Engineering Productivity & Product Reliability) and Anna Roussanova (Engineering Manager) share how they pulled it off and what's next as Zendesk helps build Investigations, our AI agent that starts digging into incidents the moment an alert fires.

Most enterprise AI agents take weeks to build. This one takes minutes. Watch how Agent Lab creates purpose-built agents with natural language, adds reusable skills, and sets guardrails before anything ships. From idea to production-ready in a single sitting.

In this quarterly update, Mike Adler, Chief Technical Officer and Chief Product Officer at N-able, breaks down the biggest product releases from Q2, all centered on bringing AI into everyday IT workflows. Highlights include: N-zo, the AI assistant in N-central — Get faster answers about your environment without digging through screens. Ask which devices need upgrades, which have the most vulnerabilities, or which warranties are expiring, and get instant results.