Ethan Mollick
22 Intel
Ethan Mollick is an associate professor of management at the Wharton School, University of Pennsylvania, where he researches the effects of AI on work, entrepreneurship, and education, and co-directs Wharton's Generative AI Labs. He holds a bachelor's degree from Harvard and an MBA and PhD from MIT Sloan. He is the author of the New York Times bestseller "Co-Intelligence: Living and Working with AI" (2024), writes the newsletter "One Useful Thing," and was named one of TIME's 100 Most Influential People in AI in 2024.
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Intel
An explanatory guide that breaks down how to choose AI tools in 2025 by understanding three layers: models (the AI brains), apps (products you use), and harnesses (systems that let AI take actions and complete tasks). It walks through the current landscape of ChatGPT, Claude, and Gemini and their various coding agents and desktop tools.
An essay by Ethan Mollick analyzing why AI capabilities improve unevenly (the 'jagged frontier') and how single bottlenecks hold back entire systems until they suddenly break through. Uses Google's Nano Banana Pro image model as a case study for how solving one weakness can unlock a wave of new capabilities.
An essay by Ethan Mollick (Wharton Generative AI Lab) exploring how AI can help or hurt human thinking across learning, creativity, and teamwork. It debunks the 'AI causes brain damage' fear and offers practical strategies plus prompts for using AI without outsourcing your thinking.
Ethan Mollick on the chatbot receding as the main way people meet AI, as capability gains accelerate and the frontier stays jagged even while release cadence quickens.
An argument that the live question is no longer what AI can do but who holds the initiative to act, built around the Hugging Face Incident from July and the METR, Redwood and OpenAI accounts of it, and what the pattern implies for how much autonomy teams hand their agents.
An essay exploring whether AI agents can navigate messy, undocumented organizational processes by training on outcomes rather than encoding human expertise. It connects Richard Sutton's 'Bitter Lesson' and the 'Garbage Can Model' of organizations to argue enterprise AI adoption may not require mapping chaotic workflows.
Mollick argues today's models like GPT-6 Astra and Fable 5.1 are already capable of weeks of guided human-equivalent work, pointing to a demo where GPT-6 Astra rebuilt the text adventure Zork as a playable 3D game by inferring visuals and mechanics from prose alone.
An essay by Ethan Mollick exploring how the nature of working with AI is shifting from collaborative 'co-intelligence' to a 'wizard' model, where AI produces sophisticated outputs through opaque processes that users can only verify, not shape.
An essay by Ethan Mollick analyzing the current state of AI, arguing that we've entered an era of managing AI agents rather than working alongside them. It explores exponential AI capability gains, radical new organizational structures like AI-only 'software factories,' and the looming reality of recursive self-improvement.
An early-access account of Claude 5 Fable, the first Mythos-class model: runs stretching to a dozen hours against multi-page specifications, a clear jump over prior models across varied tasks, and guardrails that wall it off from cybersecurity work.
An analytical essay by Ethan Mollick (One Useful Thing) examining how AI agents have crossed a threshold into performing economically valuable tasks. It explores OpenAI's expert task benchmark, uses Claude Sonnet 4.5 to reproduce academic research, and argues that the future of work depends on how thoughtfully we deploy AI.
GPT-5 is OpenAI's flagship AI model that automatically selects the right reasoning level for each task and proactively takes action on vague prompts. It can generate startup plans, build functional apps, create documents, and 'just do stuff' with minimal user guidance.
Claude Code is an agentic AI coding tool powered by Claude Opus 4.5 that works autonomously on your computer and files. It can plan, write, and deploy entire software projects for hours at a time, using tricks like context compaction, Skills, subagents, and MCP integrations to overcome LLM limitations.
Ethan Mollick's early evaluation of Gemini 4: a major jump that reaches the top tier, with distinct taste and better agentic behavior, but overconfidence, laziness and weaker complex multi-agent performance, partly due to its harness.
An article examining how AI interfaces shape usability, highlighting Anthropic's Claude Cowork (a Claude Code variant for knowledge workers) and its Dispatch feature, which lets you control an AI agent on your desktop from your phone via QR code. It explores why chatbot interfaces impose cognitive load and how specialized or on-demand interfaces unlock AI's real capabilities.
Antigravity is Google's agentic coding tool built on the Gemini 3 model, letting you assign tasks to autonomous AI agents in plain English that write code, build sites, run research, and check in for approval. It functions as a general-purpose 'digital coworker' that can do almost anything on your computer, not just program.
An essay by Ethan Mollick arguing that organizations should evaluate AI models like job candidates rather than relying on public benchmarks. It explains why standardized benchmarks fall short and offers practical approaches like vibes-testing, real-world task benchmarking (GDPval), and probing an AI's judgment on ambiguous business questions.
An analytical essay by Ethan Mollick (One Useful Thing) exploring how powerful AI is becoming as accessible as a Google search, covering the economics, ease of use, and societal implications of a billion people gaining access to advanced models like GPT-5 and Gemini's 'nano banana' image generator.
An essay by Ethan Mollick exploring how to use AI thoughtfully for writing and learning without surrendering the cognitive work that builds real skill. It draws on research studies to distinguish AI use that shortcuts thinking from AI use that strengthens it.
Ethan Mollick revises his view that managing agents requires careful organizational design, arguing the Bitter Lesson applies: models now plan, seek information and coordinate themselves, making elaborate human scaffolding less valuable.
The promotional website for Ethan Mollick's book 'Co-Existence,' notable for including a dedicated version of the page addressed to AI agents that read on behalf of human users. The site was built with Claude Code and A/B tested against dozens of AI models to optimize how it presents to both humans and AI readers.
A practical comparison guide for choosing between ChatGPT and Claude's agentic modes (Work/Cowork and Codex/Code), explaining how to pick models and thinking levels, when to give an AI access to your own computer versus a company-provided one, and how to manage permissions against risks like prompt injection. It also covers where Google, Microsoft Copilot, and Chinese open-weight models fit in, and notes gaps in image, video, and voice capabilities across the major AI systems.