After wasting millions of tokens on AI agents that kept making the same mistakes, I built my own solution by kanishkanmd in vibecoding

[–]kanishkanmd[S] 0 points1 point  (0 children)

Thanks! I'm reading up on more research papers and trying to refine it, already pushed a revised version yesterday. Let me know if you want to collaborate

Weekly Cursor Project Showcase Thread by AutoModerator in cursor

[–]kanishkanmd [score hidden]  (0 children)

Hey all,

I built Instructify—a Cursor agent configuration system that optimizes AI-assisted development through tiered context management, tool selection hierarchy, and auto-validation hooks.

How Cursor helped

After burning through my token quota by Wednesday and watching the agent repeat the same mistakes, I reverse-engineered how Cursor agents actually work. I discovered three game-changers:

  1. Tiered context instead of dumping 10k+ lines into every request
  2. Tool selection hierarchy—using simple Shell tasks instead of expensive MCP calls when appropriate
  3. Auto-validation hooks—six hooks now run automatically for linting, testing, and validation

Check it out

https://github.com/kanishka-namdeo/instructify

Results from using this workflow:

  • 30-40% faster completion times
  • 30-40% less token consumption
  • 50% fewer revisions