Designing backend architectures Tradeoff analysis (DB, queues, caching, others) Infra diagrams Documentation
My current pick would be Claude Opus 4.6, because I've found it strong at structured reasoning and long context
But I'm curious what others are using today
I’ve been using Codex and Claude code over the past 6 months. They both do pretty well creating well structured normalized database schemas for both RDMS databases and single table design + appropriate GSIs with enough (business context). But they both have are suboptimal architecture and ETL designs.
I know AWS very well (trust me). But I would never go in blind for instance doing a green field implementation on Azure trusting AI.
It is expensive, I know. I mean, it takes a lot of tokens and the $20 is just not enough, but the price worth it, in my opinion. I did it with my project.
I tried, Gemini, GLM, Sonnet, and each of them has it strengths for specific things, but for initial architecture - Opus and BMAd
The naive way to do it is just to submit the file to the API, the API saves it to S3 and then does bulk INSERTS.
Claude did the first part right - create a pre signed S3 URL, send it to the browser and the file is uploaded directly to S3.
But it did the second part incorrectly - a bulk INSERT after getting the file from S3.
The correct way was to use the AWS extension that lets you upload the file directly from S3 into a table. The difference is 40 minutes vs 2 minutes. Of course Lambda times out in 15.