
Introducing SixDegree - The Context Layer for Enterprise AI
Introducing SixDegree - the context layer for enterprise AI. Business is about relationships. Now AI can reason over them.

Introducing SixDegree - the context layer for enterprise AI. Business is about relationships. Now AI can reason over them.

Live knowledge graphs solve the biggest barriers to production agentic AI: governance, accuracy, and orchestration that RAG and raw MCP can't touch.

Getting an MCP server to work is not the hard part. The hard part is operating one: knowing who can access what, catching failures before users do, and building enough visibility to improve over time.

Model Context Protocol has moved fast, but implementation quality lags behind adoption. This post covers tool design and context quality: the two areas where most MCP servers fail.

Eval overfitting is real and underdiagnosed. Most RAG systems are built on a flat, static, insider-authored approximation of organizational knowledge. They don't have a model of the organization. They have documents about it.

Twelve rules for building AI agents that actually work. What agents are, how the agentic loop works, and the mental models that matter.

MCP tool overload is real. We benchmarked six LLMs with 25 to 150 MCP tools and measured accuracy degradation, latency spikes, and hard API limits. The cheapest model won.