Ethan Mollick

Highlights: Opus 4.7 produces the best results when it decides to think.

Worth reading: Highlights a key improvement in AI reasoning capabilities.

Highlights: References Searle's Chinese Room thought experiment to discuss AI understanding.

Worth reading: Connects classic philosophy to modern AI debates.

Highlights: Discusses AI ethics and potential of AI companies.

Worth reading: Addresses ethical considerations in AI development.

Highlights: Notes emerging nuanced discussions about working with advanced AI.

Worth reading: Reflects on the evolving human-AI collaboration landscape.

Highlights: Mollick argues that heavy AI users can recognize AI writing intuitively, but struggle to prove it objectively, highlighting the limitations of AI detection.

Worth reading: It exposes the gap between subjective AI recognition and objective proof, a key issue in AI evaluation.

Highlights: Mollick references Searle's Chinese Room argument, likely to discuss implications for AI understanding and consciousness.

Worth reading: Connects classic philosophy to modern AI debates about whether LLMs truly understand language.

Highlights: Discusses emerging nuanced conversations about collaborating with advanced AI.

Worth reading: Highlights a shift in AI discourse from hype to practical collaboration.

Highlights: Notes that Opus 4.7, when it engages in reasoning, yields superior outputs.

Worth reading: Provides insight into model performance variability and reasoning quality.

Highlights: Observes that top business students are hired for their uniquely human skills.

Worth reading: Illustrates the enduring value of human skills in an AI-driven world.

Highlights: Warns that prompt tuning will lead to escalating demands and expectations.

Worth reading: Highlights a growing challenge in prompt engineering and user behavior.

Highlights: AI as a personalized tutor is a high-impact use case; OpenAI should invest in tutoring.

Worth reading: Highlights a key ethical and practical application of AI in education.

Highlights: References Searle's Chinese Room argument to discuss AI understanding.

Worth reading: Connects classic philosophy to modern AI debates.

Highlights: Prompt tuning can make AI writing indistinguishable from human writing, challenging our assumptions about effort and value.

Worth reading: Highlights an emerging challenge in AI-generated content detection.

Highlights: Ethan Mollick criticizes Claude Opus 4.7's adaptive thinking for misclassifying non-math/code tasks as low effort, leading to worse results.

Worth reading: Highlights a key limitation in AI effort routing that affects practical usage.

Highlights: Mollick humorously references the Chinese Room thought experiment with a physical implementation using GPT-1.

Worth reading: Illustrates the philosophical implications of AI through a practical joke.

Highlights: Tweet with 124 likes and 7 replies, but content not fully captured.

Worth reading: Shows engagement but lacks substantive content.

Highlights: Mollick praises Opus 4.7's thinking capability for producing the best results.

Worth reading: Highlights a specific AI model's strength in reasoning.

Highlights: Mollick argues that AI as a personalized tutor is a top use case for societal good.

Worth reading: Provides a mission-driven perspective on AI's educational potential.

Highlights: Analysis of submissions to a major management journal reveals interesting patterns.

Worth reading: Provides insight into academic publishing trends in management research.

Highlights: Discusses emerging nuanced perspectives on collaborating with advanced AI.

Worth reading: Captures the evolving conversation around human-AI collaboration.

Highlights: Opus 4.7, when engaged, yields superior results compared to other models.

Worth reading: Highlights performance differences in AI models depending on usage.

Highlights: Proposes a thought experiment implementing the Chinese Room argument with GPT-1.

Worth reading: Connects philosophical AI concepts with practical implementation.

Highlights: Critique of efforts to simulate continual learning and memory in AI, implying it may be misguided.

Worth reading: Raises important questions about the direction of AI research and the value of genuine vs. simulated capabilities.

Highlights: Brief expression of concern, likely about an AI development.

Worth reading: Shows the author's reaction to a notable event, inviting curiosity about context.

Highlights: AI demonstrates capability in generating ideas, not just analysis.

Worth reading: Challenges the notion that AI is only good at analytical tasks, suggesting broader creative potential.

Highlights: Debate with OpenAI about AI's ability to handle organizational dynamics.

Worth reading: Raises important questions about AI's limitations in complex social and organizational contexts.

Highlights: Discusses AI's potential for personalized good, though snippet is cut off.

Worth reading: Highlights the ethical dimension of AI deployment for societal benefit.

Highlights: Careful prompt tuning can make AI writing indistinguishable from human writing, challenging our assumptions about effort and value.

Worth reading: Highlights a key psychological barrier to AI adoption in writing tasks.

Highlights: Critiques the focus on simulating continual learning and memory in AI systems.

Worth reading: Raises questions about the authenticity of AI capabilities.

Highlights: Notes that Opus 4.7 can produce excellent results when it engages in reasoning.

Worth reading: Indicates that advanced models can excel when properly utilized.

Highlights: Critiques the effort to simulate continual learning and memory in AI systems.

Worth reading: Highlights a key debate in AI research about genuine vs. simulated capabilities.

Highlights: Early access to GPT-5.4 and Pro shows significant progress.

Worth reading: Provides insight into the capabilities of upcoming AI models.

Highlights: Opus 4.7 produces the best results when it decides to think.

Worth reading: Highlights a key improvement in AI reasoning capabilities.

Highlights: Role prompting does not significantly improve AI accuracy on physics questions.

Worth reading: Challenges the effectiveness of simple role-based prompts for complex tasks.

Highlights: Criticizes two poor forms of AI posting and misinterpretation in a quote tweet.

Worth reading: Illustrates common pitfalls in AI discourse on social media.

Highlights: Mollick comments on the AI bubble discussion, noting the 'this time is different' sentiment.

Worth reading: Provides perspective on AI hype cycles.

Highlights: Mollick praises Opus 4.7 for producing the best results when it engages in reasoning.

Worth reading: Highlights a specific AI model's capability.

Highlights: Mollick notes the emergence of nuanced discussions about working with advanced AI.

Worth reading: Signals evolving discourse on human-AI collaboration.

Highlights: Critiques efforts to simulate continual learning and memory in AI, implying it may be superficial.

Worth reading: Highlights a key debate in AI research about genuine vs. simulated capabilities.

Highlights: Reports early access to advanced AI models, noting significant progress.

Worth reading: Provides firsthand insight into cutting-edge AI model capabilities.

Highlights: Notes that human skills remain valuable in finance despite AI advances.

Worth reading: Offers perspective on the enduring value of human judgment in an AI-driven world.

Highlights: Opus 4.7 produces the best results when it decides to think.

Worth reading: Highlights a key improvement in AI reasoning capabilities.

Highlights: Reflects on the profound impact of AI on people's lives.

Worth reading: Offers a human-centric perspective on AI's societal implications.

Highlights: Notes the emergence of nuanced discussions about working with advanced AI.

Worth reading: Signals a shift in the AI discourse toward practical collaboration.

Highlights: Early access to GPT-5.4 and Pro shows significant progress.

Worth reading: Provides a firsthand look at cutting-edge AI model improvements.

Highlights: Ethan Mollick praises Opus 4.7 for producing the best results when it decides to think.

Worth reading: Shows his perspective on a specific AI model's performance.

Highlights: Reflects on the profound impact of AI on people's lives.

Worth reading: Highlights the human dimension of AI deployment.

Highlights: Emphasizes the significance of industry-defined hard tasks for AI.

Worth reading: Indicates a breakthrough in AI evaluation benchmarks.

Highlights: Mollick humorously suggests using a printed GPT-1 to run the Chinese Room thought experiment, highlighting the impracticality of simulating AI manually.

Worth reading: It illustrates the scale and complexity of modern AI systems through a clever thought experiment.

Highlights: Mollick notes the trend of building systems that simulate continual learning and memory in AI, questioning the authenticity of such approaches.

Worth reading: It raises critical questions about the direction of AI development and the value of genuine vs. simulated capabilities.

Highlights: Mollick uses creative AI demos like converting cover letters into poetry to showcase AI's flexibility and engage audiences.

Worth reading: It demonstrates a practical, engaging way to present AI capabilities beyond typical use cases.

Highlights: Mollick observes that top business students are valued for their uniquely human skills, even in an AI-driven world.

Worth reading: It underscores the enduring importance of human judgment and creativity alongside AI.

Highlights: Ethan Mollick humorously describes a thought experiment implementation of the Chinese Room using a printed GPT-1, highlighting the impracticality of running it manually.

Worth reading: It illustrates the philosophical implications of AI and the Chinese Room argument in a tangible way.

Highlights: Mollick points out that even advanced AI models like GPT-5 do not believe in the existence of something, likely referring to a specific concept or fact.

Worth reading: It reveals limitations in AI's understanding or training data.

Highlights: Mollick criticizes the focus on simulating continual learning and memory in AI rather than achieving genuine capabilities.

Worth reading: It highlights a key debate in AI research about authenticity vs. performance.

Highlights: Mollick engages in discussions about AI ethics and the potential of AI technologies.

Worth reading: It reflects ongoing conversations about responsible AI development.

Highlights: Critiques the effort spent on simulating continual learning and memory in AI systems.

Worth reading: Highlights a potential misdirection in AI research priorities.

Highlights: Even an AI expert finds the pace of AI development overwhelming.

Worth reading: Emphasizes the rapid acceleration of AI progress.

Highlights: Notes common phrases that emerge from heavy AI use.

Worth reading: Observations on how AI influences language and thinking patterns.

Highlights: Profile page, not a tweet.

Worth reading: Not a tweet.

Highlights: Analysis of management journal submissions reveals interesting patterns.

Worth reading: Provides insight into academic publishing trends.

Highlights: Opus 4.7 produces best results when it decides to think.

Worth reading: Highlights a key feature of the AI model Opus 4.7.

Highlights: Industry experts identified important real-world tasks for AI.

Worth reading: Shows practical AI applications being prioritized.

Highlights: Analysis of management journal submissions reveals interesting trends.

Worth reading: Provides insight into academic publishing and research trends.

Highlights: Opus 4.7 produces best results when it decides to think.

Worth reading: Highlights performance of a specific AI model.

Highlights: AI impacts real lives, for better or worse.

Worth reading: Reflects on the human impact of AI.

Highlights: Analysis of submissions to a major management journal revealing trends.

Worth reading: Provides insight into academic publishing patterns in management research.

Highlights: Experiment using Claude Cowork on a set of 107 documents.

Worth reading: Demonstrates practical application of AI for document analysis.

Highlights: Opus 4.7 produces best results when it decides to think.

Worth reading: Highlights performance characteristics of Opus 4.7 model.

Highlights: Reflection on AI's impact: everything around is someone's life.

Worth reading: Offers a philosophical take on AI's pervasive influence.

Highlights: Ethan tested Claude Cowork on a large set of documents and shared initial results.

Worth reading: Shows practical application of AI in document analysis.

Highlights: Ethan notes that Opus 4.7 produces the best results when it decides to think.

Worth reading: Highlights the importance of model reasoning capabilities.

Highlights: Ethan observes emerging nuanced discussions about working with advanced AI.

Worth reading: Reflects evolving understanding of human-AI collaboration.

Highlights: Ethan shares analysis of submissions to a management journal, showing AI's impact.

Worth reading: Demonstrates AI's influence on academic publishing.

Highlights: Analysis of management journal submissions reveals significant patterns.

Worth reading: Provides insight into academic publishing trends in management.

Highlights: Testing Claude Cowork with a large set of documents to see how it handles multi-format data.

Worth reading: Demonstrates practical use of AI for document analysis.

Highlights: Nuanced discussions emerging about working with advanced AI.

Worth reading: Highlights evolving perspectives on human-AI collaboration.

Highlights: Business school students are hired for their human skills that complement AI.

Worth reading: Shows the value of uniquely human skills in an AI-driven world.

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Worth reading: No content available.

Highlights: Testing Claude Cowork with a large set of documents.

Worth reading: Shows practical use of AI for document analysis.

Highlights: Nuanced discussions on working with advanced AI.

Worth reading: Reflects evolving understanding of human-AI collaboration.

Highlights: Students hired for uniquely human skills despite AI.

Worth reading: Highlights enduring value of human judgment.

Highlights: Remarkable findings about model behavior.

Worth reading: Important for understanding model capabilities and risks.

Highlights: Industry experts can create better AI skills than defaults with effort.

Worth reading: Highlights the importance of customizing AI skills for domain expertise.

Highlights: Tested Claude Cowork on a large document set.

Worth reading: Demonstrates practical use of AI for document analysis.

Highlights: Notes emerging nuanced discussions on working with advanced AI.

Worth reading: Reflects evolving understanding of human-AI collaboration.

Highlights: Business school students are hired for their human judgment skills.

Worth reading: Shows the value of uniquely human skills in an AI-driven world.

Highlights: Highlights variability in human analysis of same data.

Worth reading: Illustrates the challenge of reproducibility in research.

Highlights: Ethan Mollick notes that AI can generate good ideas, challenging the notion that creativity is exclusively human.

Worth reading: It suggests AI's potential in creative tasks, which has implications for innovation and problem-solving.

Highlights: Mollick reflects on viral AI content, noting that fabricated graphs gained high engagement.

Worth reading: It highlights the challenge of misinformation and audience behavior in AI discourse.

Highlights: Mollick criticizes efforts to simulate continuous learning and memory in AI models.

Worth reading: It points to a potential misdirection in AI research, emphasizing genuine progress over superficial features.

Highlights: Mollick notes that human judgment remains valuable, as his students are hired for their unique human skills.

Worth reading: It underscores the enduring importance of human expertise in an AI-driven world.

Highlights: AI is good at generating ideas.

Worth reading: Challenges the notion that AI lacks creativity.

Highlights: AI is capable of generating good ideas.

Worth reading: Challenges the notion that AI only handles routine tasks.

Highlights: Ethan Mollick asserts that AI performs well in generating ideas, challenging the notion that AI is only good at analytical tasks.

Worth reading: It provides a concise insight into AI's creative capabilities from a leading academic.