Lightning-Fast Prototyping with AI: Rapid Prototyping Experiments Under Time Constraints

2. Direct Prototyping

• Initial Sync: Aligns and consolidates ideas, especially when working with cross-functional teams bringing different perspectives. This stage unifies flows, structure, and scenarios as the concept foundation. It also discusses new AI-enabled working methods and team role distribution.
• Feedback Session: Focus on flow and experience through live prompting, not component design. Since prototypes are immediately clickable, review and iteration can happen in real-time, both asynchronously and through direct sessions.

3. Special Case: Concept for Data Team Exploration Needs
The process is generally similar, but in some cases, generated concepts don't focus on usability or high-fidelity since the target is internal needs. For example, testing engines without involving engineering teams. Such situations require additional processes to ensure outputs remain relevant and meet team expectations.

4. Further Alignment on "Speed" Concept: As part of evaluation, we also realigned the concept of "speed," assessing whether tools and approaches truly support required time efficiency. This led to exploring alternative tools better suited for this context, such as collaboration with data teams using Streamlit and Cursor.

Impact & Reflections

⇢ Impact

Positive Impact:

• Validation processes became significantly faster and more efficient
• For design teams, repetitive work was minimized. Emerging ideas became sharper and more relevant as AI became part of the team's thinking process
• Confidence levels increased as AI became an active thinking partner
• In cross-functional collaboration, feedback became faster and focused on essential matters. Everyone could easily visualize their ideas

Risks of Speed:

Iterations can happen too quickly without reconsidering the direction and intent of the product being built. Designs can be continuously generated, feedback can be immediately fed back to AI, but we risk losing grounding in the main objective

⇢ Reflections

• Speed is good, but we still need to think and return to users. Taking breaks in the process is important. Don't make AI the primary decision-maker, we as designers must remain the directors. This redefines the meaning of a designer's role.
  Always trace back the origins of inputs we receive. Ensure implemented feedback doesn't just come from one stakeholder, but considers user needs comprehensively.
• Prompting is a skill that needs strategic development. Even tools like ChatGPT can become thinking partners in crafting more targeted and contextual prompts.
• Don't get lost in the abundance of available AI tools. Focus energy on the main objectives you want to achieve in the project, not just trying every available tool.