Most platforms today slap an AI chatbot onto a legacy IDE and call it "AI-powered." At Codigger, we took a different route. We built a six-layer stack where AI is baked into the architecture itself, moving from deep system understanding at the bottom to autonomous creation at the top.
By following the principle of "separation of concerns," we’ve created a decoupled system that balances industrial-grade stability with an AI-native workflow. Here is how the stack breaks down.
Phase 1: The Foundation (L1 – L2)
Focus: Cross-platform consistency and core logic.
This is the "hardware-agnostic" layer. We needed to ensure that code behaves exactly the same way whether it’s running on a high-end server or a local terminal.
●L1: The Mudem Layer (Infrastructure): This is our physical foundation. Mudem acts as a unified runtime that abstracts away hardware differences. It handles the heavy lifting of making Codigger work across different operating systems without performance hiccups.
●L2: The Objectsense Layer (Language): This is the logical "mother tongue" of the system. Objectsense supports cross-compilation, allowing us to break down the silos between different platforms.
●The AI Edge: At this depth, AI focuses on "Deep Understanding." Because it has a direct line to the underlying syntax and runtime characteristics, it provides high-precision code completion and optimizes performance at the compiler level.
Phase 2: The Core System (L3 – L4)
Focus: Governance and developer velocity.
Once the foundation is set, the system needs order. This phase turns raw low-level power into standardized, callable services.
●L3: Codigger OS (Operating System): Think of this as the central hub. It manages full-stack deployment, environment (Env) variables, and our MVC architecture. It sets the ground rules for how resources are scheduled.
●L4: Platform GNT (Framework): This is the developer’s toolkit. It provides a library of UI frameworks, standard components, and engineering tools right out of the box.
●The AI Edge: Here, the AI shifts to "Logic Mapping." It understands the OS rules and framework constraints, helping developers automate system configurations and orchestrate complex components without writing endless boilerplate.
Phase 3: The Value Delivery (L5 – L6)
Focus: User experience and ecosystem growth.
The final layers are where the actual work happens. This is the interface between the machine's power and the developer’s creativity.
●L5: Application & Desktop (Business Layer): This is the terminal where value is delivered. It includes our flagship IDE and desktop environment—the primary workspace where technical potential turns into actual products.
●L6: Plugins & Extensions: This is our "ecosystem antenna." Through our plugin mechanism and broad extension packages, the system becomes infinitely expandable.
●The AI Edge: At the top of the stack, AI enters "Co-Creation" mode. By facilitating a three-way collaboration between the AI Assistant, the human Developer, and the YesPMP platform, the AI directly generates business logic and builds out plugin features.
The Big Picture: A Bi-Directional AI System
The real strength of the Codigger architecture isn't just the layers—it’s how AI flows through them. We've built a closed loop of cognition and creation:
1.Bottom-Up Understanding (L2-L4): AI learns the pulse of the system, optimizing performance and ensuring the system-level stability that enterprise apps require.
2.Top-Down Generation (L5-L6): AI acts as a creative partner, helping ship features faster and pushing the boundaries of what the business can achieve.
Instead of a static foundation, Codigger is an evolving ecosystem that grows more capable as AI models improve. It’s built to stay fast, stay stable, and—most importantly—stay out of the developer's way.
Top comments (0)