AI
The Missing Runtime for Long-Running AI Agents
Enterprise AI agents need more than stronger models. They need durable execution environments that can coordinate multi-step workflows, survive failures, pause for human review and…
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8 articles

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I work on observability tooling for LLM-backed applications and the thing that surprised me most wasn’t a technical problem; it was how confidently wrong these systems can be while every dashboard stays green. Here’s a scenario th…
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AI
Enterprise AI agents need more than stronger models. They need durable execution environments that can coordinate multi-step workflows, survive failures, pause for human review and…
Blogs
Agentic AI is changing government infrastructure requirements, pushing agencies to rethink workflows, observability, data movement and resource prioritization before investing in n…
AI
Google’s open-source Scion testbed lets developers run isolated, parallel AI agents across local and remote clusters. Here’s how it works.
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Azure Global Black Belts Diego Casati and Ray Kao developed Project Nighthawk, a multi-agent system that automates deep technical research for AKS and ARO with 100% source-groundin…
AI
Anthropic Code Review dispatches agent teams to find bugs in PRs. Multi-agent analysis, severity ranking, and inline fixes for Teams and Enterprise.
AI
Discover how model context protocol (MCP) powered agentic AI is transforming DevOps by enhancing resilience and efficiency in cloud-native environments. Learn about the challenges,…
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Google’s open-source Agent Development Kit (ADK) lets TypeScript developers build modular, testable AI agents using familiar code-first workflows instead of prompt engineering.