Critical Reflection & Analysis 

What Worked Well

AI significantly accelerated the design process by improving concept development, visual exploration, workflow organization, and rapid iteration of design ideas. It also enhanced visual communication and enabled the generation of multiple design alternatives in an efficient manner.

What Did Not Work Well

Some AI-generated outputs lacked structural realism, produced impractical forms, and occasionally ignored certain environmental and climatic constraints. As a result, several outputs required further architectural refinement, correction, and critical evaluation to ensure design feasibility and coherence.

What Was the Most Useful AI Tool?

ChatGPT was highly effective in:

• organizing the workflow

• developing the concept

• generating prompts

• and supporting architectural analysis

Midjourney was most effective in:

• visual exploration

• creating architectural atmospheres

• producing conceptual renders

Google Colab also supported:

• Analytical and experimental processes

• Organizing parts of data processing and development

• Improving digital workflow efficiency

• Testing additional design tools and techniques

Where Was Human Judgment Necessary?

Architectural decision-making was essential in:

• spatial organization

• climatic response strategies

• cultural interpretation

• architectural realism

• functional planning

How Did the Workflow Improve Efficiency?

The workflow improved efficiency by accelerating:

• idea generation

• visual representation

• environmental analysis

• presentation development

It also reduced design time while enhancing the quality of exploration and visual communication.

Risks of Over-Reliance on AI

Excessive reliance on AI may lead to:

• reduced originality and creativity

• weakened architectural critical thinking

• unrealistic design outcomes

• reduced sensitivity to cultural and environmental context

Therefore, the architect must remain the primary decision-maker throughout the entire design process.