Designing for large language models requires moving beyond open-ended chatbots toward vertical, specialized interfaces that guide users through rigorous, systematic knowledge work. Maggie Appleton, lead designer at Elicit, emphasizes that AI’s true value lies in its capacity for reasoning and synthesis—helping researchers process vast amounts of literature—rather than mere content generation. Effective AI-driven design demands that practitioners understand the underlying technical materials, enabling them to build interfaces that offer reliability and human-in-the-loop verification. As low-level development tasks become automated, the role of the designer will shift toward solving complex, exploratory problems and architecting dynamic systems. Ultimately, technical literacy and the ability to articulate problems clearly remain essential for designers to navigate an evolving landscape where AI handles the grunt work while humans focus on high-level conceptual strategy.
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