Survive the scale of vibe-coded infrastructure.
AI tools built your MVP in days. Now, bloated execution paths and unoptimized code are destroying your server margins. Fix the foundation without a rewrite.
Target: AI-generated backends crashing under load and inflating cloud bills.
The hidden cost of building fast.
Using AI to write your app was the right move to get to market. But AI doesn't know how to write efficient code. Here is why your app is costing you too much to run:
AI writes for speed, not scale.
Tools like Cursor or Claude write "brute-force" code. They choose the heaviest, most direct path to make a feature work. It runs perfectly when you are testing it alone, but requires massive computing power the moment real users arrive.
The "Bad Code Tax".
Cloud providers (AWS, Vercel, Google) charge you for compute time and memory. Because AI-generated code is incredibly inefficient, your app burns through server resources. You are forced to pay for expensive server upgrades just to keep the app from crashing.
Cut the bill, keep the app.
You don't need to rebuild your product from scratch. We go under the hood, find the specific AI code that is burning resources, and replace it with a lightweight, high-performance engine. Your app looks the same, but your cloud bill drops dramatically.
For your engineering team.
AI models default to blocking loops, excessive object instantiation, and unoptimized memory allocation. It works perfectly for 10 users. It exhausts your CPU at 10,000.
When Vercel functions timeout or your AWS instances hit 100% CPU, the bottleneck isn't the framework. It's high garbage collection pauses and un-optimized runtime paths generated by the LLM.
We identify the specific execution paths burning compute, and replace them with native, memory-safe logic.
Stop scaling servers horizontally to mask vertical inefficiency. Downgrade your infrastructure instances while handling more traffic.
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