An analysis of the creative ideas, such as a lightweight UI, versus the serious legal risks, like cybersquatting, that come with owning a domain containing a major brand's trademark.
Explore strategies for addressing a colleague's overuse of unedited, low-quality AI in user communications, from direct confrontation to a subtle inquiry about company policy.
Experienced software engineers discuss the real impact of AI on their careers, offering practical advice on how to adapt, specialize, and find meaning beyond the hype.
An analysis of the modern university's credibility, exploring the tension between its role as a job credential versus a place for learning, and the impact of AI on employer trust.
Have a box full of unused tech swag? Explore practical tips for donating, repurposing, and preventing future clutter, and understand the psychology behind why companies give out these free items.
Discover why AI models tend to be conservative, from their training data mirroring our world to the deliberate safety and commercial controls placed upon them. Learn how you can even make a local AI more unpredictable.
Explore the core reasons for skepticism surrounding Large Language Models, moving beyond simplistic explanations to address technical limitations, ethical concerns, and the gap between hype and practical reality.
Exploring the use of AI to draft legal documents to save on high lawyer fees. Learn about the significant risks involved, safer DIY alternatives, and a novel (but complex) AI workflow.
Discover how tech professionals' perspectives on AI have shifted from initial skepticism to practical application. Learn how they leverage it as a tool for specific coding tasks while remaining cautious about its hype and limitations.
Struggling to earn an income from your open-source project? Explore four distinct monetization strategies, from selling services and support to dual-licensing and corporate sponsorships.