Five AI developments deserve five proper explanations—not five compressed summaries.
This edition now opens each subject at an easy, entertaining hobbyist level, then gradually moves through practical use, technical mechanics, failure modes, and the expert implication. Choose the subject that matters to you:
- Why Your AI Agent Can Look Brilliant and Still Do the Wrong Job
A friendly-to-technical guide to testing an AI agent’s goal, tool path, failure handling, authority, and real-world reliability. - Portable Agent Skills: The Recipe That Can Outlast the Model
Agent skills preserve reusable instructions, tools, references, and safeguards. Here is how they work, travel, and fail. - How to Find AI Stories Before the Headline Without Believing the Hype
Use early community and developer signals to discover AI stories—then move each clue through a disciplined verification ladder. - The Build Story Is More Valuable Than the Launch Post
A finished result gets attention. The documented failures, fixes, measurements, and limits teach readers how the work transfers. - AI Disclosure Without the Panic: A Practical Guide to Content Provenance
Start with a simple content receipt, match disclosure to risk, and understand what machine-readable provenance can—and cannot—prove.
Best use of your time today
Start with the agent-evaluation article and add one observable validation step to a workflow you already use. Then save the other four as your roadmap for skills, research, build documentation, and disclosure.