AI Engineering Foundations

AI Engineering Foundations | 12 planned modules | prompt, context, harness, and Symphony

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

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

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.