Threat-Detection Platform Architecture with Claude Code
End-to-end architecture of a Claude Code threat-detection platform: ingestion, triage agents, MCP tools, and human review.
Agentic AI, LLM engineering, and the models behind modern automation — multi-agent systems, LLM evaluation and comparisons, RAG, fine-tuning, AI infrastructure, security, and production AI engineering.
From the blog
End-to-end architecture of a Claude Code threat-detection platform: ingestion, triage agents, MCP tools, and human review.
Five proven multi-agent architecture patterns built on A2A — orchestrator, peer mesh, hub-and-spoke, marketplace, and tiered specialist.
Anthropic's expanded public beta adds sub-agent coordination and rubric-based evaluation. The actual mechanics and what it means for production AI systems.
Deploy GPT-Realtime-2 on Azure AI Foundry. Region availability, networking, data residency, BAA, and the gotchas teams hit in the first 48 hours.
How to design a multi-agent system using MCP for tools and A2A for cross-vendor coordination, with a CallSphere voice agent as a participating node.
Anthropic's finance agents handle back-office workflows. CallSphere handles the front door — the customer voice and chat layer for banks.
The 2026 desktop AI agent landscape — ServiceNow Project Arc, Anthropic Claude offerings, OpenAI agents, and Google Mariner. A buyer's map.
GPT-Realtime-2 brings GPT-5-class reasoning into voice. What that means for tool-call reliability, structured output, and production agent design.
OpenAI's Frontier platform makes model-native orchestration the default. What that means for agent builders, voice/chat buyers, and the build-vs-buy decision.