Lawyers have always worried about typos, missed deadlines, and sloppy citations—but generative AI added a new failure mode: confidently invented cases, quotes, and docket numbers that look “legal enough” to pass a quick skim. After a widely reported incident where a firm was sanctioned for submitting AI-generated citations that didn’t exist, legal teams started comparing notes in the places they always do when something breaks in the real world:
The consensus is blunt—AI can accelerate drafting, but it cannot be your source of authority. What follows is a practical, verification-first workflow (in the spirit of what working attorneys and paralegals say they actually do) to ensure every case, quote, and parenthetical is real before it hits a filing.
How Hallucinated AI Citations Triggered Court Fines
A hallucinated citation is not just a “wrong link”—it’s a fabricated authority presented to a court as though it were authentic. In the real sanction scenario that circulated widely in legal news, the problem wasn’t that AI was used; it was that the output was treated like research.
Generative models are designed to produce plausible text, not to guarantee that a case exists in Westlaw/Lexis, that a quoted passage appears on the cited page, or that a holding matches the proposition. When lawyers file that material, the court sees it as a breakdown of basic professional obligations: candor to the tribunal and reasonable inquiry.
What makes these failures so easy is how believable the formatting looks. AI can generate citations that resemble Bluebook structure, sprinkle in familiar reporter abbreviations, and even produce “quotes” that sound like judicial writing. On Reddit and legal-adjacent forums, many practitioners describe the same trap: the draft “reads clean,” and the citations are where you’d expect them to be. If the team is rushed—or if a junior person assumes the senior lawyer already verified—fake cases can slip into a brief with an air of legitimacy.
Courts respond harshly because the harm isn’t theoretical. Opposing counsel wastes time chasing ghosts, the judge’s chambers loses confidence in the filing, and the record is polluted with false authority.
Online practitioner discussions repeatedly emphasize that sanctions are often less about the tool and more about the process failure: no one performed the basic checks that would have immediately revealed “no results found” in a reputable database. That’s why the fix isn’t “never use AI”—it’s adopting a workflow where AI output is treated as an untrusted draft until verified.
A Reddit-Tested Workflow to Verify Cases and Quotes
The most common advice you see from lawyers and clerks online is simple: start verification at the citation level, not at the prose level. Step one is to take every AI-proposed case and look it up in an authoritative source (Westlaw, Lexis, Bloomberg Law, courtlistener for federal opinions, PACER for dockets, or an official state judiciary site). If the case can’t be found quickly by party name and citation, it’s dead on arrival—delete it, don’t “repair” it by guessing. If you do find it, open the opinion and confirm the key metadata: court, year, procedural posture, and whether it’s published/unpublished.
Step two is the “quote audit,” and forum veterans tend to be strict about it: no quote goes into a filing unless someone has seen it on the page. Copy the quote directly from the source opinion (not from AI, not from a secondary summary), and record the pinpoint citation while you’re there. If the AI wrote a paraphrase, rewrite it after reading the relevant section yourself and then cite to the actual language that supports your proposition. People who post about their internal checklists often recommend a bright-line rule: if you can’t produce a screenshot/PDF page of the quote with highlighting within 60 seconds, the quote is not ready.
Step three is ensuring the case actually supports what you’re saying today. Reddit threads about “don’t get burned by AI” often pivot to an older, very real legal research danger: a case can be real but no longer good law, or it can be distinguishable in a way that makes your statement misleading.
So after locating the opinion, run a citator check (KeyCite/Shepard’s/BCite) and read the negative treatment. Then validate the proposition: find the exact passage, confirm it’s not dicta if your argument requires a holding, and confirm the jurisdictional fit (binding vs persuasive). Many practitioners also add a final “human sanity check”: have someone who didn’t draft the section read it with the sources open and try to falsify it—because fresh eyes catch “sounds right” errors.
The lesson from the sanction story isn’t that AI is forbidden—it’s that AI is not a research database and not a substitute for professional verification. The fastest way to stay safe is to treat AI-generated citations as untrusted placeholders, then run a disciplined workflow: confirm the case exists, confirm the quote on the page, and confirm the authority’s current status and relevance.
If your team bakes those steps into drafting—ideally with a second-person review—you can still get the speed benefits of AI without risking the career-limiting embarrassment of citing a case that never existed.