Featured
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.
AIMCPPlatform Engineering
Craig Tracey
sixdegree
Thinking in Relationships
Building AI Agents: The Fundamentals
Twelve rules for building AI agents that actually work. What agents are, how the agentic loop works, and the mental models that matter.
AIAgentsPlatform Engineering
Craig Tracey
We Gave LLMs 150 Tools: Here's What Broke.
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.
AI AgentsTool CallingMCPBenchmarks
Craig Tracey
MCP vs CLI: You're Asking the Wrong Question
The debate between MCP and CLI for agent tooling misses the point. The real question is which mode you're building for, and where the actual token costs hide.
MCP
Craig Tracey
Internal Developer Portals vs Context Layers
IDPs were built for humans browsing catalogs. AI agents need something different: queryable relationships, real-time state, and cross-system reasoning. Here's why IDPs can't close the gap.
Platform EngineeringAI AgentsContext Layer
Craig Tracey
a16z Just Described What We've Been Building
Andreessen Horowitz published their thesis on why data agents need a context layer. Canonical entities, identity resolution, tribal knowledge, governance. We've been building exactly this.
Context LayerAI AgentsEnterprise AI
Craig Tracey
Service Catalog vs Live Ontology: Why Static Catalogs Fail
Service catalogs promised to be the single source of truth for your infrastructure. Here's why they go stale, what a live ontology provides instead, and when each approach actually makes sense.
Platform Engineering
Craig Tracey