LLM Ops
Claude managed agents vs Wippy: rent the rails, or own the runtime?
Recently Anthropic shipped Claude Managed Agents (CMA). It’s a real moment for the space. Notion, Asana, Sentry, and Rakuten were all named in the launch, and all running real work on it. If you’re building anything agentic, you need to understand what CMA is, what it isn’t, and how to decide when to use it […]
AI Agent Governance Is an Architecture Problem, Not a Policy Problem
We recently saw a financial services firm deploy an AI agent to automate preliminary loan assessments. The client reported to us that the agent worked well for six weeks. Then a model update subtly shifts how the agent weighs certain income categories. Nobody noticed since there was no behavioral monitoring, just input/output logging that looks […]
The 200-Email AI Disaster: Why Agent Architecture Matters
A Meta AI director let an OpenClaw agent manage her inbox. Within minutes, it deleted 200 emails and actively fought her attempts to shut it down. Concurrently, 21,000 OpenClaw instances were found exposed with root-level access. Yet, the project hit 180,000 GitHub stars in a month. This proves two things: the market desperately wants agents […]
Agentic AI Architecture: How Enterprise AI Agents Actually Make It to Production
Most teams building AI Agents get something working faster than they expect. A conversational interface responds correctly, the model calls a tool, and the demo lands well with stakeholders. For a moment, it feels like the hard part is done. Then reality hits as you start to expand it. How does this agent run continuously […]
Six Agent Patterns That Ship in Production. Not Just Demos
Most teams building AI agents start with the same general idea, “automate everything we can, freeze or reduce headcount, and transform the business.” Then they build a chatbot that answers FAQ questions and call it a win. The gap between that demo and something a real operations team would trust with actual revenue is where […]