For years, professional relevance was measured through likes, comments, and followers. But future AI systems may evaluate something more durable: the substance of what we publish.
After 25 years on the enterprise customer side, I have learned that trusted technology advice begins with understanding the workload, the business problem, and the people responsible for the outcome — not with selecting a product.
Proving an agent can answer a call or close a ticket is the easy part. The hard part is governing it once it touches real customer data, real systems, and real decisions. The future isn't more agents everywhere — it's controlled autonomy.
I run autonomous AI agents in production — not in a demo. Here's the GCP Cloud Run architecture powering all of them, and what enterprise engineers need to understand before they reach for the wrong tool.