🚨 BOLO: Apple's Emergency Mac Patch Closes a Screen Sharing Backdoor — Lawyers Update Now!

your apple computer may need an update right now!

Here's a security bug that has nothing to do with your caseload and everything to do with your law license. On August 6, 2026, Apple pushed an unusual, single-purpose emergency patch after security researchers discovered that Screen Sharing on the Mac could be tricked into granting full desktop access without a valid password. If you use a Mac to store client files, draft privileged communications, or manage your practice, this is a “Be On the Look Out” moment, and I mean that literally.

What Actually Happened

update your mac and windows os today and keep an eye out for new updates - they are more frequent than you think!!!

Apple's advisory describes the flaw in characteristically understated terms: "An attacker on the network may be able to authenticate to Screen Sharing without valid credentials". Translated out of engineer-speak, a bug in how macOS tracked login attempts meant the system could be fooled into treating an unauthenticated session as verified. Security firm Huntress went further, explaining that the bug exploited the Screen Sharing service's implementation of Secure Remote Password, which "ultimately allows pre-authenticated remote code execution on all supported macOS versions". In plain English: someone on your network, whether that's your building's shared Wi-Fi, a co-working space router, or a compromised office LAN, could potentially run code on your Mac without ever knowing your password. That's not a nuisance bug. That's the kind of hole that keeps ethics counsel up at night.

The flaw has an official tracking number, CVE-2026-65400, which is just a standardized ID security researchers use to reference a specific vulnerability across advisories and news coverage — think of it like a case citation for bugs 📋. It reaches across three generations of macOS: Tahoe, Sequoia, and Sonoma. Apple fixed it with macOS Tahoe 26.6.1, macOS Sequoia 15.7.9, and macOS Sonoma 14.8.9 all released the same day, an unusual move that signals Apple treated this as serious enough to skip its normal beta-testing cycle.

Why This Matters for Your Practice

your ethical duty of technological competence doesn't pause because a vulnerability sounds technical!

I've said it before on here and on the podcast, and I'll say it again: your ethical duty of technological competence doesn't pause because a vulnerability sounds technical. ABA Model Rule 1.1, Comment 8, requires lawyers to "keep abreast of changes in the law and its practice, including the benefits and risks associated with relevant technology" 📚. A screen-sharing bypass that hands an attacker the same control as someone physically at your keyboard is exactly the kind of risk that comment contemplates.

Model Rule 1.6 compounds the stakes. If Screen Sharing was enabled on a Mac holding client files, an attacker exploiting this flaw before the patch could have accessed privileged communications, case strategy, or financial data without leaving an obvious trace 🔐. That's a confidentiality problem regardless of whether you can prove exploitation occurred. And if you're a firm supervising associates or staff under Rule 5.1 or 5.3, this is also a moment to confirm every managed device across your practice, not just your own laptop, has been patched.

The silver lining: Apple has stated there's no evidence this bug was exploited in the wild before the fix shipped, and Screen Sharing is off by default on most Macs. But "off by default" isn't the same as "off on your machine," especially if you or an IT vendor ever turned it on for remote support.

How to Check and Patch Your Mac

This is a five-minute task, and it should not wait until end of day. ⏱️

1. Click the Apple menu → System Settings

2. Select General → Software Update

3. Install whichever applies: macOS Tahoe 26.6.1, Sequoia 15.7.9, or Sonoma 14.8.9

If your firm manages devices through IT and you can't update immediately, disable the feature entirely: Apple menu → System Settings → General → Sharing, then toggle Screen Sharing off. Note that Huntress specifically warns this is a pre-authentication bug, so the usual hardening tricks (removing user accounts, disabling legacy VNC passwords) won't protect you; only the patch or fully disabling the feature will.

The Bigger Pattern Worth Watching

A good rule of thumb is to keep your software os and programs up to date!

This isn't the first time Apple has issued an emergency patch outside its normal cadence, and it won't be the last. Solo and small firms need a patching routine, not just reactive fixes.

The takeaway is simple, even if the underlying vulnerability wasn’t: Almost always, keep your software up to date!  Update your Mac today, verify Screen Sharing's status even if you don't think you use it, and treat this as a reminder that competence under Rule 1.1 is an ongoing obligation, not a box you check once. 🛡️

Follow The Tech-Savvy Lawyer.Page for updates and alerts!

MTC: Washington’s Bar Exam Meltdown: What It Says About Cyber Risk, Competence, and the Future of Legal Tech ⚖️💻

Washington Bar Exam Cybersecurity Crisis Exposes Legal Technology Risks!

Washington’s last‑minute cancellation of this summer’s bar exam is not just a licensing story; it is a technology and ethics story that should make every practicing lawyer sit up straight. For solo and small‑firm practitioners, this is a case study in how fragile our exam, court, and law‑practice infrastructure has become in the face of sophisticated cyber threats—and how quickly that fragility can collide with our professional duties under the ABA Model Rules.

What Happened in Washington—and Why It Matters

The Washington bar abruptly pulled the plug on its planned exam administration, citing serious concerns about system integrity and the security of the underlying technology. Although details are still emerging, the through‑line is clear: the systems that deliver and proctor high‑stakes exams are now attractive targets for attackers and highly sensitive to infrastructure failures.

Think about the impact on examinees. Months of preparation, financial investment, travel, and childcare planning vanished with a late‑stage cancellation notice. But this is not only about logistics. This is about trust: Trust in the profession’s gatekeeping machinery and in the digital rails we have built for critical legal functions. When that trust erodes, the ripple hits everything from admissions to public confidence in our systems.

For working lawyers, this is a preview of what can happen when core legal processes—hearings, filings, exams, CLEs—depend on infrastructure that may be compromised or simply not resilient enough to withstand modern threats.

From Hotel Wi‑Fi to Bar Exams: The Captive Portal Threat 🚨

If the Washington story feels abstract, pair it with Microsoft’s recent warning about hotel and hospitality Wi‑Fi. Microsoft has identified a campaign, dubbed “CaptiveCrunch,” attributed to Russian‑linked threat actors (Storm‑2945), that hijacks captive portals—the login or “click to accept” pages we all use in hotels and conference centers—to steal credentials and deliver malware.

These attacks work by compromising the network infrastructure that sits between the user and the open internet. When a lawyer or bar examinee connects to the hotel Wi‑Fi and sees what looks like a routine sign‑in or software update prompt, that page may in fact be controlled by a threat actor. Microsoft reports that the attackers can:

• Redirect users to fake Microsoft 365 sign‑in pages and harvest credentials without sending a phishing email.

• Abuse device‑code authentication flows, so even multi‑factor authentication can be sidestepped if the victim enters a code and approves the request.

• Deliver a Windows remote access trojan (“CornFlake”) that can log keystrokes, grab files, record audio and video, and maintain persistent access.

Now layer this onto the bar exam setting. You have hundreds of exam takers in hotels and rented housing, many running locked‑down exam software on laptops that still need network access for downloads, updates, or cloud syncing before or after the exam. If the exam provider’s systems or the candidates’ devices ride on compromised networks, you have a recipe for:

• Actual or suspected compromise of exam content

• Loss or alteration of answer files

• Exposure of highly sensitive personal and biometric data

The bar’s decision to cancel may well reflect a recognition that once you have a credible cyber risk in the mix, it is better to protect exam integrity—even at enormous logistical and human cost—than to run an exam whose validity may later be attacked.  My heart goes out to the affected examinees, who have been left adrift in a difficult professional limbo—unable to move to the next stage of their careers and required to devote still more time, money, and emotional energy to preparing for another exam, with the hope that it will not be disrupted by malicious actors.

Ethics Meets Cyber Reality: ABA Model Rules in Play 📜

CaptiveCrunch Hotel Wi-Fi Attacks Threaten Lawyers’ Digital Security

This is where your daily practice intersects directly with the bar’s meltdown.

Model Rule 1.1 (Competence) explicitly includes a duty to understand “the benefits and risks associated with relevant technology.” Cyber threats like CaptiveCrunch are now squarely within “relevant technology.” If you travel for hearings, depositions, client meetings, or bar events and routinely connect to hotel Wi‑Fi without safeguards, you are not just taking a personal risk; you may be jeopardizing client confidences, privileged communications, and case strategy.

Model Rule 1.6 (Confidentiality of Information) requires reasonable efforts to prevent unauthorized access to client information. Using untrusted hotel or conference Wi‑Fi without protections—especially when we now have concrete warnings from Microsoft—raises tough questions about whether your security posture is still “reasonable.”

Model Rule 5.3 (Responsibilities Regarding Nonlawyer Assistance) and Rule 5.1 (Supervisory Lawyers) also surface here. When your cloud vendors, exam providers, or outsourced IT teams operate systems on which your work depends, your duty is not satisfied by “we assumed they had it handled.” You must perform due diligence, ask questions about security practices, and be prepared to adjust your workflows when a vendor’s risk profile changes.

The Bar Exam as a Canary in the Cyber Coal Mine 🐤

The Washington bar exam cancellation looks like a one‑off crisis, but it is better seen as a canary in the coal mine for the entire legal ecosystem.

We increasingly rely on:

• Online proctoring systems for bar exams, law school tests, and certifications

• Remote hearing platforms and e‑filing systems for courts

• Cloud‑based case management, timekeeping, and trust accounting tools

Each of these systems sits on infrastructure that can be compromised at the network, platform, or endpoint level. The CaptiveCrunch campaign shows that attackers are willing to invest in compromising hospitality networks globally, in part because those networks handle high‑value corporate and professional traffic.

If attackers can hijack captive portals to intercept Microsoft 365 logins and deliver Remote Access Trojans (RATs) like CornFlake, they can also target:

• Judicial staff connecting from hotels during conferences

• Law firm partners working on the road

• In‑house counsel traveling to negotiation sessions

Once a single endpoint is compromised, attackers can move laterally into cloud resources, email archives, document management systems, and case data.

In other words, the Washington bar’s crisis is the profession’s crisis—just seen in extreme close‑up.

Practical Security Takeaways for Solo and Small‑Firm Lawyers 🛡️

So what do you do differently now?

Microsoft’s recommendations for travelers are a good starting point: assume guest networks are untrusted, favor mobile hotspots or secured private connections, and avoid performing updates or entering credentials through captive portals. Let’s translate that into concrete steps for law practice:

Travel Playbook

• Prefer your phone’s hotspot or a dedicated travel router with a trusted VPN when accessing email, case management, or client files on the road.

• If you have no choice but to use hotel or other public Wi‑Fi, connect only through a reputable VPN and treat the captive portal as a necessary but dangerous doorway.

• Complete only the minimum captive‑portal steps needed to get online, and then avoid entering passwords, approving authentication prompts, or installing updates until your VPN is active and you are past the captive‑portal page.

Authentication Hygiene

• Move to phishing‑resistant authentication where possible (hardware security keys, platform authenticators) and restrict device‑code flows unless truly needed

• Train your team to treat unexpected device‑code prompts or update pages during hotel logins as red flags, not background noise.

Vendor and Exam Provider Scrutiny

• Ask pointed questions about incident response, logging, and how they handle suspected network compromise.

• Build contingency plans—if an exam, hearing, or critical system fails or is compromised, what is your fallback?  (Perhaps a cheap backup laptop? Apple has a pretty good return policy - check provider details for timeliness and other requirements.)

Final Thoughts: Looking Ahead - Resilience, Not Just Compliance ✅

Cybersecurity Competence Is Now Essential for Modern Legal Practice!

The Washington bar’s decision to cancel its exam sends a hard message: compliance checklists and bare‑minimum security are no longer enough. We need resilience—systems and workflows designed to fail gracefully, with clear fallback paths that do not compromise integrity or fairness.

For bar authorities and courts, that means:

• Building redundancy into exam and hearing platforms

• Running adversarial security testing and tabletop exercises

• Communicating transparently with stakeholders about how cyber risk is identified and mitigated

For practicing lawyers, it means re‑framing technology as part of our core competence, not a bolt‑on afterthought. Model Rule 1.1’s commentary on technology is not aspirational; it is a reflection of the reality that our ethical duties now live at the intersection of law and information security.

The bar exam meltdown in Washington is a wake‑up call. Pair it with Microsoft’s warning on hotel Wi‑Fi, and the message is unmistakable: our digital rails are under live fire. The question is whether we treat this as yet another “unprecedented” event—or as the moment we upgrade our tools, our habits, and our ethics posture to meet the threat.

MTC

MTC: Judges Will Be Hunting These AI Tricks After Brazil’s Scandal

it is hard to believe that judges will be happy if lawyer insert “code” into their online filings!

Recently, Brazilian court officials uncovered something that should make every tech‑savvy lawyer sit up straight. In a labor court, staff discovered a filing that looked ordinary to the human eye—until they examined it more closely. Hidden in the document was text written in white font on a white background, invisible to anyone casually reading the PDF but fully legible to the court’s AI system.

That invisible text was not a typo. It was an instruction—what technologists call a “prompt injection”—telling the court’s AI software to review the case only superficially and not to challenge the evidence submitted. In other words, the filing was designed to trick the judiciary’s own AI tools into rubber‑stamping a favorable outcome by smuggling in commands that humans would never see.

Fortunately, court staff caught the scheme before it affected the proceedings. But Brazilian authorities immediately recognized the incident as a new species of digital fraud and began discussing safeguards: automatic detection of invisible text, formatting checks before AI processing, and stronger human oversight at every stage. They also raised the prospect of stricter ethics rules and sanctions for lawyers who try to manipulate court AI systems.

For our purposes, the Brazil case does three important things:

1. It confirms that AI now sits inside judicial workflows—not just law firm workflows.

2. It shows that some lawyers will try to game those systems if they think they can get away with it.

3. It gives us a concrete example of what not to do and what to watch for as courts in the U.S. and elsewhere adopt similar tools.

From an ABA perspective, a “white‑text prompt injection” is not clever lawyering—it’s a direct collision with Model Rule 3.3 (candor toward the tribunal) and Model Rule 8.4(c)’s prohibition on conduct involving dishonesty, fraud, deceit, or misrepresentation. And because the Brazil incident exploits the very AI tools that the judiciary is using, it also implicates Model Rule 1.1 and Comment 8: the duty of technology competence now includes understanding how these systems can be abused.

So let’s unpack what we should learn from Brazil—starting with what not to do.

What Not To Do: Hidden Instructions and “Clever” Hacks

The Brazil case is a textbook on the wrong way to think about AI in litigation.

• Do not embed hidden commands in filings (through white‑on‑white text, metadata, or other tricks) with the intent to influence how a court’s AI tools process your case.

• Do not treat court‑side AI as just another system to be “SEO‑optimized” or hacked. Unlike a marketing algorithm, this is part of the machinery of justice; trying to tilt it in your favor crosses a bright ethical line.

• Do not assume that “if the judge doesn’t see it, it doesn’t count.” Malicious prompts aimed at judicial AI are still part of your submission to the tribunal, and they reflect directly on your candor and honesty under Model Rules 3.3 and 8.4.

In short: if you would never say it to the judge in plain black‑and‑white text, you should not whisper it to the court’s AI in invisible text.

What To Watch For: How to Recognize This Behavior

lawyers need to be prepared to vet opposing counsel’s filings for ai injection!

The harder question is how you, as a solo or small‑firm lawyer, can spot similar tactics when others use them—especially when you don’t control the court’s systems.

Here are practical signals and questions:

• Suspicious formatting in PDFs or Word files. Odd spacing, unexpected blank pages, or inconsistent fonts can sometimes signal hidden layers of text. While you won’t always spot white‑on‑white content, unusual formatting should prompt closer inspection.

• Metadata anomalies. If you routinely examine document properties, look for multiple authors, unusual editing histories, or automation tags that do not match the face of the document. These can indicate heavy automated processing or embedded instructions.

• Patterns in AI‑mediated decisions. If certain filings—often from the same party—seem to sail through automated queues or receive unusually favorable, boilerplate orders, you may be seeing the downstream effect of prompt manipulation or aggressive “AI‑targeted” drafting.

Because you usually won’t have direct access to the court’s internal AI, you may need to raise these concerns procedurally: requesting clarification on how filings are screened, asking whether AI systems were involved in certain steps, or moving for relief if you believe your client’s matter was prejudiced by automated processing.

How To Protect Yourself and Your Clients:

Brazil’s experience is a warning shot—not just about bad actors, but about what a healthy response should look like.

Here’s how to translate that into a practical “do this, not that” playbook for your own practice:

1. Assume courts will adopt AI—and plan for it:

Brazil’s judiciary uses AI to prioritize cases, draft reports, and propose decisions in response to massive backlogs. U.S. courts are already experimenting with similar tools, even if not as publicly. Competence under Model Rule 1.1 now includes staying informed about these trends and understanding their implications.

2.     Build “AI integrity” into your litigation strategy.

• Treat any automated system that touches your filings—court e‑filing portals, online forms, AI‑assisted triage tools—as part of the tribunal.

• Resolve that you will never include hidden instructions, misleading metadata, or manipulative formatting in documents submitted to those systems.

3.     Advocate for transparent safeguards.

• In Brazil, authorities responded by exploring automatic detection of invisible text and stronger human oversight.

• When U.S. courts announce AI pilots or tools, comment on proposed rules, advocate for clear notice when AI is used, and request mechanisms for lawyers to challenge AI‑influenced outcomes.

4.     Document your own good‑faith use of AI.

it may be deemed a “fruad upon the court” if a lawyer injects ai into their electronic filings.

• If you rely on AI to format or generate parts of your filings, keep internal records of prompts, outputs, and human review.

• This documentation will help if a court or disciplinary body later asks how you ensured candor and accuracy, especially in a world where Brazil‑style abuses are making judges more skeptical.

Final Thoughts

AI isn’t just something we use; it’s now part of the institutional environment—just like e‑filing, CM/ECF, or digital signatures. The line between legitimate technology use and unethical manipulation is not about whether you use AI, but how you use it and whether you’re honest about it.

MTC

MTC: ChatGPT, Work Product, and Waiver: New Lessons from Tate Group Automotive ⚖️🤖

Tech‑savvy lawyerS need to be able to defend ChatGPT work product before Texas Business Court.

On June 3, 2026, the Business Court of Texas issued a minute entry in Tate Group Automotive, LLC v. Legacy Automotive Capital, LLC that every tech‑curious lawyer should know about. As of today, this is one of the first reported decisions to tackle whether a non‑lawyer’s ChatGPT conversations are protected attorney work product and, if so, whether using a public AI tool waives that protection.

The court’s answer is nuanced but important: generative AI does not automatically destroy work‑product protection, at least where the disclosure is not made to an adversary under Texas Rule of Civil Procedure 192.5(a)(1). For solos and small firms experimenting with AI tools, this is both reassuring and sobering.

What Happened in Tate Group Automotive?

The case arises from a dispute in the Texas Business Court’s Eleventh Division, in which Tate Group Automotive sued Legacy Automotive Capital, The Reynolds and Reynolds Company, and individual defendants. During discovery, the plaintiff withheld “Kris Tate–ChatGPT conversations” on the basis of attorney work‑product protection and submitted them to the court for in camera review.

Defendants challenged that claim. They argued that attorney work‑product protection does not extend to a non‑lawyer’s chats with an AI tool, or alternatively, that any protection was waived when Kris Tate used ChatGPT. They also asked the court to order the plaintiff to identify all discovery materials Mr. Tate or Tate Group had shared with ChatGPT.

Judge Grant Dorfman acknowledged that the issue was “novel,” noting that all case law cited by the parties dated from 2026 and that at least one opinion called the question “a first impression nationwide.” Against that backdrop, he evaluated the ChatGPT conversations under Texas Rule of Civil Procedure 192.5(a)(1), which defines work product and addresses waiver.

The key takeaway from the minute entry—based on the Minerva summary—is that the court concluded a non‑lawyer’s chats with ChatGPT did not automatically waive work‑product protection because the disclosure was not made to an adversary. That is a narrow holding, but it marks a significant moment in the emerging law of AI and privilege.

Why This Ruling Matters for Lawyers Using AI

At first glance, Tate Group may look like a niche discovery dispute. In reality, it answers a question many lawyers have quietly asked: “If my client uses ChatGPT, have we blown work product?”

The court’s answer is “not necessarily.” By focusing on whether the disclosure was made to an adversary, Judge Dorfman signaled that the waiver analysis for AI platforms should track the familiar contours of work‑product doctrine, at least in Texas. That gives practitioners a framework instead of a panic button.

At the same time, this is a minute entry in a specific context—not a blanket blessing for all AI use. The court still treated the issue as novel, still conducted in camera review, and still scrutinized how the AI tool was used. For lawyers, that means AI usage is now part of the discovery and privilege landscape, and courts will expect thoughtful, documented positions—not hand‑waving about “just using a tool.”

From an ABA perspective, this aligns with Model Rule 1.1 and Comment 8: competence now includes understanding the “benefits and risks associated with relevant technology,” including how generative AI intersects with privilege and work product. Model Rule 1.6 (confidentiality) and Rules 5.1/5.3 (supervision of lawyers and non‑lawyers) also come into play when clients or staff use tools like ChatGPT in ways that touch litigation strategy.

Lesson 1: Treat Client AI Use as Discoverable Reality, Not a Side Note

One of the most striking aspects of Tate Group is procedural: the court required in camera review of the ChatGPT conversations and entertained requests that plaintiff identify all discovery materials shared with ChatGPT. That tells us courts are prepared to treat AI interactions as real, reviewable artifacts in discovery.

If your clients or internal teams use AI to draft, summarize, or analyze case materials, those interactions can become part of the discovery conversation, just as drafts, notes, and emails have always been. Under Model Rules 1.1 and 1.6, you cannot stay competent or protect confidentiality if you do not know whether and how AI is being used on your matters.

Practically, that means:

• Ask clients early whether they have used tools like ChatGPT or other AI services to “get help” on their case.

• Document the scope and purpose of any AI use, especially if it involves draft pleadings, strategy, or privileged communications.

• Be prepared to defend or adjust your privilege and work‑product positions in light of those uses, as plaintiff did in Tate Group by asserting work‑product and submitting chats for in camera review.

Lesson 2: Public AI Platforms Are Not Automatic Waiver Machines

Solo attorneys need to protect their privileged work product from risky AI tools.

Defendants in Tate Group argued that a non‑lawyer’s chats with an AI tool either are not work product at all or, at minimum, effect a waiver. The court rejected the idea that simply using ChatGPT automatically destroys protection under Texas Rule 192.5(a)(1) when there is no disclosure to an adversary.

That matters, because there has been a real fear—sometimes stoked by vendors—that “if anyone touches ChatGPT, all privilege is gone.” This ruling shows courts can adopt a more nuanced view, at least under a work‑product framework.

For ABA‑Model‑Rules lawyers, this should not be read as a free pass. Model Rule 1.6 still requires reasonable efforts to prevent unauthorized disclosure of client information, and using a public AI platform can create confidentiality risk even if work product is technically preserved. But Tate Group suggests that waiver analysis will still look to core principles like whether disclosure reached an adversary.

In practice:

• You should not assume that any AI use destroys work product, but you should be ready to explain why your use did not involve disclosure to an adversary or the public.

• Engagement letters and internal policies should clarify whether and how you will use AI tools and what safeguards you apply, consistent with Model Rules 1.1, 1.4, and 1.6.

Lesson 3: In Camera Review Will Become Common for AI Disputes

The court’s process—ordering in camera review of the ChatGPT conversations before ruling—signals a likely pattern for AI‑related privilege disputes. Judges will want to see how AI was used, not just hear generalities, before deciding whether protection applies or has been waived.

That has three implications for practicing lawyers:

• You should assume that AI‑related materials can be reviewed by courts under appropriate safeguards.

• You need internal workflows to collect and present those materials when necessary without scrambling through chat histories.

• You should approach AI use with the expectation that a judge, someday, may read the raw prompts and outputs and ask whether your supervision met the standards of Model Rules 5.1 and 5.3.

This is a shift from treating AI as a “black box” helper to treating it as a discoverable component of your litigation process.

Lesson 4: Non‑Lawyers and AI Need Clear Supervision

In Tate Group, the conversations at issue were between Kris Tate—a non‑lawyer—and ChatGPT, yet they were withheld under an attorney work‑product theory. The court’s willingness to consider work‑product protection in that context underscores a point many of us have made: non‑lawyers can participate in the creation of protected material if they are acting at the direction of counsel.

But it also heightens the importance of supervision. Model Rule 5.3 requires lawyers to ensure that non‑lawyer assistants’ conduct is compatible with the lawyer’s professional obligations. When non‑lawyers use AI tools on client matters, they are effectively acting as an extension of the legal team.

Practical steps include:

• Training non‑lawyers on what they may and may not share with AI platforms.

• Setting clear rules about which tools are approved, for what purposes, and under whose supervision.

• Reviewing AI outputs and underlying prompts when they feed into litigation strategy, to ensure accuracy and compliance with Model Rules 3.3 and 4.1.

As we have discussed in episodes of The Tech‑Savvy Lawyer podcast, AI is not just a “lawyer tool”; it is often a staff and client tool. Your ethical obligations follow it wherever it goes. 💼🤖

Lesson 5: This Is Only the Beginning—But You Can Prepare

Texas judges along with others will be weighing ChatGPT privilege and waiver in generative AI era.

Judge Dorfman noted that all the case law cited by the parties dated from 2026 and that one authority called its ruling a “question of first impression nationwide.” That means we are at the very start of AI‑and‑privilege jurisprudence, not the end.

Every new decision—whether from Texas Business Courts or elsewhere—will refine the analysis. Some may take a stricter view of waiver for public AI tools; others may distinguish between work product and attorney‑client privilege. Regardless, Model Rule 1.1’s technology‑competence requirement demands that we follow these developments and integrate them into our practice.

You do not need to become an AI engineer, but you do need a plan:

• Inventory where AI is used in your matters (by you, your staff, your clients).

• Align that usage with your duties of competence, confidentiality, and supervision.

• Be prepared for in camera review of AI‑related materials, as in Tate Group.

• Update your engagement letters and internal policies to reflect reality, not wishful thinking.

If you approach AI as you approached email, e‑filing, and cloud storage when they were “new,” you will be ahead of many peers—and aligned with the spirit of both the ABA Model Rules and emerging case law.

MTC

MTC: Law School, Laptops, and AI: Why Banning Computers Misses the Point!

Law schools are throwing out the baby with the bathwater by banning laptops from the classroom as an effort to combat improper ai use.

On July 10, 2026, the conversation around artificial intelligence in legal education reached a new level. Reports of universities banning both AI tools and laptops in classrooms reflect a growing anxiety: how do we preserve critical thinking in an age of automation? ⚖️

It is a fair question. It is also the wrong solution.

Let me be clear at the outset. A first-year ban on AI tools makes sense. A blanket ban on laptops does not.

The Case for Limiting AI—At First

Legal education has always been about building judgment. That means learning how to analyze facts, synthesize doctrine, and construct arguments from scratch. AI short-circuits that process if used too early.

Under ABA Model Rule 1.1 (Competence), lawyers must provide knowledgeable and skilled representation. That competence begins in law school. If students rely on AI before they understand the law themselves, they risk becoming operators instead of thinkers.

As I have noted in prior discussions on legal technology, AI should augment—not replace—legal reasoning.

So yes, a structured limitation on AI during the first year is defensible. It creates a foundation. It forces students to wrestle with ambiguity. It builds intellectual muscle. 💡

But Banning Laptops? That Is an Overreach

This is where the policy breaks down.

When I entered law school then graduated in 2002, laptops were just beginning to appear in classrooms. They were not universal. They were not always welcome.

For me, the laptop was not a distraction. It was essential.

My handwriting was and sadly still is poor. My ability to type, organize notes, and revise quickly made the difference between struggling and succeeding. My laptop was not a shortcut. It was an accessibility tool before we used that term widely.

Fast forward to today. Students are typing far more than they write. Many have never learned cursive. Their academic workflows are digital from the start.

To remove laptops is not to level the playing field. It is to shift it—often unfairly.

The Practical Reality of Modern Learning

Legal education does not exist in a vacuum. Law practice is digital.

Law students who learned on laptops will be disadvantaged if classrooms suddenly ban them.

Under ABA Model Rule 1.1, Comment 8, lawyers must understand the benefits and risks of technology. That obligation does not begin after graduation. It begins in law school.

Students today must learn:

• How to organize digital research

• How to draft and revise efficiently

• How to manage documents and workflows

• How to integrate technology into legal reasoning

You cannot teach modern legal competence while removing the primary tools of modern legal work. 🖥️

A laptop is not the problem. Misuse is.

The Enforcement Problem No One Is Talking About

There is also a practical issue. Banning AI is difficult to enforce. Banning laptops is easy.

That does not make it the right policy.

If anything, banning laptops is a workaround for the harder problem of AI enforcement. It is a policy by convenience.

And it raises a deeper concern under ABA Model Rule 5.3 (Responsibilities Regarding Nonlawyer Assistance), which increasingly applies to AI tools. Lawyers—and future lawyers—must learn to supervise and evaluate AI outputs.

You cannot teach supervision by eliminating exposure.

A Better Approach: Controlled Access, Not Prohibition

Law schools should be experimenting with smarter controls instead of blunt bans.

Some possibilities include:

• Disabling Wi-Fi and cellular signals in certain classrooms 📶

• Using locked-down exam or classroom software environments

• Creating AI-permitted and AI-prohibited assignments with clear boundaries

• Requiring disclosure of AI use in coursework

• Teaching prompt engineering and AI verification as part of the curriculum

This approach aligns with ABA Model Rule 1.6 (Confidentiality) as well. Students must learn what data can and cannot be shared with AI systems.

Exposure with guardrails is more effective than prohibition. That principle applies directly to how law schools should approach AI.

Critical Thinking and Technology Are Not Opposites

There is a persistent myth underlying these bans: that technology erodes thinking.

That is not inherently true.

Technology can weaken thinking if it replaces effort. It can strengthen thinking if it supports it.

A student who uses a laptop to organize case law, annotate notes, and refine arguments is not thinking less. They are thinking differently—and often more effectively.

The same will eventually be true of AI.

The goal is not to create lawyers who avoid technology or who think less by using AI. It is to create lawyers who use it wisely. ⚖️

What Law Schools Should Be Teaching Instead

If I were designing a first-year curriculum today, I would include:

THE MODERN LAWYER NEEDS TO KNOW HOW TO BALANCE JUDGMENT WITH AI USE IN THEIR WORK!

• A temporary restriction on AI-generated work

• Mandatory instruction on how AI tools function

• Exercises in verifying AI outputs against primary sources

• Training on ethical risks, including hallucinations and confidentiality

• Continued use of laptops as standard tools

This approach respects both sides of the equation: foundational thinking and technological competence.

Final Thought: Do Not Solve the Wrong Problem

Law schools are right to be concerned. AI is reshaping the profession at a rapid pace.

But banning laptops is not a solution. It is a signal of discomfort.

The better path is harder. It requires nuance. It requires experimentation. It requires trust in students, guided by structure.

Most importantly, it requires recognizing that the future lawyer will not choose between thinking and technology.

They will need both.

And law school is exactly where they should learn how to do that. 🚀

MTC: When Your CEO Asks ChatGPT How to Take Over: Lessons for Lawyers on Public AI, Ethics, and Confidentiality 🧠⚖️

Lawyers need to evaluate public AI chatbot against ABA confidentiality and privilege rules

In March 2026, the Delaware Court of Chancery in Fortis Advisors, LLC v. Krafton, Inc. handed lawyers one of the clearest cautionary tales yet about public AI chatbots, corporate governance, and the limits of “move fast and break things.” A South Korean gaming conglomerate, Krafton Inc., used an artificial intelligence chatbot to help devise an internal “Project X” takeover plan against its own studio, Unknown Worlds Entertainment, and then tried to defend the fallout in court. The result: a detailed opinion reinstating the studio’s CEO, extending a $250 million earnout period, and spotlighting how AI misuse can become Exhibit A when things go wrong.

If you’re a solo, a small-firm lawyer, or an AI‑curious practitioner dabbling with ChatGPT or similar tools, this case is your wake‑up call. The message is not “don’t use AI.” The message is: treat public chatbots the same way you treat email, cloud storage, or texting — through the lens of ABA ethics, client confidentiality, and privilege. 😬

In this editorial, I’ll unpack what happened, how the court framed the misuse of a chatbot, and what you should do in your own practice to stay on the right side of the rules.

The Case in a Nutshell: AI as a Takeover Co‑Pilot

Krafton bought Unknown Worlds — the studio behind Subnautica — for $500 million upfront plus up to $250 million in contingent earnout payments, with a contractually guaranteed structure: the founders and CEO (the “Key Employees”) retained operational control and could only be fired for defined “Cause.”  As Subnautica 2 approached early‑access launch, internal projections showed the game would easily trigger a massive earnout.

The CEO of Krafton grew concerned he looked like a “pushover” under the deal and turned to a public AI chatbot for advice on how to avoid paying the earnout and seize control of the studio. The chatbot’s “response strategy” included:

• Locking down publishing rights and code access.

• Crafting messaging to “secure public support” and undermine the “large corporation vs. indie” narrative.

• Preparing a “takeover” path that blended hardball legal tactics with PR framing. 

Krafton’s internal team implemented much of that plan — cutting off the studio’s access to its Steam publishing console, posting unilateral public statements, and ultimately terminating the founders and CEO on a pretext of “premature release” risk.  When sued, Krafton tried to pivot to new justifications, including the executives’ role changes and their defensive downloads of company data. 

The court was having none of it. Vice Chancellor Will held that:

• The terminations were not “for Cause” under the negotiated contract.

• The “Project X” takeover guided by the chatbot was a pretext to avoid the earnout.

• The studio’s CEO, Ted Gill, must be reinstated with full operational control, and the earnout period equitably extended by the length of his ouster. 

In other words, the AI‑assisted takeover strategy became part of the factual narrative of bad faith and breach — not a clever workaround.

Public Chatbots and ABA Model Rules: Three Pressure Points ⚖️

Attorneys must consider ethical AI chatbot use for confidential client case analysis

Even though this is a corporate earnout case, the opinion gives lawyers a concrete frame for thinking about public AI tools under the ABA Model Rules.

1. Confidentiality — Model Rule 1.6

Rule 1.6 requires lawyers to keep “information relating to the representation of a client” confidential, absent informed consent or a specific exception. Public chatbots are not your firm’s Document Management System (DMS) — they’re third‑party services that typically ingest prompts for training, quality, and logging. When Krafton’s CEO ran “Project X” through a chatbot, he was effectively outsourcing high‑stakes strategy to a non‑privileged third‑party system that could store and learn from those prompts. 

For lawyers, the parallels are obvious:

• Dropping fact patterns, names, or deal structures into a public chatbot can mean you’ve disclosed client information to a non‑controlled vendor.

• Even “sanitized” prompts can be re‑identified when combined with other data.

Under 1.6, that’s a potential confidentiality breach unless you’ve vetted the tool, negotiated appropriate terms (including data handling and retention), and obtained informed client consent for that mode of assistance. Emojis and “it’s just drafting help” don’t change that. 😉

2. Privilege — Model Rules 1.1 and 1.4 (Competence and Communication)

Privilege isn’t framed in the Model Rules, but Rule 1.1 (competence) and 1.4 (communication) require you to understand how your technology choices affect the protection of client communications. When you route strategy discussions through a public chatbot:

• You may jeopardize attorney–client privilege by involving a third‑party with no need‑to‑know and no formal role in the representation.

• You may create discoverable records that live outside your control, just as Krafton’s CEO created chat logs he then tried to delete. 

The court noted that relevant chatbot logs were deleted, which did not play well in evaluating Krafton’s narrative.  Privilege analysis is already complex with cloud tools; adding public AI as a “secret co‑counsel” without protections only compounds that risk. 

Competent use of technology now includes understanding whether your AI stack is preserving or eroding privilege and communicating those risks to clients when you propose AI‑assisted workflows.

3. Candor and Misrepresentation — Model Rule 4.1 and 8.4(c) 🚨

Although this case turns on contractual “Cause” and good faith, the court’s language about “pretextual” justifications and manufactured defenses should resonate with litigators. Model Rule 4.1 prohibits knowingly making false statements of material fact to third parties; Rule 8.4(c) bars conduct involving dishonesty, fraud, deceit, or misrepresentation. 

When you:

• Use a chatbot to generate strategic messaging designed to mislead stakeholders.

• Craft public statements or demand letters that you know are pretextual, but you’ve optimized with AI for tone and impact.

… you’re still responsible for the truthfulness of that content. The court saw through Krafton’s attempt to re‑frame events after the fact, and its internal AI‑assisted playbooks did not help. 

For lawyers, the lesson is simple: AI‑generated output is yours once you sign or speak it. If it’s misleading, you own the ethics problem — not “the algorithm.”

Practical Takeaways for Solo and Small‑Firm Lawyers 🧩

So what do you do if you’re a tech‑savvy lawyer who likes AI, but doesn’t want your prompts quoted in an opinion like this?

Here are grounded, practice‑ready steps.

1. Establish an AI Use Policy

Even if you’re a solo, write down what you will and won’t do with public chatbots.

lawyers need to build practical, ethical AI policies for practice.

• No client names, exact fact patterns, or identifiable deal terms in public tools.

• Use AI for structure and language, not for strategy or confidential analysis.

• Prefer client‑specific, non‑logging enterprise tools when handling sensitive material.

Treat this like you treat your cloud storage or remote‑work policy — it’s part of your competence under Model Rule 1.1 and your supervisory obligations under 5.1/5.3 if you have staff.

2. Separate “Public Prompting” from “Privileged Thinking” 🧠

Use public chatbots for:

• Headline and meta description drafting.

• Blog outlines, post ideas, or simple explainer language for non‑client scenarios.

• Rough templates for standard documents that you will heavily edit.

Avoid using them for:

• Fact‑specific case assessments.

• Litigation strategy, negotiation plans, or internal “playbooks” like Krafton’s “Project X.” 

• Anything that feels like the kind of conversation you’d normally have only with a colleague behind closed doors.

This separation keeps your privileged work product inside tools and workflows you control.

3. Vet Vendors Like You Vet e‑Discovery Platforms

If you move beyond public chatbots to paid AI tools, evaluate them as you would any major legaltech vendor:

• Where is data stored?

• Is training on your material disabled by default?

• Can you get a Business Associate Agreement or Data Processing Agreement / Data Protection Impact Assessment that aligns with your jurisdiction’s expectations?

The ABA’s Formal Opinion 477R on secure communications and cloud ethics opinions from state bars all provide analogies: reasonable steps, not perfection, are required — but “type client memo into random website” is not reasonable. 😄

4. Document Client Consent When AI Is Material to the Representation

If you expect to use AI in a way that materially affects how you deliver legal services, communicate that to clients under Rule 1.4:

• Explain benefits (efficiency, faster drafting).

• Explain risks (data handling, reliability, hallucinations).

• Offer an AI‑free option.

Written engagement terms that address AI use can save hard conversations later if something goes sideways.

5. Revisit Your “Bad Facts” Mindset

Reading this Delaware opinion, you see how internal strategy — including AI‑assisted plotting — can become a litigation exhibit.  For lawyers, that’s an invitation to ask: 

“If this prompt or chatbot conversation showed up in an opinion, would I be comfortable defending it under the Model Rules?”

If the answer is no, don’t send it. That simple heuristic scales across tools and platforms.

What This Case Signals for the Next Wave of Legal Tech 🌊

There can be significant legal consequences for AI chatbot misuse in legal disputes.

The opinion in Fortis Advisors v. Krafton is not an ethics decision aimed at lawyers, but it shows courts will:

• Scrutinize AI‑assisted strategies as part of broader narratives about good faith, bad faith, and pretext.

• Expect parties — and by extension, counsel — to maintain and produce AI‑related records where relevant.

• Be unimpressed by attempts to retroactively justify decisions made for economic reasons with thin “quality” or “readiness” arguments. 

As public models get more powerful and more embedded in practice, ABA Model Rules on competence, confidentiality, supervision, and candor apply just as they did when lawyers moved to email, smartphones, and the cloud. AI is just the next tool — but it’s a tool that makes it very easy to generate sophisticated bad ideas quickly.

Your job is to keep your ethical compass steady, even when the chatbot is very persuasive. 🧭

MTC

MTC: Perplexity for Legal vs. Lexis, Westlaw, and vLex Fastcase: What Today's Lawyers Need to Know About Reliability, Cost, and Ethics

Tech-savvy lawyers need to HARNESs AI legal research tools!

If you practice law in 2026 and you're even mildly AI‑curious, you've probably seen the recent announcement of Perplexity for Legal, Perplexity's enterprise offering designed specifically for law firms and legal teams. 🧠 Now the field is more crowded than ever: Lexis+ AI/Protege, Westlaw Edge/Precision, and vLex Fastcase with Vincent AI are all vying for a place in your workflow—and Perplexity is asking a provocative new question: do you even need the legacy companies anymore? For solo and small‑to‑medium firm practitioners, the real question is simple. How does each of these platforms serve you in daily practice, and how do you choose responsibly?

What Perplexity for Legal Actually Offers

Perplexity's legal-focused enterprise product is built around its core strengths: fast, cited answers, deep multi‑source research, and the ability to connect to your firm's internal knowledge bases. You ask a question, see sources inline, and move from a synthesized answer directly into primary authority—or into firm work product—without hopping across multiple systems.

Highlighted use cases include:

• Staying current on legal developments across jurisdictions in real time.

• Generating client‑ready research memos faster.

• Drafting pitch materials and Request for Proposal responses by pulling context from internal documents.

Firms like Gunderson Dettmer report using Perplexity Enterprise to scale legal research on rapidly evolving topics such as emerging company financings and technology transactions. 🚀 Latham & Watkins uses it for market intelligence and tactical research. For solos and small firms, the benefit is more pragmatic: less time wrestling with search syntax, more time actually thinking like a lawyer.

If you're a regular reader and listener of The Tech-Savvy Lawyer.Page blog and podcast, we discuss this type of workflow can enhance your firm's productivity effectively and safely.

Meet the Field: Lexis, Westlaw, and vLex Fastcase

Before we stack Perplexity against the competition, it helps to understand what each incumbent actually is today—because the landscape has shifted considerably.

Lexis+ AI layers generative AI on top of LexisNexis's curated legal content and the powerful Shepard's citator. Its AI features are bundled into subscriptions that can run from the low hundreds to several hundred dollars per user per month, depending on coverage tier. Pricing is often opaque and driven by long-term contract negotiation rather than transparent published rates—a persistent frustration for small firms.

Westlaw Edge/Precision integrates Thomson Reuters' generative AI capabilities directly into the Westlaw research ecosystem, pairing them with KeyCite and deep editorial enhancements. Like Lexis, its pricing sits at the premium end of the market, and it is best suited for firms that already rely heavily on Westlaw's proprietary citator and editorial content.

vLex Fastcase is the most democratically accessible of the three. After Fastcase merged with vLex in 2023 and vLex was subsequently acquired by Clio, the combined platform now serves over one million lawyers nationwide through partnerships with 80+ state, county, and specialty bar associations—often as a free member benefit. At the heart of its AI offering is Vincent, vLex's AI legal assistant, which handles research, drafting, document analysis, and customizable workflows through a feature called Vincent Studio for enterprise teams. The platform's Cert citator flags negative treatment and authority, replacing the older Bad Law Bot, while AI Case Analysis generates automated headnotes and summaries. For many solos and small-firm practitioners, vLex Fastcase is effectively free through their bar membership—making it arguably the highest-value entry point in the market.

If you are a member of the Florida Bar, California Lawyers Association, Illinois State Bar, or any of the dozens of other partnered associations, you likely already have access to vLex Fastcase Premium (a $995/year value) at no additional charge.

Reliability: Can You Trust These Platforms for Legal Research?

today’s lawyers need to evaluate AI legal platforms, pricing, and ethics.

Reliability is the first concern I hear from lawyers when AI enters the conversation—something we cover on The Tech-Savvy Lawyer.Page. No AI platform is infallible, but they fail in different ways.

Lexis+ AI and Westlaw AI answer from within their proprietary, editorially curated databases. Their hallucination risk is constrained by the quality of their content backbones, but they can still misinterpret authority, overgeneralize from a line of cases, or overlook nuances between jurisdictions.

vLex Fastcase/Vincent answers from vLex's global legal database—over one billion searchable documents across 100+ countries—supplemented by its AI‑powered analysis layer. Vincent has performed strongly in independent AI benchmarking, including the Vals Legal AI Report and a comparative AI evaluation by law librarians. Its Cert citator provides direct verification, making it more trustworthy for authority checking than pure generative systems.

Perplexity for Legal draws from a broad web‑scale index plus any internal data you connect through the enterprise deployment. Its core reliability strength is the inline citation on virtually every statement—you can trace each claim back to a source immediately. Its Deep Research feature structures multi‑step investigations into organized reports with full sourcing. The honest limitation: Perplexity does not have a built-in citator or a curated legal content backbone like KeyCite or Cert. For final authority verification, you still need to confirm via Westlaw, Lexis, vLex Fastcase's Cert, or a reliable citator—no exceptions.

For all four platforms, the universal rule applies: AI answers are drafts, not final work product. Read the cases. Check the citations. Verify the authority. 📋

Ethics: ABA Model Rules and AI Research

Using any AI tool in legal practice implicates several ABA Model Rules, and the analysis is the same whether you use Perplexity, Lexis+ AI, Westlaw, or vLex Fastcase:

Rule 1.1 (Competence). Comment 8 requires lawyers to understand the benefits and risks of relevant technology. This means knowing how each tool generates its answers, where it can fail, and how to verify its output. You cannot delegate judgment to any AI—Perplexity, Vincent, or otherwise.

Rule 1.6 (Confidentiality). Enterprise deployments of Perplexity are designed to isolate firm data and not train public models on your inputs. vLex Fastcase, operating within the Clio ecosystem, also maintains firm-level data controls. Regardless of which platform you use, you must confirm the contractual and technical safeguards before loading confidential client information. Never use a consumer-grade tool without verified protections.

Rule 5.3 (Responsibilities Regarding Non-Lawyer Assistance). AI is, functionally, a non-lawyer assistant. You must supervise its use, review its output, and ensure that the work product it generates meets your professional obligations. Vincent Studio's custom workflows are an interesting development in this regard—they allow firms to embed review and compliance steps directly into AI workflows, which supports Rule 5.3 compliance by design.

Rule 1.4 (Communication). If AI tools materially change how you handle matters—especially in flat-fee engagements—consider whether to disclose that to clients. Doing so can build trust and align expectations.

These obligations are vendor‑agnostic. The ABA Model Rules care about your conduct, not your software logo. ⚖️

💰 Cost and Access: The Solo and Small‑Firm Reality

For solos and small‑to‑medium firms, cost is where decisions often get made. A realistic comparison in 2026 looks like this:

• Lexis+ AI: Bundled AI features run roughly $125–$275 per user per month at the low to mid-tier; enterprise tiers go significantly higher. Opaque pricing and long-term contracts are common complaints.

• Westlaw Edge/Precision: Premium pricing in the hundreds of dollars per month per user, with AI features integrated at the top tiers. Best suited for firms already embedded in the Westlaw ecosystem.

• vLex Fastcase: Free to bar association members for the core plan, with a retail value around $995 per year. Vincent AI premium features (50-state surveys, drafting tools) require a paid upgrade, but bar members often get discounted access. For many solos, this is already sitting in their inbox—they just haven't activated it.

• Perplexity for Legal (Enterprise): Enterprise pricing is generally more transparent and leaner than full Lexis/Westlaw stacks. Exact per-seat pricing varies by deployment, but it is positioned as an accessible AI layer rather than an all-in-one legal publisher.
  
  💡 Tip: Solos and Small Firms, check out if the Enterprise Pro plan meets you needs - Perplexity Enterprise Pro runs a fraction of the cost of Lexis+ AI or Westlaw Precision—platforms that can run $125–$275 per user per month or more—making it one of the most cost-competitive AI research tools available to solo and small-firm practitioners today.

The practical calculus for solos and small firms:

• If you already have Lexis or Westlaw, Perplexity can complement them for early-stage research, cross-domain intelligence, and drafting.

• If you have vLex Fastcase through your bar, you already have a solid free primary law backbone with built-in AI. Pairing that with Perplexity Enterprise gives you AI synthesis capabilities across web-scale sources at a potentially lower total cost than upgrading to premium Lexis or Westlaw AI tiers.

• If you are starting from scratch, the vLex Fastcase bar benefit plus a Perplexity Enterprise subscription may deliver more value per dollar than any single legacy vendor stack. 💸

That is not a recommendation to ditch Lexis or Westlaw wholesale—their curated content and citator infrastructure remain industry benchmarks. It is a recommendation to audit what you actually use and design a deliberate stack around it.

A Practical Framework for Choosing and Using These Tools

tech-savvy lawyers need to compare modern ai- vs legacy- legal research tools.

• Keep Lexis/Westlaw if you heavily use KeyCite/Shepard's, proprietary treatises, or sophisticated editorial enhancements.

• Activate vLex Fastcase through your bar if you haven't already—it's free for most practitioners and now includes genuine AI capabilities via Vincent.

• Use Perplexity for Legal for early-stage issue spotting, multi-jurisdiction surveys, cross-domain research, and AI-assisted first drafts of memos and correspondence.

• Anchor everything in the ABA Model Rules:

  • Competence: know how each tool works and where it fails.

  • Confidentiality: enterprise deployments only, with verified data protections.

  • Supervision: treat all AI output as a first draft to be reviewed and verified.

• Write an internal AI use policy specifying which tools are authorized, for which tasks, and how outputs are verified and documented.

The question is never "Which one wins?" It's "How do I build a balanced, ethical, cost-conscious research stack that serves my clients well?" That's what it means to be a truly tech-savvy lawyer. 💼

MTC: Why Rising PC and AI Tool Prices (for Windows and Apple) Should Be on Every Lawyer’s Radar in 2026

Law firms need to plan Windows, Mac, and AI refresh strategy

If you feel like every new laptop quote is 15–20% higher than last year, you are not imagining things. 📈 And if your favorite AI drafting or transcript tool pinged you with a “small” price adjustment this spring, welcome to the club. 🤖

In our December 2025 editorial, “MTC: The 2026 Hardware Hike: Why Law Firms Must Budget for the ‘AI Squeeze’ Now!”, we warned that a perfect storm in the hardware market was forming: DRAM shortages, surging AI infrastructure demand, and shifting trade policy were about to push PC prices up by 15–20% in 2026. 💻 Then, in April 2026’s “MTC: Why 2026’s PC Price Hikes Put Law Firms at Risk (and Why Many Lawyers Are Quietly Switching to Macs)”, we explored how rising Windows laptop prices were reshaping law firm hardware decisions and eroding the old assumption that “Windows is always cheaper than Mac.”

Those forecasts are now reality across both Windows PCs and Macs, and the question I keep hearing from solo and small firm lawyers is simple: Should I be worried?

The short answer is yes—concerned, not paralyzed. The better question is: how do we respond strategically, in a way that respects both our budgets and our ethical obligations under ABA Model Rules 1.1 (Competence) and 1.6 (Confidentiality)?

A quick recap: what’s driving the price surge?

Let’s start with the “why,” because context matters when you sit down with your next-year budget spreadsheet. 📊

Industry analysts now confirm that average PC prices are rising in the 15–20% range for 2026, with memory costs as the biggest driver. AI data centers—those massive server farms powering tools like ChatGPT and other LLMs—are soaking up an estimated majority of advanced DRAM production, leaving less capacity for business laptops and desktops of all flavors, whether they run Windows or macOS. When memory becomes scarce and expensive, everything that relies on it gets pricier.

You can see this in both ecosystems:

Lawyers need t plan their 2026 law firm hardware budget amid rising costs

• Windows side: In April, Microsoft sharply raised prices across its Surface lineup, including the Surface Pro and Surface Laptop families, many lawyers rely on. Entry-level machines that once started under 1,000 dollars now begin well above that mark, with some configurations jumping several hundred dollars over launch prices and in some cases exceeding roughly comparable MacBook configurations.

• Apple side: In June, Apple CEO Tim Cook told The Wall Street Journal that Apple will raise prices because the company can no longer absorb skyrocketing memory and storage costs, calling the situation a “hundred-year flood” and saying he has “never seen anything like it in any area in over 40 years,” describing these increases as “unavoidable.” Apple to Raise Prices Due to Memory Chip Crunch, Tim Cook Says.

When both Microsoft and Apple are telling you that memory costs and component shortages are forcing them to push prices up, that is not a platform rivalry story. It is a signal that the entire hardware market—Windows and Mac alike—is being repriced around the AI era.

On top of that, trade policy and tariffs have increased costs for components and final assembly in key manufacturing hubs like China and Taiwan. Vendors have responded by tightening quote windows and baking in risk premiums, which is why the Windows laptop or Mac you priced in Q4 2025 quietly jumped in Q2 2026. 💸

In “MTC: The 2026 Hardware Hike”, we urged firms to accelerate planned refreshes where possible, prioritize RAM over storage, and budget for stronger machines instead of downgrading specs. In the April 2026 editorial, we drilled into how those same forces made some Mac configurations look surprisingly competitive—and why lawyers should stop treating “Windows versus Mac” as a matter of habit and start treating it as a structured evaluation tied to performance, security, and ethical duties. All of that guidance still holds.

Budgeting like a law practice, not a gadget hobby (PC‑neutral framing)

The theme of “MTC: The 2026 Hardware Hike” was simple: treat your tech like a planned, recurring investment—not a last-minute scramble when a laptop dies in the middle of trial prep. The April 2026 follow-up on PC price hikes showed how that planning must now account for both Windows and Mac options, since price gaps have narrowed or flipped depending on configuration.

Here is the approach I recommend for solos and small firms, regardless of platform:

1. Inventory and classify your devices across platforms.
   Capture which users are on Windows, which are on macOS, and what roles those machines play. Prioritize devices used for active litigation, client communications, and high-sensitivity matters.

2. Set a realistic refresh cycle that is OS‑aware.
   For most law practices, a 3–5 year cycle for primary laptops and desktops is reasonable, but the exact timing should reflect each platform’s support timeline—Windows 10 reaching end of support, macOS versions aging out, and vendor firmware commitments.

3. Budget for “competence grade” hardware on both sides.
   As we argued in both the December and April MTC pieces, it is better to buy fewer, well‑specced machines—whether that is a mid-range Surface Laptop or a MacBook Air with sufficient RAM—than to chase the absolute lowest price and end up with systems that choke under AI‑enhanced workflows.

4. Run a structured Windows vs. Mac evaluation, not a loyalty contest.
   Following the April article’s recommendation, build a simple matrix comparing specific Windows and Mac models on price, RAM, storage, performance, security features (like Secure Boot, Secure Enclave, or TPM), support life, and compatibility with your core practice software. Tie that matrix explicitly to your responsibilities under ABA Model Rules 1.1 and 1.6 so you can show you exercised reasonable diligence.

5. Cull redundant subscriptions before sacrificing baseline hardware on either platform.
   Before you decide that “Macs are too expensive now” or “Windows machines are out of reach,” examine your monthly AI and SaaS spend. Many firms can free up budget for better Windows or Mac hardware by retiring overlapping tools that deliver marginal benefits.

This is not about declaring a winner in the Windows vs. Mac debate. It is about recognizing that both ecosystems are affected by the same structural forces—AI‑driven memory demand, supply constraints, tariffs—and that your ethical obligations apply regardless of logo. ⚖️

So, should lawyers be worried? (PC‑neutral conclusion)

Concern is justified. Panic is not. 😅

Law firmS of every size need to plan Windows, Mac, and AI refresh strategy

Yes, Windows PC and Mac prices are rising and are likely to remain elevated through at least 2027, given ongoing DRAM constraints and AI demand. Yes, AI and cloud tools are adjusting their pricing and tiers in ways that can catch an unprepared firm off guard. And yes, when Microsoft raises Surface prices, and Tim Cook says he has never seen a memory crunch like this in over 40 years and calls it a “hundred-year flood,” those are market‑wide signals—not platform‑centric marketing talking points.

But you still have levers to pull, no matter which platform you use:

• Plan your hardware lifecycle instead of reacting to failures.

• Prioritize “competence grade” devices and security over optional features, whether that is a mid‑range Windows laptop or a MacBook with enough RAM.

• Rationalize your AI and SaaS stack so you pay for what actually moves the needle.

• Treat your tech stack as part of your ethics compliance, not just overhead. ⚖️

Lawyers on both Windows and Mac should treat 2026’s hardware and AI price hikes as a market‑wide issue that affects competence, confidentiality, and client service—not as a referendum on one platform. 💻⚖️

MTC

MTC: From Shingles to SEO to GEO: The History of Lawyer Advertising and the Ethics That Still Govern It

From hanging a shingle to GEO-driven law firm visibility!

If you listen only to today’s marketing jargon, you might think lawyer advertising started with SEO (Search Engine Optimization) and ends with GEO—Generative Engine Optimization. In reality, the story begins with word of mouth, a wooden shingle, and a profession that worried about dignity long before anyone worried about keywords. The tools have changed repeatedly, but the ethical backbone has stayed remarkably consistent.

The ABA didn’t adopt the Model Rules of Professional Conduct until 1983, yet the core prohibitions we now see in Rules 7.1, 7.2, and 7.3—no false or misleading communications, limits on advertising, and restrictions on solicitation—simply codified principles that were already there. As we move from classic SEO into GEO, those same principles should still keep us grounded, especially for solos and small firms tempted to let AI do too much of the talking. 🤖

Before the Codes: Reputation and Norms

In the late 19th and early 20th centuries, there was no ABA Model Rule 7.1, no Model Code, and no national advertising standard. Lawyers built practices through referrals, courthouse reputations, civic involvement, and the quiet endorsements of former clients. Marketing was informal and relational, but that didn’t mean it was unregulated; courts and local bars still sanctioned dishonesty, fraud, and improper solicitation.

What we now call “communications concerning a lawyer’s services” was mostly face-to-face, but the expectation was already clear: do not lie, do not overreach, and do not exploit people at vulnerable moments. Those instincts would later become structured into the Canons, the Model Code, and ultimately the Model Rules.

1908–1969: Canons and the Shingle-to-Directory Transition

The ABA adopted the Canons of Professional Ethics in 1908, its first national ethics code, drawing heavily from an 1887 Alabama code and other local precedents. The Canons emphasized dignity, restraint, and loyalty to the client—not revenue at any cost. Advertising was generally discouraged, but basic identification (your name, that you were a lawyer, and where you could be found) was tolerated.

This is the era of “hanging a shingle”—literally putting up a sign that said you were an attorney—and later of simple listings in early directories and the White Pages. The shingle and the simple listing are analog ancestors of your Google Business Profile today: name, practice, contact information. 🪧 The message was informational, not boastful, which is exactly the line modern Rule 7.1 tries to maintain.

Yellow Pages and the Rise of Display Advertising

Lawyer advertising evolution: referrals, Yellow Pages, SEO, and GEO

As the telephone spread, lawyers moved from the White Pages into the Yellow Pages, and that’s where things changed. Yellow Pages display ads offered space for slogans, graphics, and bold type. By the late 20th century, they were one of the most important consumer marketing channels for lawyers, especially in personal injury, family law, and criminal defense.

During much of this period the profession was governed by the Model Code of Professional Responsibility (adopted in 1969), which carried forward the Canons’ skepticism of overt advertising. Some bars attempted to maintain near-blanket bans on lawyer ads, while others allowed limited, highly regulated Yellow Pages entries. The underlying concern, however, was familiar: Advertising that created unjustified expectations, promised results, or made unverifiable “best lawyer” claims was considered unethical—an early expression of what would become the Model Rule 7.1 prohibition on false or misleading communications.

Bates and the Birth of Modern Lawyer Advertising

Everything shifted in 1977 when the Supreme Court decided Bates v. State Bar of Arizona. The Court held that lawyer advertising is commercial speech protected by the First Amendment, striking down a state disciplinary rule that effectively banned ads by lawyers. The Court recognized that consumers need information about legal services and cannot evaluate lawyers if they are kept in the dark.

Bates did not remove ethical guardrails. It confirmed that states may still prohibit false, deceptive, or misleading advertising and may impose reasonable rules to protect the public. In modern terms, Bates opened the door to lawyer advertising but left the profession responsible for staying on the right side of truthfulness, clarity, and fair dealing.

1983–Present: Model Rules, the Web, and SEO

In 1983, the ABA replaced the Model Code with the Model Rules of Professional Conduct, which remain the baseline for state rules today. Three provisions matter most for marketing:

• Model Rule 7.1 – A lawyer shall not make a false or misleading communication about the lawyer or the lawyer’s services.

• Model Rule 7.2 – Lawyers may advertise through various media, subject to 7.1 and restrictions on paying for recommendations.

• Model Rule 7.3 – Governs solicitation of clients, especially direct, real-time contact with people who may be vulnerable to undue influence.

When law firms began building websites in the 1990s and early 2000s, those sites were simply new “media” under Rule 7.2 and subject to the same truthfulness requirements as a print ad. As SEO emerged, lawyers learned to optimize pages for terms like “car accident lawyer” or “divorce attorney near me,” and local search became the new Yellow Pages.

The temptation, then as now, was to let the algorithm drive the ethics. Yet nothing in the Model Rules says “this doesn’t count if you’re trying to rank.” Every meta description, headline, and testimonial remains a communication about your services under 7.1.

Remember, your website is your biggest ethics footprint. If an SEO consultant suggests language you would never put in a sworn pleading, it probably doesn’t belong on your homepage either.

GEO: Generative Engine Optimization

Comparing classic law firm SEO with modern GEO AI answers

Fast-forward to 2026, and many law firm marketers are talking about GEO—Generative Engine Optimization. GEO focuses on making your content understandable and trustworthy to AI-driven answer engines (ChatGPT, Gemini, Perplexity, Bing Copilot, Google AI Overviews, and similar tools), not just to traditional search rankings.

Where SEO primarily asks, “How do I rank in the list?”, GEO asks, “When a prospective client asks a natural-language question, does an AI system understand my firm, recognize my authority, and cite my content accurately in its answer?” For law firms, GEO strategies generally include:

• Structuring content around clear questions and answers clients actually ask

• Strengthening entity profiles so AI can correctly associate attorneys, practice areas, and locations

• Enhancing trust signals: consistent directory listings, complete bios, reviews, and citations from reputable sources

• Updating content for depth, context, and semantic clarity so generative systems don’t misinterpret your guidanc

If that sounds like “SEO with better structure and more discipline,” you’re not wrong. GEO builds on strong traditional SEO, not replaces it.

Ethically, the message is straightforward: AI is just another channel. If your content is misleading, overbroad, or exaggerated, it does not become acceptable because it is being summarized by a generative engine instead of displayed as a blue link. Rule 7.1 applies regardless of whether a human or an AI is reading your copy.

GEO, AI Tools, and Model Rule Guardrails

For solos and small firms, GEO often intersects with increasing use of AI tools to draft or refine marketing content. That raises several recurring ethics touchpoints:

• Truthful content (Rule 7.1): Any AI-assisted copy that inflates your experience, implies special certification you don’t actually hold, or hints at guaranteed outcomes violates the same rule as if you wrote it manually.

• Supervision and review (Rules 5.1, 5.2, and 5.3): Ethics guidance on AI marketing emphasizes human review protocols: lawyers must review AI outputs for accuracy, tone, and compliance before publishing.

• Solicitation concerns (Rule 7.3): If a GEO-driven workflow extends into chatbots, proactive outreach, or personalized sequences, you must ensure the system isn’t effectively engaging in real-time solicitation of individuals facing stress or duress.

GEO is powerful, but it’s not magic. It does not relieve you of the duty to understand the technology and to ensure that every public-facing statement about your services is accurate and appropriate for the audience.

The Through-Line: What Has Stayed the Same

Lawyer advertising evolution: referrals, Yellow Pages, SEO, and GEO

Once you understand the timeline—no Model Rules in 1890, no GEO in 2000—the continuity becomes obvious:

• The codes changed; the core idea did not. From unwritten norms to the Canons, the Model Code, and the Model Rules, the message is consistent: tell the truth, don’t mislead, and respect client vulnerability.

• Every new channel inherits the old duties. Yellow Pages, websites, SEO, AI answers, and GEO all fall under the same prohibitions on false or misleading communications and improper solicitation.

• Technology amplifies both good and bad. Clear, helpful content that respects the rules will travel farther through generative systems; sloppy or overstated claims will too.

For tech-curious lawyers, the takeaway is simple: be excited about GEO, but not starstruck. ✨ Use it to structure better answers, not to stretch the truth. Let AI and generative engines distribute your expertise, not redefine your ethics.

MTC

MTC: AI Voice Cloning, Deepfake Fraud, and Crime Junkie: What Lawyers Must Learn Now ⚖️🧠

As a tech-savvy and ethically compliant lawyer, are you prepared to handle an ai voice-call scam?

We live in a world where a client can hear their child scream for help over the phone, know that voice down to the quiver in their sobs, and still be wrong about what’s real. At the same time, lawyers are getting “official” calls from spoofed sheriff’s offices demanding Bitcoin bail payments that feel just plausible enough to pass the sniff test. If you think your clients are the only ones at risk, you’re already behind.

As a long-time Crime Junkie fan, I’m grateful to Ashley Flowers, Brit Prawat, and the Audiochuck team for doing something the legal profession hasn’t always done well: translating complex, evolving tech crime into stories real people understand. Their recent warnings about AI voice cloning, virtual kidnappings, and sophisticated online scams are more than compelling podcast episodes—they’re mandatory listening for lawyers who care about their clients, their firms, and their own digital safety.

In this editorial, I want to bridge those Crime Junkie stories into practical takeaways for solo and small-firm lawyers, AI‑curious practitioners, and even tech‑skeptical colleagues. We’ll look at how these scams work, how the ABA Model Rules already expect you to understand enough technology to spot them, and how to turn “true crime” lessons into concrete safeguards for your practice. ⚙️

When Your Ears Can’t Be Trusted: AI Voice Cloning and Virtual Kidnappings 🎙️

In “WARNING: AI Voice Cloning and Virtual Kidnappings,” Crime Junkie walks us through a terrifying call to a mother who hears her daughter sobbing, begging for her life, while a man demands a ransom and lays out graphic threats. The twist, as many of us now know, is that the daughter is safe; the “kidnappers” are using AI‑cloned audio drawn from a tiny sample of her voice to weaponize panic.

Researchers cited in the episode describe how low‑cost AI tools can create a convincing voice clone from as little as three seconds of audio. Caller ID spoofing then makes it look like the call is coming from the victim’s phone, while scammers press for fast, untraceable payments in cash, gift cards, or crypto. The technology is cheap, the scripts are refined, and the goal is simple: override your critical thinking before you can verify anything.

From a legal ethics perspective, this isn’t just an interesting cybersecurity anecdote. ABA Model Rule 1.1 on competence—especially Comment 8—requires you to stay abreast of “the benefits and risks associated with relevant technology.” An environment where your client can be tricked into paying a fake ransom, or where your own voice can be cloned to mislead staff or opposing parties, is very much “relevant technology.”

If you are not talking with clients and staff about AI‑driven fraud risk, you are not just missing a teaching moment—you may be edging toward a competence problem under the Model Rules.

Lessons for Client Counseling: Safe Words, Verification, and Panic‑Proof Plans 🛟

One of the most practical takeaways in the AI voice cloning episode is also one of the simplest: set a family and a seperate law office “safe word” and rehearse how to verify calls under extreme stress. The FBI, National Cybersecurity Alliance, and digital forensics experts interviewed for the episode all echo the same theme—pre‑commitment beats improvisation when panic hits.

This is precisely the kind of low‑tech, high‑impact advice lawyers can—and should—be giving in client counseling sessions, especially with:

• Family law clients dealing with high‑conflict co‑parenting or domestic violence

• Estate planning clients with vulnerable or elderly relatives

• Business clients whose executives or finance staff could be targeted by “CEO voice” scams

Here’s a concrete, lawyer‑friendly checklist you can adapt:

1. Safe Word Policy
   Encourage clients to adopt a family or organizational safe word, shared only in person or via secure channels, for any call alleging an emergency or ransom demand.

2. Verification Protocols
   Teach clients to verify via a second channel: call back on a known number, text from another device, or contact a third person who can physically locate the supposed victim.

3. Call 911 First When in Doubt
   Emphasize that if they believe a life is at risk, they should call 911—even if they suspect it might be a scam. Law enforcement can help triage the situation; if it’s a scam, they can sort that out after.

4. Evidence Preservation
   Tell clients to screenshot call logs, save audio, and preserve any “proof of life” photos or messages before they disappear, as some software can make photos exist only for seconds. Those artifacts can be invaluable if law enforcement or insurers later investigate.

This kind of counseling fits squarely within ABA Model Rule 2.1 (Advisor), which encourages lawyers to consider “moral, economic, social, and political factors” in advising clients. You’re not just parsing statutes; you’re helping clients design their own risk‑management frameworks in a world where even their senses can be hacked.

The second Crime Junkie episode I wanted to share, "WARNING: Online Scams", focused on other kinds of scams involving technology:

How Scammers Use Our Systems Against Us: Fake Warrants, Bitcoin Bail, and “Officer Smith” 👮‍♂️💸

Lawyers, are you prepared to advise your client on ai scams?

A couple receives a voicemail from what appears to be their local sheriff’s office, learns there’s a warrant for missing jury duty, and is told they can avoid booking if they pre‑pay bail via Bitcoin and Venmo. They do their homework—they verify the number online, they look up “Officer Smith,” they cross‑check the department. Yet they still end up running between ATMs, feeding money into a Bitcoin kiosk, and nervously wiring funds to what looks like a legitimate bail account.

Only later, after calling a non‑emergency line and getting a return call from a blocked number (as their real department actually uses [versus the scammer’s phone number that appeared on their caller ID), do they learn the uncomfortable truth: the “bail by Bitcoin” story was a scam.

Crime Junkie does an excellent job breaking the lessons down into clear rules:

• Police will not call to give you a “heads‑up” that you’ve broken the law.

• Bail is paid in person, not by Bitcoin, gift card, or Venmo.

• Hanging up and calling back on a separately verified number can serve as an important safety/security step.

For lawyers, these stories are a vivid reminder that many scams are “legal‑adjacent”—they borrow just enough from real procedures (jury duty, warrants, bail, sheriff’s offices) to feel legitimate. That makes them particularly dangerous for our clients and our staff, who may over‑defer to anything with a whiff of authority.

Under ABA Model Rule 5.3, lawyers have an obligation to ensure that nonlawyer assistants act in a manner compatible with the lawyer’s professional obligations. That includes training staff to handle legal‑sounding calls skeptically: to question unusual payment methods, verify claims through known channels, and escalate suspicious calls before anyone withdraws or wires funds.

If your receptionist or office manager wouldn’t know how to respond to a call like the one just described, that’s a training gap you can fix—ideally before it becomes a loss.

Fraud in the Grey Zones: Sugar Daddies, Freelance Gigs, and Client Shame 🧾

Crime Junkie also covers scams that operate in more personal and sometimes stigmatized spaces: sugar‑daddy arrangements gone wrong; freelance “job offers” that rely on fraudulent checks; supposed production gigs that pay you to buy equipment, then claw back your real money once the check bounces.  These scams involve computers, phones, the World Wide Web, and even an electronically altered check

In the sugar‑daddy story, a young woman on a sugar‑daddy online platform is manipulated into buying hundreds of dollars’ worth of Steam gift cards to “prove” she’s not scamming her would‑be benefactor, only to realize too late that she’s been exploited. In the job offer story, a freelance audio professional is mailed a check to buy gear for a production; he wisely flags the check, closes his account, and discovers that the job posting piggybacked on a real company’s identity.

Three legal practice lessons stand out here:

lawyers and their clients can learn a lot from shows like crime junkie about ai scams and their impact on their clients!

1. Clients may not tell you everything, especially if the scam involves sex, money, or perceived “stupidity.” The victims in these cases describe deep embarrassment and shame, which initially kept them from reporting to the police. For lawyers, this kind of hesitation could cause further bar issues beyond the incident itself.

2. Financial exploitation often intersects with the kinds of matters solos and small firms already handle. Think consumer protection, elder law, family law, or small business disputes. Clients who’ve been scammed may appear with half‑formed stories, partial evidence, and a strong desire to move on rather than report.

3. Failing to respond promptly—or at all—to suspected scams or financial exploitation can compound the harm and create independent ethics problems. When a lawyer ignores red flags, delays advising the client, or fails to investigate and remediate potential trust‑account or fraud issues, regulators may view that as a separate violation of duties of competence, diligence, communication, and safeguarding client property, even if the underlying scam originated outside the firm. In extreme cases, a pattern of slow or inadequate responses can trigger bar complaints or disciplinary investigations that focus less on the initial scam and more on the lawyer’s failure to act once on notice.

ABA Model Rule 1.4 (Communication) and 1.14 (Client with Diminished Capacity) come into play here. You must explain matters to clients in a way they can understand, but you also need to create a space where they can safely share how they were targeted without fear of ridicule. That’s emotional work, not just analytical work.

One practical move: incorporate scam‑screening questions into your intake forms and interviews. Ask clients explicitly whether anyone has recently requested unusual payment methods, impersonated a government agency, or pressured them to act quickly under threat of legal or physical harm.

Firm‑Level Risk: Deepfakes, Staff Training, and Incident Response 🏢🔐

These Crime Junkie episodes also raise uncomfortable questions about law firm operations. What happens when it’s not a client but you whose voice is cloned? What if a deepfake of your voice instructs staff to release trust funds or share confidential documents?

In “WARNING: AI Voice Cloning and Virtual Kidnappings,” the FBI describes how scammers run these operations like call centers, constantly cycling through numbers and scripts to maximize success. The same industrialization is happening in business email compromise (BEC) and invoice fraud—areas where law firms are already prime targets.

Three concrete actions you can take at the firm level:

1. Adopt a “trust but verify” rule for any out‑of‑band instruction involving money or confidential data. No transfer of client funds, no disbursement of settlement proceeds, and no release of sensitive documents should happen based on a single phone call, even if the caller “sounds” like you.

2. Implement multi‑factor workflows, not just multi‑factor authentication. For example, any financial instruction must be confirmed via a second channel (secure client portal, verified email, or in‑person) before action. 

3. Document an incident response plan that includes deepfake and scam scenarios. ABA Model Rules 1.6 (Confidentiality) and 5.1 (Responsibilities of Partners and Supervisory Lawyers) expect you to have reasonable safeguards and supervisory structures. That includes knowing what to do when—not if—your systems or people are tested.

These are precisely the kinds of measures we walk through in The Tech-Savvy Lawyer.Page blog and podcast episodes on AI, deepfakes, and metadata—where we discuss the intersection of ethics, evidence, and emerging tech.

Bridging Crime Junkie and Legal Ethics: Story as a Compliance Tool 📚✨

lawyers need TO think calmly when confronted with ai scams let alone any scam!

One of the most useful things about Crime Junkie is that Ashley and Brit don’t just scare you; they give you scripts, safe‑word strategies, and “here’s what to do next” checklists. Lawyers can—and should—borrow that model.

Instead of sending clients dense policy memos, consider:

• Sharing these specific episodes with a short email explaining why they matter:

• “WARNING: AI Voice Cloning and Virtual Kidnappings” – Crime Junkie’s breakdown of how cloned voices fuel virtual kidnapping scams and what the FBI recommends.

• “WARNING: Online Scams”, the online scams episode about fake warrants, sugar daddies, job scams, and fraudulent checks.

• Pairing the episode with your own one‑page client guide that translates the stories into local, practical legal advice—how your jurisdiction handles actual warrants, how bail really works, and how you want clients to contact you if they suspect a scam.

• Integrating these stories into CLEs and staff training, using them as case studies for ABA Model Rule 1.1 (Competence), 1.6 (Confidentiality), 1.4 (Communication), and 5.3 (Nonlawyer Assistants).

The goal isn’t to turn your practice into a true crime podcast. It’s about leveraging narratives your clients and staff will actually remember when the phone rings, the voice shakes, and the clock starts ticking.

Lawyers in words, facts, and rules. But in an era of AI voice cloning, deepfake fraud, and industrialized scamming, the difference between a near‑miss and a catastrophe may come down to whether your clients have heard the right story—and practiced the right response—before the crisis hits.

So grab your headphones, queue up Crime Junkie, and then bring those lessons into your practice. Your clients, your firm, and yes, you, will be safer for it. 🎧⚖️