๐ช๐ต๐ ๐ฌ๐ผ๐๐ฟ ๐๐ ๐๐ผ๐ฑ๐ถ๐ป๐ด ๐๐ด๐ฒ๐ป๐ ๐๐ฎ๐ถ๐น๐ ๐๐ฎ๐ฟ๐ด๐ฒ ๐ฃ๐ฟ๐ผ๐ท๐ฒ๐ฐ๐๐
Your AI tools finish tasks fast. They solve small problems with high success.
But they fail at large projects. They do not understand your whole codebase.
The reason is simple. These tools mix professional skill with project rules. They care about the current request. They do not care about project history.
This ruins your architecture. Every fast fix creates a future bug.
CBIM fixes this. It separates skill from project context.
The formula is simple: CBIM = Capability x Business x Independence + Memory
- Capability: Professional skills. An agent knows backend architecture or web dev. These skills move across projects.
- Business: Project logic. This is the map of your modules and rules. This stays with the project.
- Independence: Skills and rules stay separate. You swap projects without relearning how to code.
- Memory: This stops noise. It turns experience into long term knowledge.
Current tools are like a construction crew. They lay bricks fast. CBIM is a chief engineer. It handles the blueprints and standards.
The goal is a virtual team. One system organizes specialized tools. It finds the right skill for the right part of your project.
This is a design draft. It is not a proven guide. I share this to get your feedback.
Part 2 will cover the engineering.
Source: https://dev.to/nan023063/cbim-why-your-ai-coding-agent-cant-actually-read-a-large-codebase-4l29 Optional learning community: https://t.me/GyaanSetuAi