FIT1056 · Making with artificial intelligence: Software in the AI era

Overview

Software is increasingly built by people working in partnership with AI tools, but useful software still starts with understanding real needs and making good design decisions. This unit introduces you to AI-powered software development through the design and delivery of working digital solutions such as apps, tools, systems and websites. You will learn how to understand user and stakeholder needs, define requirements, shape feasible software solutions, and use contemporary AI coding tools to support implementation, testing, documentation and refinement across the software development lifecycle. The unit incorporates core software engineering practices, including requirements analysis, system design, modular implementation, version control, testing, deployment, technical documentation and collaborative development. You will learn to use AI-enabled development tools responsibly and critically, including prompting, reviewing, adapting and validating AI-generated code and design suggestions. Emphasis is placed on building software with appropriate complexity while maintaining code quality, correctness, maintainability, security awareness and alignment with user needs. Through practical, project-based activities, you will create, evaluate and improve software artefacts using modern development workflows. The unit develops the capability to move from problem or need to working software solution, while understanding the role, limits and responsibilities of AI-assisted development in contemporary software engineering practice.

Areas of study: Software development Software engineering Web development

Offerings

Assessment

The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

The Handbook lists no prerequisite, corequisite or prohibition for this unit.

Learning outcomes

1. Apply software lifecycle practices to understand needs, define requirements, shape feasible designs, and plan the delivery of a working digital solution;
2. Use AI-enabled software development tools to support implementation, testing, documentation, and refinement while reviewing, adapting, and validating generated outputs;
3. Develop a working software artefact of appropriate complexity that demonstrates modular structure, readable implementation, functional behaviour, and attention to maintainability;
4. Contribute to collaborative software development workflows using version control, shared artefacts, technical documentation, and automated build, test, or deployment practices;
5. Evaluate and refine software artefacts with attention to correctness, maintainability, responsible AI use, security awareness, and alignment with user and stakeholder needs.

Workload

Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled online and face to face learning activities and independent study. Independent study may include associated reading and preparation for scheduled teaching activities.

Student experience, not official rules. Nothing here changes what the Handbook says.