notes from the field
Making cloud run itself,
one agent at a time.
Hands-on writing on agentic infrastructure, MCP, and reliability — from someone shipping it in production at a Fortune-500 aviation platform, not theorizing about it. By Ajin Baby.
Right now:
Latest field notes
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Autonomy is a budget, not a toggle: error budgets for AI operators
SRE solved runaway release risk twenty years ago with the error budget. The same mechanism governs AI agents: authority per action class, burned in proportion to blast radius, demoted fast, promoted slow. In simulation it tracks a full-knowledge oracle within ~8%. Here's the model.
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The reliability gap: a framework for trusting autonomous SRE agents
In January 2026 an autonomous airline agent rebooked 1,247 passengers onto the wrong flights in one weather event. It worked in the demo. The gap between what agents can do and what we can trust them to do is a reliability problem — and reliability is not model accuracy. Here's how to measure it.
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Agentic Resource Discovery: I Read the Spec, Then Published a Catalog
Google, Microsoft, and Hugging Face shipped Agentic Resource Discovery — a well-known ai-catalog.json plus a registry search API so agents can find, verify, and connect to tools without scraping the DOM. The real schema, a working catalog, serving config, and the gotchas that break it.
Tools I build in the open
Who's writing this
Ajin Baby — 15 years making cloud platforms reliable, 2x founder before that. Azure AI Engineer, Neo4j Certified, IEEE member. More about me →