Context Engineering: How Dev Teams 10x Productivity with AI
Context engineering isn't just an AI buzzword. It's how high-performing dev teams are transforming productivity at scale.
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Komodor AI SRE vs. OSS AI Agent: A Technical Comparison of Agentic AI for Kubernetes Troubleshooting
Gartner predicts that AI agents will be implemented in 60% of all IT operations tools by 2028, up from fewer than 5% at the end of 2024. This acceleration has sparked an explosion of AI SRE solutions, from enterprise platforms to open-source alternatives, all promising faster root cause analysis and reduced MTTR.
3 Tips for a Smoother Software Deployment Process
Just because software releases have become more frequent doesn't necessarily mean they're always smooth. Many teams can push changes on schedule and still lose time to noisy pipelines, brittle handoffs, and production checks that start only after users complain. The result is work that feels fast until it gets slowed down by issues.
Everything you need to know about ITIL 5, AI and incident management
ITIL 5 launched in January 2026, and for the first time in the framework's 40-year history, AI governance is front and center. If you're running incident management, on-call rotations, or building operational tooling, this matters: the gap between AI adoption and AI governance is about to become a compliance and operational risk issue. I’m not usually a big ITIL fan, but this guidance has some genuinely useful framing and questions.
Automating Infrastructure as Code changes with an AI agent
The infrastructure management landscape is undergoing a fundamental transformation. Infrastructure as Code has already revolutionized how we provision and manage cloud resources by treating infrastructure as software. The next evolutionary step involves intelligent automation that can understand, adapt, and optimize these configurations independently.
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What Do You Use for AI Agent Infrastructure? The Complete Guide to Building Production-Ready Agent Systems
The question "what do you use for AI agent infrastructure?" has become one of the most searched queries in the DevOps and platform engineering space. And for good reason: the global AI agent market is projected to grow from $5.1 billion in 2024 to $47.1 billion by 2030, representing a compound annual growth rate of nearly 45%. With 85% of enterprises expected to implement AI agents by the end of 2025, getting the infrastructure right has never been more critical.
AIEnhancer AI room design: See Your Space Clearly Before You Redesign
Most interior projects don't fail because of bad taste; they fail because people can't fully see the outcome early enough. A vague idea lingers, doubts creep in, and decisions stall. AIEnhancer was built to shorten that uncertain phase, turning ordinary room photos into convincing visual directions that help ideas settle into something concrete and usable.
Why Integrated HR Technology is the Backbone of Modern Workforce Operations
In today's fastmoving business landscape, organizations face unprecedented operational challenges. From onboarding new talent to managing payroll and navigating complex compliance requirements, the sheer volume of tasks that HR teams must handle can easily overwhelm even the most seasoned professionals. To operate effectively, many companies are turning to integrated HR technology as the foundation for workforce operations. At its core, this approach unifies disparate systems into a single platform, enabling operational efficiency, strategic insight, and a better employee experience.
How we cut our NLQ agent debugging time from hours to minutes with LLM Observability
This article is part of our series on how Datadog engineering teams use LLM Observability to build, monitor, and improve AI-powered systems. At Datadog, we’re always looking for ways to make complex data easier to explore.