Outline

Overview

Architectural Design and AI introduces students to emerging workflows at the intersection of architectural design and artificial intelligence. Through hands-on experimentation with generative tools such as Diffusion models, LLMs and RAGs, students will explore new modes of ideation, iteration, and communication in architectural design. Emphasis is placed on integrating these tools into coherent visual strategies and critically evaluating their impact on the architectural process. The unit includes a speculative project and a reflective guide that documents and critiques design workflows. Students work individually or in small groups to develop proposals that are both visually compelling and conceptually engaged, gaining skills in prompt-craft, diagrammatic storytelling, and AI-enhanced design literacy.

Unit details and rules

Academic unit	Architecture
Credit points	6
Prerequisites ?	BDES1027
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Simon Weir, simon.weir@sydney.edu.au

Assessment

The census date for this unit availability is 30 January 2026

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Presentation	AI Design How-To Guide Report on a specific aspect of the available Gen-AI tools and their uses for the architectural designer’s workflow.	40%	Week -02 Due date: 11 Feb 2026 at 10:00	Group Presentation	AI allowed
Outcomes assessed:
Creative work	AI Design Guide PDF Document that accompanies the Presentation.	0%	Week -02 Due date: 13 Feb 2026 at 17:00	Multi-page PDF	AI allowed
Outcomes assessed:
Creative work	Design Workflow Project Architectural design task using Gen AI.	40%	Week -03 Due date: 04 Feb 2026 at 10:00	Multi-page PDF	AI allowed
Outcomes assessed:
Presentation	Design Project Design Proposal in response to a given design brief oriented around a specific hybrid Gen-AI and non-AI design process.	20%	Week -04 Due date: 28 Jan 2026 at 10:00	Individual Presentation	AI allowed
Outcomes assessed:
Creative work	Project PDF PDF Document that Accompanies the Presenation.	0%	Week -04 Due date: 28 Jan 2026 at 10:00	Single Page PDF	AI allowed
Outcomes assessed:
= hurdle task ? = group assignment ? = early feedback task ?

Early feedback task

This unit includes an early feedback task, designed to give you feedback prior to the census date for this unit. Details are provided in the Canvas site and your result will be recorded in your Marks page. It is important that you actively engage with this task so that the University can support you to be successful in this unit.

Assessment summary

Assessment 1 / 2 : Design Proposal using AI, as Presentation (1) and PDF (2).
Design Proposal in response to a given design brief oriented around a specific hybrid Gen-AI and non-AI design process.

Assessment 3 : Architectural Design Proposal. Architectural design task using Gen AI.

Assessment 4 / 5 : AI Design Guide as Presentation (4) and PDF (5). Report on a specific aspect of the available Gen-AI tools and their uses for the architectural designer’s workflow.

Assessment criteria

Result name

Mark range

Description

High distinction

85 - 100

The assessments demonstrate command of the project space, and has communicated theis exceptionally.

Distinction

75 - 84

The assessments demonsrate a high level of insight into the project space, and has communciated this very well.

Credit

65 - 74

The assessments demonsrate substantial insight into the project space, and has communciated this well.

Pass

50 - 64

The assessments demonsrate some valid insight into the project space, and has communciated this adequately.

Fail

0 - 49

The learning outcomes of the unit of study have not been met to a satisfactory standard.

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

Late submission In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date: Deduction of 5% of the maximum mark for each calendar day after the due date. After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Week -02	Day 5: Guest Lecture on emerging AI	Lecture (1 hr)
	Day 5: Design using Gen AI and Software	Workshop (3 hr)
	Day 6: Design using Gen AI and Software	Workshop (4 hr)
	Day 6: Collaborative workshop evaluating AI design solutions and design workflows.	Tutorial (2 hr)
Week -03	Day 3: Communicating with AI Models 1: Different Designers with Different Motivations facing the Limitations of Different Modes of Communication	Lecture (1 hr)
	Day 3: Exercises in meta-prompting and developing the language of design intention.	Tutorial (2 hr)
	Day 3: Design using Gen AI and Software	Workshop (3 hr)
	Day 4: Communicating with AI Models 2: Tokens and their parameters, objects and their qualities Designing “Design Meaning,” Concrete, Abstract and Poetic Language.	Lecture (1 hr)
	Day 4: Develop, clarify and expand and working document set for using AI in architectural design workflows appropriate for a University studio setting.	Tutorial (2 hr)
	Day 4: Design using Gen AI and Software	Workshop (3 hr)
	Day 5: Pulling together perspectiives and architectural drawings into a coherent project.	Tutorial (2 hr)
Week -04	Day 1: Introduction to the unit, project and tools; Design Workflow Sequences.	Lecture (2 hr)
	Day 1: Introductory Exercises on the AI Tools	Tutorial (2 hr)
	Day 1: Design using Gen AI and Software	Workshop (1 hr)
	Day 2: Deeper Skiils in AI Prompting, Promptcraft, and Meta-Prompting. How to make a plan from a perspective.	Lecture (1 hr)
	Day 2: Exercises in developing skiils in AI Prompting, Promptcraft, and Meta-Prompting.	Tutorial (2 hr)
	Day 2: Design using Gen AI and Software	Workshop (3 hr)

Attendance and class requirements

Please refer to the Resolutions of the University School: University of Sydney School of Architecture Design and Planning Faculty Resolutions 2022
Clause 8 (3) (a). Students are expected to attend a minimum of 90% of timetabled activities for each unit of study, unless granted exemption.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. Apply an increased familiarity with the opportunities of Generative-AI to the problems of architectural design, representation, and ability to design projects.
LO2. Interpret an architectural brief for a building, and devise an imaginative and plausible response.
LO3. Work productively in an architectural studio setting.
LO4. Evaluate feedback from others in a manner that is both reflective and proactive.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

Hi everyone, Thank you for completing the Unit of Study Survey for DESA3551 and for providing considered feedback on your experience in the unit. The Unit has a new Unit Code for 2026, DESA2006. I am pleased that the unit was rated positively overall, particularly in relation to teaching quality, intellectual reward, access to learning resources, and the flexibility and independence afforded in the design process. Your comments reinforce the importance of allowing students to pursue topics they are genuinely passionate about while developing alternative ways of thinking about architectural design. Your feedback also indicated that more specific guidance around assessment expectations, particularly for the final presentation, would be beneficial. In response, the next offering in DESA2006 will include more detailed preparatory assessment tasks, clearer articulation of what is expected at each stage, and explicit guidance on presentation scope and format (including indicative presentation length). The unit structure has also been adjusted to run over three weeks rather than two, providing more time to connect preparatory work to the final submission. These changes are intended to maintain the unit’s open and exploratory character while improving clarity, confidence, and alignment between assessment tasks. Thank you for your feedback and for contributing to the ongoing development of DESA3551. Kind regards, Simon Weir Unit of Study Coordinator, DESA3551 and DESA2006

Additional information

Additional costs

Students can access Microsoft CoPilot through their University of Sydney account. There are many AI models that have limited free access, and others that require payment for access or additional access. Students may choose to purchase additional AI subscriptions, the likely costs of which would be in the range of $20-200.

Work, health and safety

Working in an office environment all day, remember to take breaks, walk around occasionally, get some fresh air, and drink water.

Disclaimer

Important: the University of Sydney regularly reviews units of study and reserves the right to change the units of study available annually. To stay up to date on available study options, including unit of study details and availability, refer to the relevant handbook.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Early feedback task

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Additional costs

Work, health and safety

Disclaimer

On this page

Useful links

DESA2006: Architectural Design and AI

Intensive January - February, 2026 [Block mode] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Early feedback task

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Additional costs

Work, health and safety

Disclaimer

On this page

Useful links