Explore the varied experiences with AI, from users naturally reducing their engagement due to inaccuracies to those integrating it deeply for significant productivity gains in specific tasks and workflows.
Explore the primary reasons local LLMs haven't achieved widespread use, from hardware limitations and cost to evolving cloud privacy solutions and superior hosted model performance. Discover where local models still find their niche.
Discover why curved quotation marks (“ ”) are not a reliable 'tell' for AI-generated content. Learn about their history in typography and why the real issue is often company policy, not the tool itself.
Developers share their real-world experiences as companies push for AI adoption. Explore the spectrum of policies from forced use to outright bans, and learn where AI tools actually help versus where they hinder productivity.