Person profile
Associate Professor; AI researcher at Wharton (UPenn).
Tools Ethan Mollick has publicly discussed or demonstrated using. Curated by Magpie's editorial team from podcasts, posts, and public stacks.
Ethan Mollick is Associate Professor at the Wharton School and Co-Director of the Wharton Generative AI Labs. He writes One Useful Thing, a Substack with hundreds of thousands of readers, where he names the AI tools he uses, why, and what they're good for.
Mollick names Claude as one of three systems he recommends to anyone serious about using AI, alongside ChatGPT and Gemini. His 'Using AI Right Now: A Quick Guide' essay frames the three as the canonical default-stack for serious users. He calls out Claude (especially Sonnet and Opus) as one of his most-used assistants in nearly every comparison essay, and his 'Claude Code and What Comes Next' essay treats Claude Code as a category-defining shift in agentic coding.
Mollick names ChatGPT as one of three AI systems he recommends for anyone serious about using AI alongside Claude and Gemini. His comparative essays test ChatGPT against the other two on advanced and fast modes, voice, image generation, document handling and Deep Research, treating ChatGPT as the canonical reference point for what a serious AI assistant looks like.
Mollick uses Gemini especially for long-context tasks like reviewing entire documents at once and counts it as one of his three recommended AI systems. His comparative essays benchmark Gemini against Claude and ChatGPT, with particular attention to where Google's context-window advantage translates into real workflow gains for educators and analysts.
Mollick has written multiple essays praising NotebookLM's grounded-on-source workflow for research and teaching prep, including its audio-overview feature. He frames NotebookLM as the right tool when you want LLM synthesis that's strictly grounded in documents you provide rather than the broader pretraining set.
Mollick uses Midjourney for image generation in essays and demonstrations. He's documented prompt-engineering experiments and the model's evolution across versions, treating Midjourney as the canonical example of how generative tools shift the cost curve for visual content production.
Last researched May 10, 2026
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