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I’ve spent the last few weeks going deep on the Headless 360 documentation and auditing early deployment patterns. And I keep having the same conversation with architects who built it and leadership who approved it where I ask one question and get the same uncomfortable pause. “What’s your API quota strategy for when the agent is live?” Silence. Then: “We assumed it would be fine.” That assumption is the problem. Headless 360, announced at Salesforce TDX in April 2026, is a genuinely significant platform shift - it opens your entire CRM to AI agents via APIs, MCP tools, and CLI commands, no browser required. The marketing is compelling. The demo is clean. What the launch deck doesn’t show you is what happens on day one when real users start talking to your agent, or what happens when someone figures out your agent will do whatever it’s told by anyone. ...

Have you ever asked your smart speaker to “Play my Morning Focus playlist on Spotify,” only to have it confidently blast a random death metal mix at 7:00 AM? If you rely on Google Home or Alexa for your daily routines, you already know the dirty little secret of modern IoT: the “smart” part is often just a cloud algorithm guessing what you want. The “Real Talk” Architecture: Local Control, Deterministic Execution Before we get into the step-by-step story of my struggle, let’s talk about the solution. What I built is simple: I declared independence from the cloud for this specific routine. I took an old, dormant desktop and turned it into a headless, local-first automation server. ...

I recently looked at the GCP bill for the “Revenue Radar” agent I built (the one I documented in my “Beyond ‘Hello World’” deep dive), and the usage costs provided a significant and unexpected reality check. The Python code was clean. The logic was sound. But the sheer volume of JSON I was shoving into Gemini’s context window for every single RAG retrieval was burning through credits like a startup burning through VC cash in 2021. ...