Building applications without managing servers. Covers event-driven architectures, managed compute, scaling models, cost considerations, and serverless patterns for production systems.
View All Tags
My #1 rule:
Deploy the boring loop first. Add intelligence later.
Because if the simple loop doesn't work in production, the fancy version won't save you.
Your vibe-coded AI app does not need a complicated backend on day one.
🙅♀️ No RAG
🙅♀️ No tools
🙅♀️ No streaming
🙅♀️ No multi-agent orchestration
It needs one boring backend loop:
Getting to a live URL is the easy part now.
The harder question is whether you actually own what you built.
Can you move it?
Can you debug it?
Can you explain the stack to a client?
Can you protect your API keys?
If the answer is "No 🙂↔️" or "I'm not sure 🥹" → your AI app is still a hosted prototype.
Here are the 7 things you need to deploy your vibe-coded app and own the whole stack on AWS:
How to build a secure Lambda backend with API Gateway and Cognito authorization to trigger AI calls
Day 12: You build a protected frontend
Today: We build the secure backend that triggers calls
Here's the critical security issue:
Remember your ALB endpoint we built on Day 9 ↗?
https://ai-caller.yourdomain.com
If we add a /make-call endpoint directly to Fargate:
POST https://ai-caller.yourdomain.com/make-call
→ Publicly accessible
→ Anyone can trigger calls
→ Could rack up *huge* OpenAI/Twilio bills
→ Even with frontend auth, the endpoint is exposed
This is not acceptable.