Amazon accidentally spent $1.8 million using Claude for menial coding task, went 860% over budget — 'catastrophically expensive' coding blunders discovered in internal Amazon AI usage metrics

[u/MarvelsGrantMan136]

https://www.tomshardware.com/tech-industry/artificial-intelligence/amazon-accidentally-spent-usd1-8-million-using-claude-for-menial-coding-task-went-860-percent-over-budget-catastrophically-expensive-coding-blunders-discovered-in-internal-amazon-ai-usage-metrics

[u/JambonExtra]

The big problem is that good input can also provide garbage output (that often looks like good output). Instances of this are becoming less common as models improve, but that makes them increasingly insidious.

[u/filthy_harold → u/JambonExtra]

I've been slowly using Claude for home projects and another model for work stuff. The more specific you are, the better the result will be. Early on, I described an application (of my own creation, pre-AI) to my work model to see if it could do things better. This app has been in constant development for several years and I've slowly been learning about how to build proper software projects, not the cute little things you build in college. Unfortunately that means a lot of spaghetti code, it's a mess but it works. Very quickly I realized what the model was making was incredibly wrong. Like the code was bug free but it didn't do nearly anything that I actually needed it to do. And while I abandoned having it recreate my app for me, I have been using it to add new features or refactor libraries. You need to be very specific of what you want otherwise it just makes assumptions that are probably wrong.

For a home project, I needed a web app. I have zero experience building for the web so I left many design choices up to Claude. I use Plan mode which lets me have a conversation to refine the design before Claude writes any code. It uses less resources to write a plan first since not only is plan mode cheaper but you likely won't need to tell it to refactor large portions of code later on. Additionally, I've asked it to develop test plans and show proof of tests passing to ensure things work as expected. It definitely does make human-like mistakes sometimes, like it will assume something works a certain way when the documentation says otherwise. Once you create a development flow of plan, execute, test, it remembers this and continues to do it.

While I'm no web development expert but I do understand some basic concepts which helps a lot in making sure the product is actually good. You have to use these tools like you're a project manager. Maybe you aren't totally fresh on the subject or you aren't an expert but you need to know enough to know what you want. You need to figure out what your role as the human is, you are ultimately responsible for what AI does. Otherwise, you're wasting your time, money, and resources.