Copilot at Work: How Generative AI is Quietly Rewriting Job Descriptions
A mechanism-first reading of Microsoft’s Copilot usage study, showing how generative AI maps onto real work activities without pretending that applicability equals automation.
Cognaptus Insights
Industry thoughts, trends, and commentary.
Echo Chamber in a Prompt: How Survey Bias Creeps into LLMs
A field guide to why LLM-generated survey responses are fragile, biased, and useful only when treated as instruments to validate rather than respondents to trust.
The Bullshit Dilemma: Why Smarter AI Isn't Always More Truthful
A mechanism-first reading of why alignment for user satisfaction can make language models more persuasive while making them less committed to truth.
Humans in the Loop, Not Just the Dataset
A practical reading of why AI-assisted monitoring tools need feedback infrastructure, not just better classifiers.
Jolting Ahead: Why AI’s Acceleration Is Accelerating
A mechanism-first reading of the Jolting Technologies Hypothesis: useful as an early-warning framework, not yet proof that AI capability curves are already superexponential.
The Invisible Hand in the Machine: Rethinking AI Through a Collectivist Lens
Michael I. Jordan’s paper argues that AI systems should be designed less like isolated minds and more like markets of people, data, incentives, uncertainty, and local knowledge.
Delta Force: How Weak Models are Secretly the Best Teachers
A mechanism-first look at why preference tuning can extract strong gains from weak model pairs, and where the shortcut stops working.
From Prompting to Porting: Surviving the LLM Upgrade Cycle
A case-first analysis of why production LLM prompts need migration discipline, not just better wording, when model versions change.
School of Thought: How Fine-Tuned Open LLMs Are Challenging the Giants in Education
A comparison-based read of how fine-tuned open models can rival proprietary LLMs for narrow educational feedback tasks—without pretending they have conquered tutoring.
The Trojan GAN: Turning LLM Jailbreaks into Security Shields
CAVGAN shows that LLM jailbreaks and defenses may be two sides of the same hidden-representation boundary problem.