Operations | Monitoring | ITSM | DevOps | Cloud

In the Age of AI, Taste Isn't About Aesthetics

AI can generate a UI in seconds. So what do designers actually bring to the table? Marcela, Principal Product Designer at Rootly and former Founding Designer at Ramp, has spent 20 years in design. Her answer: taste isn't about aesthetics or crafting pleasant interactions. It's about asking the uncomfortable questions, and choosing the right problem, not the easiest one.

The Edwin AI Agent Orchestrator: Coordinated Incident Investigation Across the Tools You Already Use

Edwin AI’s Agent Orchestrator keeps incident investigation, context, and response aligned as work moves across tools, eliminating the manual handoffs that slow resolution. Every major incident has two timelines running in parallel. The first is the incident itself—services degrading, users affected, business impact accumulating. The second is quieter and just as costly: engineers switching tabs, re-explaining context to new responders, moving notes from one tool to another by hand.

AI for Everything After Code: Ship Fast, Stay Safe

Recorded at @DevOpsLive Most teams have “done DevOps” and “built a platform,” but still wrestle with the same core problems: platforms that developers dodge, AI that accelerates coding while quietly degrading delivery performance, security and compliance that can’t keep up, cloud bills that keep climbing, and incident response that hasn’t caught up with cloud‑native complexity.

PagerDuty Invests in the AI-First Operations and Resilience of Healthcare and Crisis Response Organizations

At PagerDuty, we believe operational excellence and social impact are inseparable. As AI rapidly transforms how nonprofits operate, our AI and agentic technology empower mission-driven teams to automate complexity and focus their limited resources on what matters most: delivering reliable services that create meaningful impact at scale.

Debugging multi-agent AI: When the failure is in the space between agents

I've been building a multi-agent research system. The idea is simple: give it a controversial technical topic like "Should we rewrite our Python backend in Rust?", and three agents work on it. An Advocate argues for it, a Skeptic argues against, and a Synthesizer reads both briefs blind and produces a balanced analysis. Each agent has its own model, its own tools, its own system prompt. It worked great in testing. Then I noticed the Synthesizer kept producing analyses that leaned heavily toward one side.

A Prototype's Worth 1,000 Minutes: How Claude Prototypes Accelerate The Product Planning Process

The relationship between product managers (PMs) and engineers is due for an upgrade. The division between these personas is responsible for a healthy, if laborious, collaboration when envisioning and building new products. A PM generates the vision; engineers translate it into an architectural approach, raising the technical questions that sharpen it along the way. This back-and-forth eventually produces tight alignment, a solid PRD, and functional code.

You're Running Agents. Your Tooling Is Still Catching Up.

Introducing GitKraken Desktop 12.0. At some point in the last year, the question shifted. It stopped being “should I use AI coding agents?” and became “how do I run more than one at a time without losing my mind?” If you’ve been there, you know what the management layer looks like. A terminal per agent. A worktree created by hand before each session.

Route OTel data from AI apps to ClickHouse and Datadog using Observability Pipelines

As organizations continue to heavily invest in AI and build more agentic workflows, their telemetry data volumes can surge quickly, and the associated costs can become unpredictable. To regain control of their data, many AI-forward teams are turning to high-throughput, low-latency pipelines to collect and route data to tools such as OpenTelemetry (OTel) and ClickHouse. But these self-hosted solutions come with drawbacks.

What Parents Should Know About AI Essay Grader Tools

Artificial intelligence is showing up in more classrooms than ever before, and parents are right to have questions. One area that has grown quickly is AI-powered writing assessment. Schools and teachers are increasingly turning to automated tools to help manage the workload of grading student essays, and while this might sound like a behind-the-scenes administrative change, it directly affects how your child receives feedback on their writing. Understanding what these tools do, how they work, and what they cannot do will help you stay informed and involved in your child's education.