Operations | Monitoring | ITSM | DevOps | Cloud

Transform IT with Agentic AI: the Dawn of Accelerated, Autonomous Service

The IT service management (ITSM) industry stands at a real inflection point. For decades, service desks have operated on a fundamentally reactive model — employees face problems, submit tickets and wait for human analysts to diagnose, triage and resolve their issues. Automation improved throughput within that model, but it never challenged the model itself.

Agentic Pipelines now supports Claude Code

Last month, we introduced Agentic Pipelines, a new way to orchestrate AI agents to automatically, and routinely, handle the repetitive engineering chores so you can get back to solving the fun, cool problems. When we launched, Agentic Pipelines supported Atlassian’s developer AI agent, Rovo Dev. Today, we’re opening up Agentic Pipelines to even more teams: You can now run agentic steps in your pipeline with Claude as the provider.

Media Monitoring Evolved: How AI Makes Website Tracking Tools Essential

The average person would need 180 million years to read everything published online in a single day. For organizations trying to track what people say about their brand, manual monitoring stopped being viable somewhere around 2015. AI-powered media monitoring tools now process this impossible volume automatically, detecting brand mentions, analyzing sentiment, and flagging potential crises before they spiral.

Agent Timeline: The Flight Recorder for Your AI Agents

Last week, we introduced Agent Timeline, a powerful new observability experience purpose-built for debugging AI agent workflows in production. Agent Timeline uniquely connects AI-layer visibility to full-stack observability by organizing telemetry around an agentic conversation. A conversation contains one or more agent executions, each of which may contain LLM calls, tool invocations, handoffs, retries, human escalations, and downstream system calls.

Keep your Agents Under Control with agent-belt

You’re shipping a product with an AI-facing interface, or embedding AI-facing interfaces across your existing product line – skills your customers trigger, MCP servers their agent reaches for. Indie author or enterprise, your code runs in someone else’s agent runtime, against a model that updates every other day and a CLI that updates every other week. Cursor 2026.05.05-84a231c rolls out. Claude Code 2.1.132 lands the same week. OpenAI bumps gpt-5.5.

Building Automated Document-to-Video Workflows for Enterprise Operations

In enterprise environments, the volume of documentation is staggering. An average Fortune 500 company maintains hundreds of thousands of documents across HR policies, engineering specifications, sales playbooks, compliance guidelines, and customer support knowledge bases. This content represents a massive investment in institutional knowledge, but its impact is limited by a persistent delivery problem: people do not read documents.

Commercial Trucking Technology for Better Driver Awareness

Modern highways demand constant focus from professional drivers. New tools help fleets stay safe on long trips across the country. Fleet operators can monitor road hazards much better than in past decades. New onboard systems protect both the driver and the cargo from unexpected road events. High highway speeds mean split-second decisions dictate safety margins. Stay aware of your surroundings to prevent severe accidents before they happen. New updates give teams better visibility than ever. Drivers feel more secure when they have technology backing them up on dark roads.

Cracking the AI Detector Code: How to Keep Your Writing Authentic, Human, and Undetectable

Let's be completely real for a moment: artificial intelligence has completely transformed the way we write. Whether you are drafting a comprehensive research paper, putting together a weekly newsletter, or scaling a blog to reach thousands of readers, tools like ChatGPT and Claude have become the ultimate brainstorming sidekicks. They are fast, incredibly smart, and always ready to pull a structured outline out of thin air.

Anatomy of the AI Software Factory: The Context Layer

This is Part 2 of the AI Software Factory series. In Part 1, we established that the Agile methodology is buckling under the weight of “elastic code.” When AI agents can generate functionality in seconds, two-week sprints and manual task management become organizational bottlenecks. We introduced the concept of the AI Software Factory: a shift from managing human tasks to managing business intent through a “Funnel of Increasing Trust.” But a factory requires infrastructure.