Long-form guides for enterprise AI teams.
Deep, opinionated takes on custom MCPs, agent governance, and the operational realities of deploying AI in production.
Multi-agent orchestration: CrewAI, LangGraph, and Agno compared
CrewAI, LangGraph, and Agno are the three most common multi-agent orchestration frameworks in enterprise deployments today. This guide compares their actual operational properties — programming model, state management, debugging surface, and production readiness — and when a simpler architecture is actually the right call.
AI agents for healthcare: HIPAA-safe architectures that actually ship
Healthcare AI agent deployments live or die on compliance posture, EHR integration, and clinical escalation design. This guide walks through a reference architecture that meets HIPAA obligations and actually ships — what to build, what to avoid, and how to stage rollout.
AI agent governance: a practical guide to writing an agent constitution
An AI agent constitution is the written policy that defines what your agent can and cannot do. This guide covers the structure of a good constitution, how to enforce it at runtime, how to test it, and how to evolve it over time.
What is a custom MCP? Model Context Protocol, explained for enterprise teams
Model Context Protocol (MCP) is an open standard for connecting AI agents to the tools and data they need. A custom MCP extends that standard with your own organization-specific tools, governance, and compliance controls. This guide walks through what MCP is, when you need a custom one, how to design it, and the traps to avoid.