๐ฃ๐ฟ๐ผ๐บ๐ฝ๐๐ ๐๐ผ ๐ฃ๐ฟ๐ผ๐ฑ๐๐ฐ๐๐ถ๐ผ๐ป: ๐ฆ๐๐ผ๐ฝ ๐ฉ๐ถ๐ฏ๐ฒ ๐๐ผ๐ฑ๐ถ๐ป๐ด
Many developers treat AI like a search engine. They paste an error. They ask for a page. They copy the code. It breaks. They treat the tool like autocomplete. This leads to mediocre output.
The problem is simple. Every new session starts at zero. Claude does not know your database. It does not know your auth patterns. It gives you a generic answer. It looks right. It does not fit your system.
You need an architecture file. We built one for our app, TracE. It is a single file with everything the AI needs to work.
Put these in your file:
- Your tech stack and versions.
- Your database schema.
- Your API routes and payloads.
- Lessons from your mistakes.
Now Claude stops guessing. It builds for your specific system. You get correct code on the first try.
Follow this workflow:
- Build the architecture file first.
- Build in order: Data, Backend, then UI.
- Use a feedback loop to fix errors.
- Document your deployment steps.
AI is not a way to write code faster. It is a way to think through your system faster. Stop prompting. Start architecting.
Source: https://dev.to/deepakthamizhk/prompts-to-production-a-full-stack-application-by-sonnet-with-catalyst-4i9e Optional learning community: https://t.me/GyaanSetuAi