AI Engineering Foundations
AI Engineering Foundations | 12 planned modules | prompt, context, harness, and Symphony
Purpose
Section titled “Purpose”This section teaches the engineering layer between casual AI tool use and production agent operations.
The organizing model is the prompt | context | harness triplet.
Prompt work defines the instruction interface.
Context work manages what the model sees on each turn.
Harness work turns repeated agent work into enforceable, observable systems.
The final module applies those layers to Symphony-style orchestration, where issue contracts and lifecycle hooks become a control plane for AI-assisted engineering.
Planned Modules
Section titled “Planned Modules”| Module | Topic | Status |
|---|---|---|
| 1.1 | Prompt Fundamentals | drafting |
| 1.2 | Reasoning and Logic Prompts | drafting |
| 1.3 | Prompt Safety and Evaluation | drafting |
| 1.4 | Prompt Libraries and Contracts | drafting |
| 2.1 | Context Engineering Fundamentals | drafting |
| 2.2 | Repository Engineering for Agents | drafting |
| 2.3 | Retrieval, Tools, and Memory Boundaries | drafting |
| 2.4 | Dynamic Context Orchestration | drafting |
| 3.1 | Harness Fundamentals — Layers and System of Record | drafting |
| 3.2 | Guardrails, Gates, and Agent-Legible Apps | drafting |
| 3.3 | Operating the Harness | drafting |
| 4.1 | Symphony — Work Orchestration as Applied Harness | drafting |
Reading Path
Section titled “Reading Path”Start with prompt fundamentals if you need the instruction-design baseline.
Move to context fundamentals when the same prompt behaves differently across fresh sessions, agents, repositories, or model windows.
Use the harness modules when good individual sessions need to become repeatable team workflows.
Use the Symphony capstone only after the lower layers feel boring enough to operate.
For operators who need to learn AI tool habits before building systems, see AI-Native Work. If you are an engineer looking for IDE and CLI tooling, start with AI-Native Development.