Resources

Practical tools for figuring out whether an AI idea is useful, risky, overhyped, or just a very expensive way to avoid writing a process document.

AI Use Case Gut Check

Before you buy, build, or announce anything, ask:

• What exact job are we trying to make easier?
• What input does the AI need, and who owns that data?
• What does a good output look like?
• Who verifies the result?
• What happens when it is wrong?
• Is this automation, assistance, search, drafting, classification, or executive wishcasting?

Good AI projects tend to be boring

• Summarize long internal documents into decision briefs
• Draft standard responses for human review
• Classify incoming work and route it faster
• Extract structured data from messy text
• Generate checklists, test cases, and implementation plans
• Watch for anomalies and notify a human before the wheels exit the vehicle

Bad AI project warning signs

• “We need an AI strategy” but nobody can name the workflow.
• “It will save headcount” before anyone has measured the work.
• No one knows who checks the output.
• The demo only works with perfect inputs and a sales engineer nearby.
• Security review is treated like optional garnish.

More templates, scorecards, and checklists will land here as the site grows. Yes, a resource page with “resources coming soon” is legally required by the internet. I don’t make the rules.