$ cat ~/blog/ai-reliability-checklist-law-firms.md
An AI Reliability Checklist for Law Firms (One Page — Print It)
A printable checklist for legal AI reliability — model portability, data control, human-in-the-loop, and fallbacks. The one-pager an office manager can actually pin up.
I wrote a longer piece on what happens when a frontier model gets recalled and your firm’s tools go dark. This is the short version — the one-pager you can print, pin to a wall, and actually use. No theory, just the checks.
Before you adopt an AI tool
- Where does our data go? On-device, your cloud, or the vendor’s? Is testimony leaving the building, and does it need to?
- What model is under the hood, and can it be swapped? If the vendor’s model is recalled or deprecated, does the tool keep working?
- Is the method portable, or model-specific? Prompts and processes should survive a model change. (This is why vendor-neutral tools like CasePrompts matter.)
- Does it cite the record? Page:line on every claim, “not in the record” when it can’t. No exceptions for convenience.
For everything already in your workflow
- Human in the loop on anything accountable. A professional reviews before it leaves the firm. Always.
- A tested fallback exists. A second model — even a smaller or local one — you’ve actually verified works.
- You can run the critical path by hand. Slower is acceptable. Impossible is not.
- Continuity plan written down. If your primary AI vanishes tomorrow, the next steps are on paper, not in someone’s head.
The one-line version
Treat AI like any other tool a professional relies on: with a backup, a process, and your own hands still on the work. The firms that did this barely noticed the last recall. The firms that treated one model as load-bearing had a very bad week.
I’m building toward tools that pass this checklist by default — vendor-neutral, on-device, accountable. That’s DepoStack, and early access is open.
Want this as an actual printable PDF for your office? Tell me and I’ll make one.