I architect and build systems that scale â secure, data-rich, AI-ready.
I balance that with a maker mindset: prototyping apps, automating workflows, and exploring emerging technology. Welcome to my digital garden.
I architect and build systems that scale â secure, data-rich, AI-ready.
I balance that with a maker mindset: prototyping apps, automating workflows, and exploring emerging technology. Welcome to my digital garden.

Iâve 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. âWhatâs your API quota strategy for when the agent is live?â Silence. Then: âWe assumed it would be fine.â 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 doesnât 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 itâs told by anyone. ...

Have you ever asked your smart speaker to âPlay my Morning Focus playlist on Spotify,â 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 âsmartâ part is often just a cloud algorithm guessing what you want. The âReal Talkâ Architecture: Local Control, Deterministic Execution Before we get into the step-by-step story of my struggle, letâs 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 âRevenue Radarâ agent I built (the one I documented in my âBeyond âHello Worldââ 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 Geminiâs context window for every single RAG retrieval was burning through credits like a startup burning through VC cash in 2021. ...