That’s the lesson of Quinteros v. Harbor Distributing, LLC (Cal. Ct. App., 1st Dist., June 11, 2026), where the First District affirmed sanctions against a law firm and three of its attorneys after a brief filed under their names turned out to be built on citations to cases that don’t exist and quotations nobody ever wrote. The firm’s defense was that an outside contract attorney did the drafting and apparently used AI to do it. The court wasn’t moved.

How a Routine Motion Became the Worst Misconduct the Judge Had Ever Seen

The underlying dispute was ordinary. The Lipeles Law Group filed a wage-and-hour class action in Los Angeles, then filed a nearly identical one in San Francisco against the same defendants six months later. The defense moved to stay the second as a duplicate. That’s a routine request. The firm opposed it, and that’s where everything came apart.

The trial court found the brief contained two case citations that were entirely fabricated, meaning the cases simply do not exist, plus no fewer than eight quotations falsely attributed to real cases. The judge called it the worst attorney misconduct he had seen from the bench. He sanctioned the firm and its three attorneys $6,000, jointly and severally, meaning each is on the hook for the full amount, and flagged the matter for the State Bar.

When confronted, the firm pointed at its contract attorney, who had signed a declaration swearing he used a legitimate research tool, ran a citation check three times, and never touched AI. The lawyers whose names were on the brief said they trusted him. Two admitted they never read it before it went out.

Generative AI Doesn’t Change Who Answers for It

On appeal, the firm raised three arguments and lost all three, though not all the same way. Two of them, the procedural timing complaint and the objection to paying the other side, the court wouldn’t even reach, on forfeiture, the rule that you can’t raise on appeal an objection you didn’t make in the trial court first. The firm never invoked the statute’s 21-day safe harbor, a window to withdraw a bad filing and avoid sanctions, while it was before the trial judge. It buried its central request in a footnote. It even stipulated to the tentative ruling it later attacked. The third argument, that the conduct didn’t merit sanctions, the court did reach, and rejected on the merits as within the trial judge’s discretion.

The part that matters for everyone else is what the court said about responsibility. Drawing on a fast-growing line of California decisions about AI-fabricated authority, the panel held that the duty to verify every citation cannot be handed off to any technology, or to any other person. The lawyers’ names were on the brief. One of them signed it. That signature certifies that the contents are warranted by existing law, and you don’t get to walk it back because a contractor or a chatbot did the typing.

Why This Matters Beyond the Courtroom

The holding is about lawyers, but the principle reaches any business that uses AI or outside vendors. If your team uses AI to draft a contract, a compliance filing, or a regulatory submission, accountability for the result sits with the human who releases it. The fluent, confident, fabricated output is the dangerous one, because it reads as authoritative right up until somebody checks.

For in-house counsel and executives who supervise outside firms and vendors, the case is a prompt to ask one question. Who actually reads the work before it carries our name? “We trusted the vendor” lost here, and it loses anywhere the buck is supposed to stop with you.

For anyone wiring AI into a workflow, the rule is simple. A human who understands the subject reviews the output before it goes anywhere, every time. The speed is real. So is the exposure when nobody checks.

The Bottom Line

AI is now part of how work gets produced, and courts have stopped treating “the AI did it” as an excuse. Quinteros confirms that delegation, whether to a contractor or to a machine, doesn’t move responsibility off the person whose name is on the result. The businesses that get hurt by this won’t be the ones that banned the tools. They’ll be the ones that used them without deciding, in advance, who reads the output and signs off. That decision is far cheaper as a policy than as a sanction. Horst Legal Counsel advises businesses on AI governance, professional responsibility, and litigation risk. If you want to pressure-test how AI-assisted work moves through your organization before it becomes a problem, we’re glad to talk it through.

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Horst Legal Counsel | March 2026

If you have been following California’s growing body of appellate authority on AI-generated legal citations, you have watched the courts build a wall, one published opinion at a time.

• First came the warnings to attorneys.

• Then came the sanctions.

• Then, in Torres Campos v. Munoz, the consequences reached the bench itself when fabricated case law made it into a signed court order.

Now the First District Court of Appeal has laid another brick. In Sheerer v. Panas (2026) ___ Cal.App.5th ___ (A171804), the court extended the prohibition against unverified AI-generated citations to self-represented litigants, and it made clear that the available penalties go well beyond striking a deficient brief.

The message is no longer limited to the bar. It applies to everyone who files a document in a California court.

What happened

The underlying dispute was a family law matter involving child support. Anna Sheerer appealed a trial court order that failed to account for her ex-husband Thomas Panas’s bonus and restricted stock unit compensation when calculating support. The Department of Child Support Services agreed with Sheerer that the trial court had erred. On the merits, the Court of Appeal reversed. That part of the opinion is unpublished.

What the court chose to publish was something else entirely.

In his respondent’s brief, Panas:

• Cited at least two cases that do not exist.

• Fabricated quotations that appear nowhere in the real cases he did cite.

• Referenced hearings in the proceedings below that the appellate court could not locate in the record.

When Sheerer moved to strike the brief, Panas filed a declaration explaining that his “error” resulted from using a generative AI tool without verifying the output. The court was not persuaded by his framing.

The court’s reasoning

The First District began where you would expect: with the principle that self-represented litigants are held to the same standards as attorneys. Citing Kobayashi v. Superior Court and Keitel v. Heubel, the court rejected the notion that pro se status provides any shelter from the obligations that attach to every filing.

As our Supreme Court put it more than three decades ago, a doctrine permitting exceptional treatment for self-represented parties “would lead to a quagmire in the trial courts, and would be unfair to the other parties to litigation.”

The court then situated Panas’s conduct within the line of authority developing since generative AI tools became widely available:

1. Noland v. Land of the Free, L.P.: The Second District decision warning attorneys about unverified AI citations.

2. People v. Alvarez: Holding that honesty in court filings is paramount.

The opinion includes a passage that captures the court’s concern precisely: The rule of law depends on courts impartially applying law to facts. That foundation is threatened when litigants falsify the truth, “especially when done by using technological innovations that can spin persuasive webs of untruths and invent legal principles or authorities.”

Consequences and Penalties

Having disregarded Panas’s brief in its entirety, the court turned to consequences. It noted that under California Rules of Court, rule 8.276(a)(4), the court may impose monetary sanctions on its own motion for unreasonable violations. While the court declined to impose sanctions here due to the interests of the children involved, it published the warning as a deterrent.

Why this matters beyond family court

Sheerer v. Panas is a narrow case on its facts, but the published portion carries broad implications. Three things stand out:

• Universal Obligations: The court closed the gap. Sheerer makes explicit that the same obligations apply to every litigant, represented or not.

• Escalating Consequences: The court has put all parties on notice that monetary sanctions are available for AI-related citation failures. Future litigants should not expect the same restraint shown to Panas.

• No “Ignorance” Defense: The court’s response to Panas’s claim that he didn’t “knowingly” submit false info was direct: his lack of knowledge resulted from a failure to verify. The duty is to confirm every citation exists and says what you claim it says.

What businesses and individuals should take away

If your company uses AI tools in any part of a legal workflow—whether for research, drafting, or document review—Sheerer v. Panas adds to the growing authority that verification is not optional.

Key Takeaway: The obligation runs to the person whose name is on the filing, regardless of whether that person is an attorney, a corporate representative, or a self-represented individual.

• For Litigants: If you suspect an opposing party is submitting AI-generated work product without verification, you now have clear authority to seek relief.

• For Self-Represented Parties: Understand that the tools you use do not change the standard you are held to. The consequences are getting sharper.

Bottom Line

Sheerer v. Panas confirms what the California appellate courts have been building toward for the past two years: The duty to verify every citation in every court filing is universal. Horst Legal Counsel tracks AI-related litigation developments as part of its commitment to responsible AI integration in legal practice. For questions about how these decisions affect your business or your case, contact Jason Horst at jason@horstcounsel.com.

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Horst Legal Counsel | March 2026

Reviewing a judicial order that analyzed parties’ respective rights under AI-hallucinated case law cited and “interpreted” extensively by the parties, the Court of Appeal in Torres Campos v. Munoz felt compelled to publish its opinion in order to send a clear message to all officers of the court, whether at bar or on the bench:

“In a system of precedents that is designed to achieve consistency, predictability, and adherence to the rule of law, the judiciary cannot function properly unless judges and lawyers confirm the authenticity of cited authorities and review them to evaluate their holdings and reasoning. When the participants fail to perform this basic function, it compromises these institutional values and diminishes faith in the judicial process.”

In Torres Campos, the court confronted a family court order that relied on two entirely fictitious cases. The appellate panel agreed the trial court abused its discretion by basing its ruling on nonexistent authority. The Court nonetheless upheld the order, finding that appellant, whose own lawyer had drafted and submitted the very order that included the fake citations, had forfeited his right to challenge the order.

The case represents perhaps the most egregious single instance of AI hallucinations infecting the judicial process. A woman with custody of the dog she had shared with her ex-domestic partner told the family court that Marriage of Twigg and Marriage of Teegarden controlled her ex’s claim for custody over the dog. After a hearing, her ex’s lawyer submitted a proposed order to the court citing Marriage of Twigg and Marriage of Teegarden. The family court then adopted that proposed order, finding that, under Marriage of Twigg and Marriage of Teegarden, the ex receiving visitation rights was not in the best interests of the parties.

The problem? Both Marriage of Twigg and Marriage of Teegarden were AI-hallucinated cases.

How the Fake Citations Got Into the Record

The underlying dispute was a pet custody fight in San Diego family court. Joan Pablo Torres Campos sought shared custody and visitation of a dog named Kyra after his domestic partnership with Leslie Ann Munoz was dissolved. Munoz was represented pro bono by her cousin, Roxanne Chung Bonar, who cited the two fictitious cases in a letter opposing Torres’s motion, in Munoz’s declaration, and in filings in the Court of Appeal. Neither Twigg nor Teegarden, as cited, exists. The official citation Bonar provided for Twigg actually corresponds to an unrelated criminal case, and her citation for Teegarden misidentified the year, volume, and subject matter of a real but irrelevant spousal support decision.

After a hearing, the court directed Torres’s counsel to prepare a formal order. Torres’s counsel drafted that proposed order—and included the fictitious citations in the court’s reasoning. The commissioner signed it.

Forfeiture: You Can’t Challenge an Error You Created

On appeal, the Fourth District agreed that relying on fabricated case law constitutes an abuse of discretion, calling it “fundamentally incompatible with an informed exercise of discretion controlled by genuine principles of law.” But the court held Torres forfeited the claim under the doctrine that bars a party from challenging an error on appeal when that party caused or failed to correct the error below.

Torres’s own counsel had drafted the proposed order containing the hallucinated citations. She submitted it without verifying the authorities and without flagging the problem. The court found both affirmative conduct, drafting the order, and inaction, failing to object, supported forfeiture. The panel declined to exercise its discretion to overlook the forfeiture, reasoning that doing so would effectively excuse counsel’s own breach of her duty to the court.

Sanctions and a State Bar Referral

Bonar’s conduct drew direct consequences. When the issue was first raised on appeal, she defended the fictitious cases as legitimate, calling Torres’s challenge “baseless” and “unfounded.” She doubled down by providing additional fabricated parallel reporter citations and a fictitious date of decision for Twigg. She later acknowledged that the original citations came from a Reddit article shared at a family dinner and admitted she lacked a paid legal research subscription. At oral argument, she conceded the additional fictitious citation details may have come from AI tools.

The court imposed $5,000 in sanctions—significantly higher than the $1,500 and $1,750 imposed in the earlier Alvarez and Schlichter decisions, citing two aggravating factors: Bonar persisted in defending the fake authority even after being alerted to it, and she never fully explained where the additional fabricated citation information came from. The court also referred Bonar’s conduct to the State Bar.

Bottom Line

Torres Campos v. Munoz is the first published California appellate decision to directly address a trial court’s reliance on AI-hallucinated case citations in its own order. That distinction matters. Prior decisions like Alvarez, Schlichter, and Noland sanctioned attorneys for submitting fake citations. Torres Campos confronts what happens when fabricated law passes through every checkpoint, opposing counsel, drafting counsel, and the bench, and becomes the stated basis for a judicial order.

The court chose to publish its opinion for a reason. Its message was directed not only at the lawyers who failed here, but at the system itself. When a court order cites nonexistent authority as the legal basis for its ruling, the institutional values the court identified in its opening, consistency, predictability, and adherence to the rule of law, are not just compromised. They are absent. The court recommended that the Judicial Council consider adopting guidelines or rules for verification of citations, particularly in orders drafted by the parties and submitted to the court for signature.

That recommendation reflects the reality that the current safeguards failed at every level. Bonar cited fake cases. Torres’s counsel incorporated them into a proposed order without checking. The commissioner signed it. No one in the process did the basic work of confirming that the cited authorities were real. As AI tools become more embedded in legal research and drafting, every participant in the system, lawyers and judges alike, bears responsibility for ensuring that the law being applied actually exists.

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A Brief Filled With Quotes That Never Existed

The case itself is a straightforward business dispute. But the Court of Appeal never reached the merits because something far simpler stopped the entire process: the appellant’s opening brief contained several quotations attributed to California cases that simply aren’t real.

Respondent moved to strike the brief and dismiss the appeal. Their argument was that the lawyer relied on AI tools that hallucinated these quotes and even pulled a transcript excerpt from the wrong case.

When confronted, the attorney didn’t deny the errors. Instead, he said these were “clerical citation mistakes”—the result of his staff forgetting to replace a few paraphrased placeholders with actual case language. He denied the involvement of AI.

The court didn’t seem to buy it for a second. More importantly, though, it made clear that it couldn’t matter less how the errors happened.

The Court’s Point: You Chose the Workflow, You Own the Consequences

The justices started with a basic rule every litigator learns early in their career:
You don’t misquote the law. Period.

Whether the bad quotes came from AI, a rushed associate, or a sloppy editing process didn’t matter. California courts have made their position very clear in recent decisions like People v. Alvarez and Noland v. Land of the Free, L.P.: if you file a brief containing fabricated authority, you are responsible for the misrepresentation.

In Shayan, the court walked through the types of inaccuracies it found—stitched-together quotes that never appeared in the cited case, paraphrases disguised as direct quotations, and even language about issues the underlying opinions never discussed.

Some of these errors didn’t even help the attorney’s argument. But that’s not the point. The court emphasized the systemic harm: if fake quotes make it into the briefing ecosystem, they get repeated, cited, and eventually accepted as “law” by someone who doesn’t double-check.

Sanctions: Not Fatal, But Serious

The court didn’t dismiss the appeal outright, but the sanctions were still significant:

• $7,500 payable to the court,
• The opening brief stricken, with a corrected version required, and
• A State Bar referral.

The message here is plain and consistent with the Court of Appeal’s previous decisions on AI-generated inaccuracies: California courts are no longer giving the benefit of the doubt—or a slap on the wrist—when legal arguments are backed by unreliable authority.

Why Clients and In-House Teams Should Pay Attention

At first glance, this looks like a lawyer problem. It isn’t.

This is now a business-risk issue tied directly to the quality of your litigation strategy and your selection of litigators. The Court did not dismiss the appeal this time, but make no mistake: client outcomes are being placed directly at risk every time this phenomenon recurs.

Key Takeaways

• AI can assist, but cannot replace verification.
  Courts won’t tolerate briefs containing AI hallucinations, and no amount of finger-pointing at software will fix it.
• Your company’s reputation gets dragged in too.
  A sanctions order like this affects credibility—not just for the lawyer, but for the client behind the filing.

What Companies Should Do Right Now

AI is already part of litigation, whether anyone says it out loud. The question is whether your company has guardrails in place to control the risks.

Two Immediate Steps

• Update outside counsel guidelines to require disclosure of AI use in research and drafting, and insist on human review before anything goes to court.
• Set internal protocols so your in-house team doesn’t accidentally send AI-generated text into a filing or regulatory submission without a second set of eyes.

Shayan v. Shakib won’t be the last case where a California court confronts AI hallucinations, but it’s already one of the clearest. The takeaway is simple: AI can speed up drafting, but it cannot replace judgment, accuracy, or professional responsibility. Companies should expect their attorneys—and their internal teams—to build workflows that reflect that reality.

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Schlichter v. Kennedy: California Courts Continue to Make Examples of “ChatGPT Lawyers”

Generative AI has become a part of many workflows for a lot of litigators, whether or not they say so out loud. But California’s appellate courts are drawing a very clear line: you can use AI as a tool, but you cannot shift your professional duties onto it—especially when it comes to legal research and citations.

In Schlichter v. Kennedy (Fourth District, Div. Two, Nov. 17, 2025), the Court of Appeal issued a published sanctions order against appellate counsel after finding that his briefs contained multiple fabricated case citations with all the hallmarks of AI “hallucinations.” The court imposed monetary sanctions and referred the matter to the State Bar. For all of the litigators out there, the lesson is simple: AI governance is now part of litigation risk management.

What actually went wrong?

In an appeal arising from a civil dispute, counsel for the appellant filed a petition for writ of supersedeas and an opening brief that cited several cases which, as cited, did not exist. The case names looked real. The reporter citations looked real. The propositions they supposedly supported were the kind you see every day in appellate practice.

When the court attempted to verify those authorities, the volume and page numbers pointed to entirely different cases—or to nothing at all. The court ordered counsel to provide official copies of four specific cases. He responded by producing different cases with the same names but different citations, and those real cases did not say what the brief claimed they said.

That triggered an order to show cause why sanctions should not be imposed for relying on fabricated legal authority. In response, counsel submitted a declaration under penalty of perjury. He admitted the citations were wrong, but characterized the problem as a “clerical error” tied to breakdowns in his office processes. He denied relying on hallucinated output from generative AI, even as he acknowledged using AI tools at least in connection with one of the filings.

After a hearing, the Court of Appeal found his explanations not credible. It concluded that the pattern of bogus citations fit what other courts have described as AI hallucinations: realistic-looking case names and cites that do not correspond to real authorities supporting the propositions offered. The court then issued a published order imposing sanctions.

The court’s message about AI

The court did not sanction the mere use of AI. Instead, it grounded its analysis in familiar rules that predate any large language model:

• Each point in a brief must be supported, where possible, by citations to legal authority.
• The Courts of Appeal may sanction unreasonable violations of those rules.
• By signing a brief, an attorney certifies that the legal contentions are warranted by existing law or a non-frivolous argument for change.

What Schlichter does is connect those long-standing duties to the reality of generative AI. The opinion leans on earlier California decisions such as Noland and Alvarez, which emphasized that attorneys must personally verify that each cited case exists, that the citation is correct, and that the case actually stands for the proposition asserted. That verification obligation, the courts have now said more than once, cannot be delegated to AI or to any other technology.

In Schlichter, the court imposed a $1,750 sanction payable personally by counsel and directed the clerk to notify the State Bar. The referral matters: it signals that misuse of AI in litigation is not just a “tech mistake,” but is treated as a potentially-significant ethical issue.

Why this matters

Schlichter is not simply about one lawyer’s missteps. It is part of an emerging rulebook for AI in California litigation.

First, it emphasizes that how you use AI is far more important in the courtroom than whether you use AI, as its use has become generally accepted as not inherently inconsistent with lawyers’ professional responsibility. Courts are less interested in whether a brief was touched by AI and much more interested in whether the filing is accurate, candid, and competently researched. But when that accuracy, candor, and competence is undermined by the presence of AI hallucinations, judges are attuned to how these tools can go wrong, and they are committed to reducing the rising instances of their misuse.

Second, and relatedly, the case highlights that lawyers should not expect to get off from these instances with a slap on the wrist. A published decision, fine of more than $1,000, and a State Bar referral are significant on their own, but they can also create substantial collateral consequences in other matters, from availability and pricing of insurance to how courts view a lawyer’s future representations. For corporate clients, that translates into reputational and strategic risk if key matters are being handled by lawyers who lack sound AI practices.

Finally, Schlichter pushes AI governance into the relationship between in-house teams and outside counsel. Many companies already have policies about not feeding confidential information into public AI tools. Fewer have addressed how their outside litigators are allowed to use AI when drafting documents that will be filed with courts and regulators.

Practical questions to ask now

You do not need to ban AI to stay safe after Schlichter. But you do need to treat it as a high-risk tool that requires controls. In practice, that means asking:

• How are our outside counsel using generative AI in appellate and motion practice, and what is their documented process for verifying citations?
• Do our outside counsel guidelines expressly require human verification of authorities and quotations before anything is filed?
• Internally, are we building AI tools or workflows that make it too easy for AI-generated text to move straight into court filings without a robust review layer?

Schlichter v. Kennedy is unlikely to be the last California case on AI in litigation. But it amplifies an already clear signal: courts expect the same level of accuracy and candor they always have, and they will not accept “the AI made me do it” as an excuse.

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