Workflow Orchestration
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 […]
Encode Your Firm’s Expertise Before a Competitor Does
Something shifted in professional services since the start of this year, and it didn’t arrive with a press release. It showed up in the margins but could be seen in the way a mid-size law firm suddenly started turning around contract reviews in hours instead of days, in the way a consulting practice began onboarding […]
The Missing Layer Between Your AI Agent and Production
Every engineering team building AI agents eventually hits the same wall. The prototype works. The chain runs. The agent calls a tool, gets a response, and produces something useful. Then someone asks: “Can this run in production?” And the answer, if you’re honest, is usually “not yet.” I’ve been shipping software for 16 years at […]
Your AI Demo Works. Your AI Project Will Not. Here Is Why.
There is a moment in every AI project where everything feels possible. You have a prototype that summarizes documents, or a chatbot that answers questions about your product catalog, or an AI agent that drafts emails from CRM data. The demo works. Everyone is excited. The CEO sends a Slack message with a fire emoji. […]
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 […]
Stop Building “AI Products.” Start Encoding Tribal Knowledge.
A hydraulic hose distributor we work with has a senior sales rep who has been quoting custom assemblies for 22 years. He knows which fittings are compatible under specific pressure ratings, which substitutions will pass inspection, and which configurations a customer’s engineering team will reject before they even review the spec sheet. None of that […]
