System Roadmap

System Topology

The curriculum moves from first principles into deployable architecture. Each layer introduces constraints that later modules depend on: model fundamentals shape prompt design, prompt design shapes orchestration, orchestration shapes evaluation, and evaluation shapes security and rollout strategy.

flowchart TD
  A["AI Fundamentals"] --> B["LLM Engineering"]
  B --> C["Embeddings & Search"]
  C --> D["Production RAG"]
  D --> E["Autonomous Agents"]
  E --> F["AI System Design"]
  F --> G["Evaluation Systems"]
  G --> H["AI Security & Red Teaming"]
  H --> I["Production Projects"]
  I --> J["Architectural Case Studies"]
  J --> K["Interview Preparation"]

Curriculum Backbone

The first module establishes how models represent information, consume compute, and behave under uncertainty. The middle modules translate those foundations into practical systems: structured outputs, tools, memory, retrieval, routing, tracing, and production evaluation. The final modules focus on security, reference projects, real-world architectures, and interview-grade system design fluency.

Delivery Matrix

Every topic follows the same three-page structure:

• 01-overview.md: the conceptual boundary, vocabulary, and engineering purpose.
• 02-architecture.md: components, data flow, constraints, and failure surfaces.
• 03-deep-dive.md: implementation details, performance mechanics, and production tradeoffs.

Publishing Rule

The full folder matrix exists in the repository, but placeholder-only topics stay hidden from the public sidebar. When a page moves beyond scaffold text, the sidebar reveals that page automatically on the next build.

Writing Rule

The foundation is designed so future writing can happen without sidebar, routing, or build-configuration churn. New content should only need to fill the existing overview, architecture, and deep-dive pages for a topic.