Featured
AI·MCP·Platform Engineering
Introducing SixDegree: live operational state for the agentic enterprise, auto-derived from your systems of record and served to AI agents via MCP.
Craig Tracey ·
AI·Context·Agents
Your CRM tracks the deal. It can't see the support tickets, the usage drop, or the AE who went quiet. Why deal risk lives between your systems, and what it takes for AI to actually catch it.
Craig Tracey ·
AI·Context·Operations
Most AI readiness advice tells you to build a data team, document your APIs, and codify your knowledge before you start. For a mid-sized company, that's months of work before a single outcome. Here's why you can skip it.
Craig Tracey ·
Context·Agents·AI
Context engineering operates at the prompt layer. Context management is the infrastructure underneath. Why mixing them up is the most common reason agent pilots fail.
Craig Tracey ·
Operations·Enterprise AI·Context
Every operations leader has tried to fix the opacity problem. AI agents make the cost of failure visible and immediate. Here is what changes now.
Craig Tracey ·
AI Agents·Governance·Enterprise AI·Context
Policies and approval workflows can't constrain agents that don't share your view of reality.
Craig Tracey ·
Context·Enterprise AI·Data
Data catalogs tell you where data lives. A context layer tells agents how the business runs. Here is the difference, and how to pick the right one before you burn a budget cycle.
Craig Tracey ·
Agents·Context·AI
Aaron Levie nailed the job description. But the person he wants to hire will spend most of their time doing plumbing nobody planned for.
Craig Tracey ·
Context·Agents·Platform Engineering
Most teams managing AI context are using markdown files. Here's what better looks like.
Craig Tracey ·
Platform Engineering·Context
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.
Craig Tracey ·
Agents·Context·Governance·MCP
Live knowledge graphs solve the biggest barriers to production agentic AI: governance, accuracy, and orchestration that RAG and raw MCP can't touch.
Craig Tracey ·
MCP·Agents
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.
Craig Tracey ·
MCP·Agents
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.
Craig Tracey ·