Posts

Autonomous agents introduce attack surfaces traditional security never anticipated — and the new OWASP ASI framework is the first standard built to address them.

KV cache memory kills agent throughput at scale — here’s how to fix it with TurboQuant, FP8 quantization, and H2O eviction in production.

Multi-agent FinOps systems don’t just surface waste—they eliminate it automatically, and the numbers prove it.

The TCO math has shifted decisively toward RAG for most enterprise agents — unless your query volume exceeds 100K/day with static knowledge.

gstack packages 21 Claude Code role configurations as SKILL.md files — and that’s both its strength and its limit.

Sparse MoE architectures have won the LLM scaling race — here is how to actually run them at production scale.

OpenAI’s Computer-Using Agent (CUA) navigates any website by seeing and reasoning — no DOM, no selectors. This deep dive covers how CUA works, how it compares to Anthropic’s approach and traditional RPA, and where the technology still falls short.

A practical guide to hybrid episodic-semantic memory architectures that enable production AI agents to maintain coherent behavior across sessions without hitting context window limits.

The MAST taxonomy provides the first systematic framework for diagnosing why enterprise AI agents fail in production IT environments.

Accuracy benchmarks built for static LLMs fail completely when applied to AI agents. Here’s the three-layer evaluation framework, four production KPIs, and CI/CD integration patterns that actually work.