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
10 Best Practices for AI Context Management
Most teams managing AI context are using markdown files. Here's what better looks like.
ContextAgentsPlatform Engineering
Craig Tracey
The Service Catalog Problem Isn't Backstage. It's the Catalog.
Backstage is hard to run. Cortex and OpsLevel made it easier. But none of them changed what a catalog fundamentally is: a human-authored approximation of system state that starts drifting the moment someone forgets to update it.
Platform EngineeringContext
Craig Tracey
Why Live Knowledge Graphs Are the Missing Context Layer for Safe Agentic AI in 2026
Live knowledge graphs solve the biggest barriers to production agentic AI: governance, accuracy, and orchestration that RAG and raw MCP can't touch.
AgentsContextGovernanceMCP
Craig Tracey
Operating MCP Servers in Production
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.
MCPAgents
Craig Tracey
Building MCP Servers That Models Can Actually Use
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.
MCPAgents
Craig Tracey
Your RAG Passed Every Test and Failed Every User
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.
AIContext
Craig Tracey
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.
AgentsMCP
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 EngineeringAgentsContext
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.
ContextAgents
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