CTA INTEGRATION

CTA Integration (Critical Thinking & Triangulation Analysis)

Comparative Analysis of AI Outputs

To improve the design process, the outputs from Perplexity, Gemini, and Midjourney were compared and evaluated. Each AI contributed different strengths but also produced limitations that required human judgment.

Perplexity AI

• Provided climate and environmental data for Kajang.

• Helped identify solar exposure, wind directions, and passive design strategies.

• Strong in research but limited in design creativity.

Gemini AI

• Developed the architectural concept and design narrative.

• Helped generate ideas such as the wave roof and wind corridor.

• Strong in concept development but sometimes unrealistic.

Midjourney

• Produced high-quality visualizations and architectural renderings.

• Helped visualize form, materials, and atmosphere.

• Strong visually but often ignored structural feasibility.

Human Judgment

Human intervention was required to combine the strengths of all three AI systems. Environmental data from Perplexity guided the design decisions, Gemini developed the concept, and Midjourney visualized the final outcome. Unrealistic forms, structural issues, and impractical ideas were refined and adjusted through architectural judgment.

Conclusion

The best results were achieved through a combination of AI tools and human decision-making. AI accelerated research, concept development, and visualization, while human judgment ensured the final Wave Pavilion remained functional, buildable, and climate-responsive.

AI Contradictions & Critical Analysis 

AI Contradictions Identified

During the design process, differences emerged between the outputs of the AI systems.

Perplexity (Research AI) focused on environmental performance and realistic building requirements. It recommended strategies such as solar protection, natural ventilation, shaded glazing, and climate-responsive design solutions suitable for Kajang's tropical climate.

Midjourney (Image AI) focused primarily on visual impact and architectural atmosphere. It generated dramatic roof forms, large transparent façades, and highly expressive architectural images that were visually appealing but sometimes difficult to construct.

As a result, contradictions appeared between environmental performance and visual aesthetics.

Perplexity (Research AI)

Midjourney (Image AI)

Climate-responsive solutions

Dramatic architectural forms

Practical shading strategies

Large exposed glazed surfaces

Realistic environmental performance

Highly idealized visualizations

Buildable design recommendations

Occasionally unrealistic structures

Human Resolution

Human judgment was required to balance both approaches. Environmental recommendations from Perplexity were combined with the visual quality of Midjourney to create a final design that was both climate-responsive and architecturally expressive.

Final Outcome:
A Wave Pavilion that balances environmental performance, structural feasibility, and architectural identity through the integration of AI-generated research, concept development, and visualization.

Contradiction 1: Environmental Performance vs. Visual Design

The Contradiction:
Research AI recommended deep roof overhangs, shaded glazing, and controlled daylight to reduce heat gain in Kajang's tropical climate. However, the Image AI frequently generated large exposed glass surfaces and dramatic open façades that could increase solar heat gain and reduce thermal comfort.

AI Limitation:
The Image AI prioritized visual appearance and transparency over environmental performance and passive design requirements.

Contradiction 2: Structural Feasibility vs. Architectural Expression

The Contradiction:
The concept developed by the Text AI emphasized a flowing wave-shaped roof and open communal spaces. However, the Image AI often produced roof spans and cantilevers that lacked realistic structural support systems.

AI Limitation:
The Image AI focused on creating iconic forms without considering material limitations, load transfer, or construction feasibility.

Human Resolution

Resolution 1: Environmental Optimization

The final design retained the large curtain-wall glazing suggested by the visualizations but incorporated deep roof overhangs, timber shading elements, and a central courtyard. These additions reduced solar heat gain while preserving daylight and visual openness.

Resolution 2: Structural Rationalization

The wave-shaped roof was refined into a buildable glulam and steel structural system. Roof spans were adjusted, support locations were clarified, and the geometry was simplified while maintaining the architectural identity generated during the AI design process.

Final Architectural Synthesis

The final Wave Pavilion combines the environmental intelligence of the Research AI, the conceptual ideas of the Text AI, and the visual quality of the Image AI. Human judgment reconciled the contradictions between performance, aesthetics, and constructability, resulting in a climate-responsive, functional, and realistic architectural proposal.