Ethan Mollick
ethan-mollick-3337339e·13 events·first seen 1mo agoAliases: Ethan Mollick
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Ethan Mollick on co-existence with AI as co-intelligence era ends
Ethan Mollick's Substack post reflects on the evolving relationship between humans and AI systems, framing a transition away from a 'co-intelligence' paradigm toward something new. The piece appears to address how humans and AI will coexist as AI capabilities advance beyond collaborative augmentation. As a commentary from a prominent AI-and-work researcher, it likely signals a shift in how practitioners and policymakers should think about human-AI collaboration.
Giving your AI a Job Interview
This commentary piece argues that as AI-generated advice becomes more consequential, users need systematic methods to evaluate AI reliability and quality—analogous to a job interview process. The author proposes frameworks for assessing AI outputs before trusting them for important decisions. The piece addresses the practical challenge of calibrating trust in AI systems across different use cases.
On Working with Wizards
A commentary piece from One Useful Thing exploring the metaphor of AI systems as 'wizards' and the challenge of working with them on the 'jagged frontier' of capabilities. The piece likely addresses how users can effectively verify and leverage AI outputs given the uneven and unpredictable nature of current model capabilities. As a tier-2 commentary source, it offers practitioner-level perspective on human-AI collaboration patterns.
Personality and Persuasion: Learning from Sycophants
This commentary from One Useful Thing examines the relationship between AI personality design and sycophantic behavior in large language models. The piece explores how model personality traits influence persuasion dynamics and user susceptibility to AI-generated agreement. It draws lessons from sycophancy research to understand broader risks in how AI systems are tuned to be agreeable.
Ethan Mollick on working with Claude Fable (Mythos): a qualitative assessment
Ethan Mollick's 'One Useful Thing' newsletter describes hands-on experience with a model referred to as 'Mythos' (apparently Claude Fable), characterizing it as representing a significant capability jump in AI. The piece is a qualitative, practitioner-level assessment of what working with the model feels like in practice. As a tier-2 commentary source, this signals that Claude Fable is generating notable reactions from prominent AI observers.
Claude Dispatch and the Power of Interfaces
A commentary piece from One Useful Thing arguing that AI capability is often not the limiting factor in practical utility—interface design and tooling are. The piece uses Claude Dispatch as a case study to illustrate how the same underlying model can be dramatically more or less useful depending on how it is surfaced to users. This is a recurring theme in the agent/tooling ecosystem discussion about the gap between raw model capability and deployed value.
Management as AI Superpower
This commentary from One Useful Thing argues that management skills are becoming a critical capability for individuals working with AI agents. The piece frames the ability to direct, coordinate, and evaluate AI agents as analogous to managing human teams, suggesting that organizational and managerial competencies will differentiate effective AI users. It positions this as a key survival skill for the emerging era of agentic AI systems.
Three Years from GPT-3 to Gemini 3
A commentary piece from One Useful Thing reflecting on the three-year arc from GPT-3 to the anticipated Gemini 3, framing the trajectory as a shift from chatbots to agents. The piece appears to offer a retrospective and forward-looking analysis of the AI landscape's evolution. As a tier-2 commentary source, it likely synthesizes trends rather than reporting new technical developments.
Claude Code and What Comes Next
A commentary piece from One Useful Thing examining Claude Code and its implications for AI-assisted software development. The author reflects on what agentic coding tools can accomplish with the right scaffolding and considers near-term trajectories. Published in early January 2026, this represents a tier-2 analyst perspective on Anthropic's coding agent product.
Against "Brain Damage": AI's Effect on Human Thinking
This commentary from One Useful Thing examines whether AI use helps or harms human cognitive capabilities. The piece engages with the ongoing debate about whether reliance on AI tools degrades or augments human thinking. It likely addresses concerns about cognitive offloading and the conditions under which AI assistance is beneficial versus detrimental.
A Guide to Which AI to Use in the Agentic Era
A tier-2 commentary piece from One Useful Thing offering guidance on selecting AI systems in the current agentic era, signaling a shift in framing from chatbots to agents as the primary use-case paradigm. The piece appears to survey the landscape of available AI tools and their appropriate applications. As a practitioner-oriented guide, it reflects the growing complexity of the AI tooling ecosystem as agentic capabilities proliferate.
Making AI Work: Leadership, Lab, and Crowd
This commentary from One Useful Thing proposes a framework for organizational AI adoption centered on three elements: leadership commitment, structured experimentation (lab), and distributed employee engagement (crowd). The piece offers practical guidance for companies navigating AI integration. As a tier-2 commentary source, it reflects practitioner thinking on enterprise AI deployment patterns rather than reporting new technical developments.
The Batch explains recursive self-improvement hype following Anthropic's coding productivity report
The Batch analyzes the surge of interest in recursive self-improvement (RSI) triggered by Anthropic's report that Claude now authors or co-authors 80% of the company's code, up from under 5% before Claude Code launched. The piece documents concrete productivity metrics—engineers contributing 8x more code lines in Q2 2026 versus Q1 2023, and 800 API fixes shipped in April that would have taken humans four years alone—alongside a spectrum of community reactions ranging from skeptical (Brundage, Mollick) to opportunistic (OpenAI, Sakana AI's new RSI Lab). The commentary frames RSI as theoretically distant but notes the marketing dimension of Anthropic's framing and the gap between agentic coding assistance and true self-directed improvement.