Specs > prompts

After trying Cursor, Claude Code, and Google Antigravity for a bit, I keep ending up at the same conclusion.

The tool matters less than the workflow.

What has been working better for me

• start with a spec before writing code
• break the work into small tickets
• keep the context short and clear
• review the output before merging

What usually causes problems

• vague prompts
• too much context at once
• no clear acceptance criteria
• trusting the first output too much

Most AI tools are decent at writing code, but not that great at keeping the work structured.

That is why something like Traycer started making more sense to me.

It feels more focused on the planning side first, then execution, then review.

The flow is more like

spec → tickets → execution → review

instead of

prompt → code → fix → repeat

I also like that it can sit alongside tools like

• Cursor https://cursor.sh
• Claude Code https://claude.ai/code
• Google Antigravity https://antigravity.google
• Windsurf https://windsurf.ai
• Gemini CLI https://ai.google.dev
• CodeRabbit https://coderabbit.ai

For me, the real win is not some magic model.

It is just having a cleaner process and less chaos.

Curious how other people here are handling this.

Are you mostly prompting directly, or are you using a more spec first workflow?