Saturday, May 16, 2026 · ISSUE
Your Personal AI Insurance Policy
1,300 court cases prove generic just verify it advice does not work. Build yours in 5 questions.
Your Personal AI Insurance Policy
1,300 court cases prove generic "just verify it" advice doesn't work. Build yours in 5 questions.
AI Super Simplified
May 16, 2026
Most AI agents demo well. Few ship real work.
Most AI agents can run a task. The problem is everything around it: setup, memory, context, cost, and figuring out what actually happened.
Built for founders, operators, and marketers who want AI to ship work, not become another tool to babysit.
Friday we wrote about the lawyer who just lost his license for trusting ChatGPT. Today we write about the system he didn't have.
Since 2023, the Charlotin tracker has documented 1,300+ court cases where someone used AI output containing fabricated facts — citations, statutes, quotes, precedents. Roughly 800 came from US courts. The largest sanction so far: $109,700, in Oregon.
The cases aren't all lawyers. There's a marketing manager who briefed a CEO using an invented industry benchmark. A financial advisor who quoted a regulation that doesn't exist. An analyst whose Q3 deck was anchored to a fabricated competitor stat. Most never make the news. They show up as quiet firings, lost accounts, and stalled careers.
What every case has in common: confident AI output → trusted user → no verification → consequences. The chain is identical. Only the price tag changes.
TLDR
The AI that got a lawyer sanctioned six figures is the same AI getting marketers, advisors, and analysts in trouble for smaller-but-real reasons every day. But verification protocols can't be generic — a courtroom audit looks nothing like a client-email scan. Today's prompt designs YOUR protocol in 5 questions, calibrated to your work, your audience, and your worst-case scenario. Run time: about a minute. Use time: every AI output, forever.
AI Doesn't Lie. It Lies Confidently.
That's the part that makes it dangerous.
AI doesn't say "I'm guessing." It states facts in the same calm, polished tone whether the fact is real or invented. There is no detectable difference between "the Federal Reserve raised rates by 25 basis points last quarter" (which you can verify in 4 seconds) and "Section 412(b)(2) of the Securities Act prohibits…" (which may be entirely fictional).
Your brain registers both as authoritative because they sound identical. That's not a bug AI vendors will fix soon — it's structural to how language models work. They're built to sound right, not to be right. Even the best frontier models hallucinate on a meaningful percentage of factual queries. The rate gets lower every release. It will never reach zero.
Which means the responsibility for catching hallucinations falls entirely on the human pressing send. Every time. Forever.
Why "Just Check It" Fails Almost Everyone
The default advice — "always verify AI output" — fails for the same reason every generic productivity tip fails: it ignores your context.
A lawyer running a citation audit needs 15+ minutes per brief. A copywriter pitching client subject lines has 90 seconds. A regulator-facing financial advisor needs a totally different checklist than an internal analyst writing a status update. Telling all four of them the same thing — "verify your AI" — guarantees three of them won't.
A USEFUL VERIFICATION PROTOCOL HAS THREE PROPERTIES
1Calibrated to your worst-case. Lawsuit ≠ embarrassment ≠ wrong tone.
2Calibrated to your work type. Research differs from writing differs from code.
3Calibrated to your time budget. Under-1-min and 15+-min protocols look completely different.
Generic advice gives you none of those. That's why most professionals don't actually verify — the advice they've been handed is either too heavy to follow or too vague to apply. So they ship. And every time they get away with it, the bar for the next time drops a little lower. Until it doesn't.
The Fix: A Protocol Built for You
The prompt below interviews you in five questions — work type, audience, worst-case scenario, top fear, time budget — then designs a verification protocol calibrated to your exact situation.
It produces:
- A 3-step verification protocol matched to your time budget
- The specific questions to ask AI before trusting any output
- A red-flag checklist tuned to your failure mode
- One concrete example applied to your real workflow
Run it once. Save the output. Use it on the next AI draft you send.
You are a senior compliance officer designing a personal AI verification protocol. Before giving any output, INTERVIEW me with these questions ONE AT A TIME, waiting for my answer before asking the next: 1. What kind of work do you use AI for most often? (e.g., research, writing, code, client-facing content, internal analysis, customer responses) 2. Who is the final reader of what you produce with AI? (clients, the public, your boss, regulators, internal team) 3. What's the worst-case consequence if AI fabricates something and you don't catch it? (embarrassment, lost client, lawsuit, fired, regulatory fine, no big deal) 4. What AI mistake do you fear most — what would you most want a system to catch before you publish or send? 5. How much time can you realistically spend on verification per AI output? (under 1 minute, 1-5 minutes, 5-15 minutes, more than 15) After all 5 answers, design me: - A 3-step verification protocol tailored to my exact work and risk tolerance - The specific questions I should ask my AI BEFORE trusting any output it gives me - A "red flag" checklist of things that should make me pause and verify manually - One concrete example of how to apply this to a real task in my workflow Be specific. No generic advice. The protocol should feel like it was built for me — because it was.
Below is what the same prompt produced for four very different professionals — same five questions, wildly different protocols.
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PROMPT PROOF
Same Prompt. Four Professions. Four Protocols.
Color-coded by hallucination risk. Find your row.
| PROFILE | WORST CASE | PROTOCOL THE PROMPT BUILT | TIME / RISK |
|---|---|---|---|
Lawyer Legal briefs · Court filings | Sanctions, license suspension, malpractice suit | Citation-by-citation audit. Pull every case cited. Confirm in Westlaw/LexisNexis. Flag anything not in primary sources. Never paste AI output into a brief without independent verification of every authority. | 15+ MIN · CRITICAL |
Financial Advisor Client comms · Compliance docs | Regulatory fine, FINRA action, lost AUM, lawsuit | Compliance scan. Verify every regulation cited against SEC/FINRA databases. Confirm rates, contribution limits, and tax thresholds against current IRS publications. Flag any forward-looking projection AI produced without your data. | 5–15 MIN · HIGH |
Marketing Manager Client decks · Campaign copy | Embarrassment in front of CEO, lost client, fired | Fact-spot scan. Highlight every number, percentage, named company, and "industry standard" claim. Verify any stat AI produced without you supplying it. Soften "always," "everyone," and "the data shows" into "based on what we've seen…" | 1–5 MIN · MEDIUM |
Internal Analyst Status updates · Personal notes | Awkward Monday meeting, bad decision, wasted hour | Sanity check. Read once. Does anything contradict what you already know? Does any number look suspiciously round? If yes, verify. If no, ship. Don't over-engineer this — your audience is forgiving. | <1 MIN · LOW |
Same prompt. YOUR situation. Try it. The protocol the prompt builds for you will look like none of these — it'll look like the one calibrated to your work, audience, and time budget. That's the point.
The Bottom Line
The lawyer didn't get sanctioned because AI made things up. AI was always going to make things up.
He got sanctioned because he didn't have a system.
Generic advice doesn't give you a system. The prompt above does.
Run it. Save the output. Then forward this to the colleague most likely to be next.
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