COON optimizes code before sending it to AI models, enabling developers to save 30-50% on API costs while improving response times. It seamlessly integrates with existing code and scales with usage, ensuring more efficient AI development without sacrificing functionality.
COON is a powerful tool designed to optimize the use of AI models by significantly reducing token usage when sending code. By compressing code before submission, COON enables developers to cut 30-50% off their AI costs and achieve quicker responses from AI models without compromising the integrity of their code.
Before COON (150 tokens):
class LoginScreen extends StatelessWidget {
final TextEditingController emailController = TextEditingController();
final TextEditingController passwordController = TextEditingController();
Widget build(BuildContext context) {
return Scaffold(
appBar: AppBar(
title: Text("Login"),
),
body: SafeArea(
child: Padding(
padding: EdgeInsets.all(24.0),
child: Column(
children: [
Text("Welcome Back"),
Text("Login to continue"),
],
),
),
),
);
}
}
After COON (45 tokens - 70% smaller):
c:LoginScreen<StatelessWidget>;f:emailController=X,passwordController=X;m:b S{a:B{t:T"Login"},b:A{c:P{p:@24,c:C{h:[T"Welcome Back",T"Login to continue"]}}}}
You save 105 tokens per request!
COON supports various development platforms including:
To maximize efficiency further, COON suggests generating code directly in the compressed format. This method allows for the generation of code in COON format from the outset, dramatically lowering resource usage:
Example Prompt:
Generate a Flutter login screen in COON format. Use these rules:
- class → c:
- Scaffold → S
- Column → C
- Text → T
- AppBar → B
- body: → b:
- children: → h:
Output format: c:LoginScreen<StatelessWidget>;m:b S{a:B{t:T"Login"},b:C{h:[T"Welcome"]}}
Implementing COON provides a streamlined and economical approach to AI deployment, making it an essential tool for developers aiming to enhance their productivity while minimizing costs.