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Once upon a time, site reliability engineering rested on a linear assumption: monitor more, detect early, and you’ll recover faster. The rise of alert fatigue makes modern SRE teams realize otherwise: Ramadass's (2025) paper, Building an AI-Powered Observability Pipeline for Modern System Reliability, cited research that discovered that:
A frontier language model is only one component of an AI agent. The surrounding agent system—often called a harness—determines how the model receives... A frontier language model is only one component of an AI agent. The surrounding agent system—often called a harness—determines how the model receives context, uses tools, maintains state, responds to feedback, recovers from failure, and sustains progress over long-running tasks. The challenge is how to build the agent architecture that makes fro
As AI agents become more capable and operate over longer horizons, building security and trust into the applications they power becomes increasingly important.... As AI agents become more capable and operate over longer horizons, building security and trust into the applications they power becomes increasingly important. Drawing on work with NVIDIA OpenShell, agent developers, open-source projects, and partners across the ecosystem, AI safety and security teams at NVIDIA offer their perspective
Run AI agents in GitHub Actions with Docker Sandboxes. See how isolated agents can run Testcontainers tests, fix code, and open draft pull requests.
The type confusion bug can lead to V8 sandbox escape and control-flow hijacking of the host process. The post Critical Isolated-vm Vulnerability Leads to RCE on Host appeared first on SecurityWeek.
The U.S. Cybersecurity and Infrastructure Security Agency (CISA) ordered U.S. federal agencies to prioritize patching two actively exploited vulnerabilities in the TrueConf Server self-hosted communications platform. [...]
Comments
When teams first integrate large language models (LLMs) into their software platforms, the initial experience often feels surprisingly simple. A developer writes a few lines of code, sends a prompt to a model API, and receives a response that looks intelligent, contextual, and almost magical. A prototype can be built in days, sometimes hours, and the business quickly starts imagining how AI will transform customer support, automation, analytics, and decision-making. This early success creates a
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