Tag: ai-agents

Comparing the five major approaches to building agentic AI workflows — when to use monolithic frameworks, multi-agent orchestration, or the emerging LLM router pattern for autonomous tool selection.

Microsoft's DELEGATE-52 benchmark proves frontier models corrupt documents beyond 20 interactions. One week later, Google confirmed criminals used AI for a real zero-day exploit. The two findings describe the same gap from opposite ends.

How CoreCoder reverse-engineered Anthropic's Claude Code from 512K lines into a minimal 950-line implementation, revealing the essential architecture of modern AI coding agents.

The failure modes that plague distributed systems appear identically in multi-agent AI teams: stale locks, split brain, cascade failures, and Byzantine faults. The solutions are decades old.

ACP standardises how editors talk to coding agents. Here's how it works, who supports it, and how to orchestrate 90+ projects with a single CLI.

Kubescape 4.0 brings eBPF-based runtime threat detection to general availability, adds AI agent security scanning for KAgent workloads, and removes the high-privilege host-sensor DaemonSet entirely.

Combine n8n's workflow automation with NVIDIA GB10 Grace Blackwell hardware for privacy-preserving, high-performance AI automation. Real-world use cases and implementation guide.