There are no pre-requisites for this module to be added

Software engineering is being transformed by AI-assisted development tools that can generate, review, and test code at a speed and scale no human engineer can match. For working developers, this creates both opportunity and risk: the same tools that can accelerate delivery can also propagate subtle defects, introduce security vulnerabilities, and erode the professional judgement that separates good engineering from dangerous engineering. This module takes the position that AI tools amplify existing competence rather than replace it, and that the discipline of software engineering has therefore become more important, not less, in an era of AI-assisted development. Students will develop the technical and professional skills needed to work with cutting-edge AI tools and agentic systems whilst maintaining rigorous standards of code quality, security, and process governance. The goal is to develop engineers who can command these tools rather than be commanded by them.

Upon completion of this module you will be able to

LO1: Critically analyse AI-assisted software development workflows to identify failure modes, quality deficiencies, and security vulnerabilities introduced by AI-generated code, applying systematic evaluation frameworks including static analysis, structured code review, and mutation-based testing.

LO2: Design, implement, and instrument AI-assisted development workflows, including agentic and multi-agent systems, that incorporate explicit quality gates, human-in-the-loop checkpoints, and observability mechanisms, demonstrating controlled and accountable use of current tools and protocols.

LO3: Articulate and defend considered positions on the professional, ethical, and governance dimensions of AI-assisted software engineering, including security, intellectual property, environmental cost, and regulatory context, demonstrating independent critical judgement appropriate to a responsible practitioner.