Closer to the Metal Beats More Abstraction
AI collapsed build cost. That changes which infrastructure layer is worth paying for.
For twenty years, the rational response to expensive development was abstraction. Heroku over AWS. Vercel over Docker. Zapier over code. n8n over state machines. Lovable over engineering. Each layer traded control for speed — and when building was slow and expensive, that trade made sense.
AI inverts the equation. When Claude Code writes your infrastructure configs and deploys your state machine in an afternoon, the speed premium of abstraction platforms disappears. What remains is the cost: vendor lock-in, execution markup, opinion constraints, and a dependency you don’t control.
The Abstraction Tax
Every platform layer between you and the infrastructure is a dependency (the platform’s roadmap becomes your constraint), a rent extraction point (the markup isn’t for compute — it’s for convenience that AI now provides for free), an opacity layer (you debug the platform’s abstraction, not the actual infrastructure), and a portability trap (your deployment isn’t yours).
Cloud primitives — state machines, event buses, serverless functions, AI inference — have three properties that matter now:
They’re durable. State machines deployed years ago still run today. Your n8n workflow breaks when n8n changes their node API.
They’re composable. Each primitive does one thing. You compose them declaratively. A state machine orchestrates. A function executes. An event bus routes. The composition is visible in files that AI agents read, modify, and deploy.
They map to reality. A state machine IS the business process, not an approximation of it. Application code with background jobs is a developer’s model of a state machine, with all the drift and maintenance that modeling implies.
What Changed
Three capabilities converged: infrastructure-as-code made cloud resources declarative and reproducible. AI coding assistants absorbed the complexity that justified platforms. And API-first cloud services became composable primitives, not products you integrate with.
The old bottleneck was “cloud infrastructure is hard.” It isn’t hard anymore when your AI collaborator knows every service and every resource type.
Implication
The right response to AI making development faster isn’t more abstraction — it’s less. Get closer to the metal. Compose primitives. Declare infrastructure.
A workflow automation system on cloud primitives costs $68/month, runs on the customer’s own account, has execution guarantees from the cloud provider (not from application code), and is maintainable by any competent engineer with an AI coding assistant.
Build the factory on bedrock, not on someone else’s platform.
Contrarian To
“Use Vercel / Lovable / n8n to move fast.”
You can move just as fast with primitives now, and what you build is more durable, cheaper, more portable, and actually yours.