AI-Augmented Software Engineering

Course materials for the AI-Augmented Software Engineering lecture series.

This repository collects lecture notes, slides, code examples, assignments, and resources exploring how modern AI tools change the way software is designed, built, tested, and maintained.

Course Overview

AI-augmented software engineering is the practice of using AI systems — code assistants, agents, and LLM-based tooling — as active collaborators across the software development lifecycle. This course covers both the how (practical use of these tools) and the why (their strengths, limits, and implications for engineering practice).

Lectures

1. Setup Environments — install Git, GitHub, Python, and a coding agent before the rest of the course.
2. Specs-Driven Development — the agentic SDLC, when SDD fits, Plan Mode, SDD maturity levels, good specs, and SDD frameworks.
3. Anatomy of Coding Agents — how LLMs work, the model landscape, why LLMs are good at coding, and coding agents under the hood.
4. Advanced Context Management — a taxonomy of context, context assembly and discovery, the agent runtime pipeline, session management, and MCP fundamentals.
5. Agentic Codebase Structure — skills, rules, and guardrails; CLAUDE.md / AGENTS.md / SKILL.md / intent.md; hooks; and subagent patterns.
6. Agentic Code Review and Testing — deterministic guardrails, LLM-based review, safe deployment, runtime safety, and monitoring agents.
7. Agent Orchestration — the generator-critic loop, the goal pattern, the Ralph loop, running multiple agents, and the subagent pattern.
8. Security in the Age of AI — SAST/SCA and secret leaks, prompt injection and agent attack surfaces, and agent-assisted triage.
9. Software Factory and the Future of Software Engineering — self-running, self-improving systems and where AI software engineering goes next.
10. AI-Native Engineering Teams — how AI-native teams work, the standardized team stack, and LLM gateways, model routing, and cost optimization.

Repository Structure

.
├── lectures/       # Lecture notes and slides, one folder per session
├── assignments/    # Homework and project briefs, one folder per lecture
├── resources/      # Papers, links, and supplementary reading, one folder per lecture
└── README.md

Getting Started

Browse the lectures/ folder for session-by-session material. Each lecture folder contains a short README describing that session’s goals and contents.

License

Course materials are shared for educational use. See LICENSE if present, or contact the instructor for reuse terms.

---

AI-Augmented Software Engineering