Practical, reusable methods and decision guides. These articles focus on how to evaluate, verify and use tools—not on untested product verdicts.
GitHub Agentic Workflows is now generally available. Teams can describe reasoning tasks in Markdown, but approvals, permissions and compute costs still determine whether automation is dependable.
Check release status, account and regional access, pricing, product limits, privacy and evidence before repeating an AI launch claim.
Choose productivity software by testing real workflows, adoption friction, accessibility, data portability and the full cost of staying or leaving.
Trace a claim to its source, corroborate evidence, verify photos and videos, separate facts from uncertainty and correct errors transparently.
A practical guide to Google Trends topics, search terms, normalized 0–100 scores, rising queries and the limits of search-interest data.
A repeatable way to test an AI product’s usefulness, output quality, data practices, permissions, real cost and exit path before relying on it.
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