MTC: “Legal AI institutional memory” engages core ethics duties under the ABA Model Rules, so it is not optional “nice to know” tech.⚖️🤖

Institutional Memory Meets the ABA Model Rules

“Legal AI institutional Memory” is AI that remembers how your firm actually practices law, not just what generic precedent says. It captures negotiation history, clause choices, outcomes, and client preferences across matters so each new assignment starts from experience instead of a blank page.

From an ethics perspective, this capability sits directly in the path of ABA Model Rule 1.1 on competence, Rule 1.6 on confidentiality, and Rule 5.3 on responsibilities regarding nonlawyer assistance (which now includes AI systems). Comment 8 to Rule 1.1 stresses that competent representation requires understanding the “benefits and risks associated with relevant technology,” which squarely includes institutional‑memory AI in 2026. Using or rejecting this technology blindly can itself create risk if your peers are using it to deliver more thorough, consistent, and efficient work.🧩

Rule 1.6 requires “reasonable efforts” to prevent unauthorized disclosure or access to information relating to representation. Because institutional memory centralizes past matters and sensitive patterns, it raises the stakes on vendor security, configuration, and firm governance. Rule 5.3 extends supervision duties to “nonlawyer assistance,” which ethics commentators and bar materials now interpret to include AI tools used in client work. In short, if your AI is doing work that would otherwise be done by a human assistant, you must supervise it as such.🛡️

Why Institutional Memory Matters (Competence and Client Service)

Tools like Luminance and Harvey now market institutional‑memory features that retain negotiation patterns, drafting preferences, and matter‑level context across time. They promise faster contract cycles, fewer errors, and better use of a firm’s accumulated know‑how. Used wisely, that aligns with Rule 1.1’s requirement that you bring “thoroughness and preparation” reasonably necessary for the representation, and Comment 8’s directive to keep abreast of relevant technology.

At the same time, ethical competence does not mean turning judgment over to the model. It means understanding how the system makes recommendations, what data it relies on, and how to validate outputs against your playbooks and client instructions. Ethics guidance on generative AI emphasizes that lawyers must review AI‑generated work product, verify sources, and ensure that technology does not substitute for legal judgment. Legal AI institutional memory can enhance competence only if you treat it as an assistant you supervise, not an oracle you obey.⚙️

Legal AI That Remembers Your Practice—Ethics Required, Not Optional

How Legal AI Institutional Memory Works (and Where the Rules Bite)

Institutional‑memory platforms typically:

• Ingest a corpus of contracts or matters.

• Track negotiation moves, accepted fall‑backs, and outcomes over time.

• Expose that knowledge through natural‑language queries and drafting suggestions.

That design engages several ethics touchpoints🫆:

• Rule 1.1 (Competence): You must understand at a basic level how the AI uses and stores client information, what its limitations are, and when it is appropriate to rely on its suggestions. This may require CLE, vendor training, or collaboration with more technical colleagues until you reach a reasonable level of comfort.

• Rule 1.6 (Confidentiality): You must ensure that the vendor contract, configuration, and access controls provide “reasonable efforts” to protect confidentiality, including encryption, role‑based access, and breach‑notification obligations. Ethics guidance on cloud and AI use stresses the need to investigate provider security, retention practices, and rights to use or mine your data.

• Rule 5.3 (Nonlawyer Assistance): Because AI tools are “non‑human assistance,” you must supervise their work as you would a contract review outsourcer, document vendor, or litigation support team. That includes selecting competent providers, giving appropriate instructions, and monitoring outputs for compliance with your ethical obligations.🤖

Governance Checklist: Turning Ethics into Action

For lawyers with limited to moderate tech skills, it helps to translate the ABA Model Rules into a short adoption checklist.✅

When evaluating or deploying legal AI institutional memory, consider:

1. Define Scope (Rules 1.1 and 1.6): Start with a narrow use case such as NDAs or standard vendor contracts, and specify which documents the system may use to build its memory.

2. Vet the Vendor (Rules 1.6 and 5.3): Ask about data segregation, encryption, access logs, regional hosting, subcontractors, and incident‑response processes; confirm clear contractual obligations to preserve confidentiality and notify you of incidents.

3. Configure Access (Rules 1.6 and 5.3): Use role‑based permissions, client or matter scoping, and retention settings that match your existing information‑governance and legal‑hold policies.

4. Supervise Outputs (Rules 1.1 and 5.3): Require that lawyers review AI suggestions, verify sources, and override recommendations where they conflict with client instructions or risk tolerance.

5. Educate Your Team (Rule 1.1): Provide short trainings on how the system works, what it remembers, and how the Model Rules apply; document this as part of your technology‑competence efforts.

Educating Your Team Is Core to AI Competence

This approach respects the increasing bar on technological competence while protecting client information and maintaining human oversight.⚖️

This approach respects the increasing bar on technological competence while protecting client information and maintaining human oversight.⚖️

MTC: Everyday Tech, Extraordinary Evidence: How Lawyers Can Turn Smartphones, Dash Cams, and Wearables Into Case‑Winning Proof After the Minnesota ICE Shooting 📱⚖️

Smartphone evidence: Phone as Proof!

The recent fatal shooting of ICU nurse Alex Pretti by a federal immigration officer in Minneapolis has become a defining example of how everyday technology can reshape a high‑stakes legal narrative. 📹 Federal officials claimed Pretti “brandished” a weapon, yet layered cellphone videos from bystanders, later analyzed by major news outlets, appear to show an officer disarming him moments before multiple shots were fired while he was already on the ground. In a world where such encounters are documented from multiple angles, lawyers who ignore ubiquitous tech risk missing powerful, and sometimes exonerating, evidence.

Smartphones: The New Star Witness

In the Minneapolis shooting, multiple smartphone videos captured the encounter from different perspectives, and a visual analysis highlighted discrepancies between official statements and what appears on camera. One video reportedly shows an officer reaching into Pretti’s waistband, emerging with a handgun, and then, barely a second later, shots erupt as he lies prone on the sidewalk, still being fired upon. For litigators, this is not just news; it is a case study in how to treat smartphones as critical evidentiary tools, not afterthoughts.

Practical ways to leverage smartphone evidence include:

• Identifying and preserving bystander footage early through public calls, client outreach, and subpoenas to platforms when appropriate.

• Synchronizing multiple clips to create a unified timeline, revealing who did what, when, and from where.

• Using frame‑by‑frame analysis to test or challenge claims about “brandishing,” “aggressive resistance,” or imminent threat, as occurred in the Pretti shooting controversy.

In civil rights, criminal defense, and personal‑injury practice, this kind of video can undercut self‑defense narratives, corroborate witness accounts, or demonstrate excessive force, all using tech your clients already carry every day. 📲

GPS Data and Location Trails: Quiet but Powerful Proof

The same smartphones that record video also log location data, which can quietly become as important as any eyewitness. Modern phones can provide time‑stamped GPS histories that help confirm where a client was, how long they stayed, and in some instances approximate movement speed—details that matter in shootings, traffic collisions, and kidnapping cases. Lawyers increasingly use this location data to:

Dash cam / cameras: Dashcam Truth!

• Corroborate or challenge alibis by matching GPS trails with claimed timelines.

• Reconstruct movement patterns in protest‑related incidents, showing whether someone approached officers or was simply present, as contested in the Minneapolis shooting narrative.

• Support or refute claims that a vehicle was fleeing, chasing, or unlawfully following another party.

In complex matters with multiple parties, cross‑referencing GPS from several phones, plus vehicle telematics, can create a robust, data‑driven reconstruction that a fact‑finder can understand without a computer science degree.

Dash Cams and 360‑Degree Vehicle Video: Replaying the Scene

Cars now function as rolling surveillance systems. Many new vehicles ship with factory cameras, and after‑market 360‑degree dash‑cam systems are increasingly common, capturing impacts, near‑misses, and police encounters in real time. In a Minneapolis‑style protest environment, vehicle‑mounted cameras can document:

• How a crowd formed, whether officers announced commands, and whether a driver accelerated or braked before an alleged assault.

• The precise position of pedestrians or officers relative to a car at the time of a contested shooting.

• Sound cues (shouts of “he’s got a gun!” or “where’s the gun?”) that provide crucial context to the video, like those reportedly heard in footage of the Pretti shooting.

For injury and civil rights litigators, requesting dash‑cam footage from all involved vehicles—clients, third parties, and law‑enforcement—should now be standard practice. 🚗 A single 360‑degree recording might capture the angle that police‑worn cameras miss or omit.

Wearables and Smartwatches: Biometrics as Evidence

GPS & wearables: Data Tells All!

Smartwatches and fitness trackers add a new dimension: heart‑rate, step counts, sleep data, and sometimes even blood‑oxygen metrics. In use‑of‑force incidents or violent encounters, this information can be unusually persuasive. Imagine:

• A heart‑rate spike precisely at the time of an assault, followed by a sustained elevation that reinforces trauma testimony.

• Step‑count and GPS data confirming that a client was running away, standing still, or immobilized as claimed.

• Sleep‑pattern disruptions and activity changes supporting damages in emotional‑distress claims.

These devices effectively turn the body into a sensor network. When combined with phone video and location data, they help lawyers build narratives supported by objective, machine‑created logs rather than only human recollection. ⌚

Creative Strategies for Integrating Everyday Tech

To move from concept to courtroom, lawyers should adopt a deliberate strategy for everyday tech evidence:

• Build intake questions that explicitly ask about phones, car cameras, smartwatches, home doorbell cameras, and even cloud backups.

• Move quickly for preservation orders, as Minnesota officials did when a judge issued a temporary restraining order to prevent alteration or removal of shooting‑related evidence in the Pretti case.

• Partner with reputable digital‑forensics professionals who can extract, authenticate, and, when needed, recover deleted or damaged files.

• Prepare demonstrative exhibits that overlay video, GPS points, and timelines in a simple visual, so judges and juries understand the story without technical jargon.

The Pretti shooting also underscores the need to anticipate competing narratives: federal officials asserted he posed a threat, while video and witness accounts cast doubt on that framing, fueling protests and calls for accountability. Lawyers on all sides must learn to dissect everyday tech evidence critically—scrutinizing what it shows, what it omits, and how it fits with other proof.

Ethical and Practical Guardrails

Ethics-focused image: Ethics First!

With this power comes real ethical responsibility. Lawyers must align their use of everyday tech with core duties under the ABA Model Rules of Professional Conduct.

• Competence (ABA Model Rule 1.1)
  Rule 1.1 requires “competent representation,” and Comment 8 now expressly includes a duty to keep abreast of the benefits and risks of relevant technology. When you rely on smartphone video, GPS logs, or wearable data, you must either develop sufficient understanding yourself or associate with or consult someone who does.

• Confidentiality and Data Security (ABA Model Rule 1.6)
  Rule 1.6 obligates lawyers to make reasonable efforts to prevent unauthorized access to or disclosure of client information. This extends to sensitive video, location trails, and biometric data stored on phones, cloud accounts, or third‑party platforms. Lawyers should use secure storage, limit access, and, where appropriate, obtain informed consent about how such data will be used and shared.

• Preservation and Integrity of Evidence (ABA Model Rules 3.4, 4.1, and related e‑discovery ethics)
  ABA ethics guidance and case law emphasize that lawyers must not unlawfully alter, destroy, or conceal evidence. That means clients should be instructed not to edit, trim, or “clean up” recordings, and that any forensic work should follow accepted chain‑of‑custody protocols.

• Candor and Avoiding Cherry‑Picking (ABA Model Rule 3.3, 4.1)
  Rule 3.3 requires candor toward the tribunal, and Rule 4.1 prohibits knowingly making false statements of fact. Lawyers should present digital evidence in context, avoiding selective clips that distort timing, perspective, or sound. A holistic, transparent approach builds credibility and protects both the client and the profession.

• Respect for Privacy and Non‑Clients (ABA Model Rule 4.4 and related guidance)
  Rule 4.4 governs respect for the rights of third parties, including their privacy interests. When you obtain bystander footage or data from non‑clients, you should consider minimizing unnecessary exposure of their identities and, where feasible, seek consent or redact sensitive information.

FINAL THOUGHTS

Handled with these rules in mind, everyday tech can reduce factual ambiguity and support more just outcomes. Misused, it can undermine trust, compromise admissibility, and trigger disciplinary scrutiny. ⚖️

Word of the Week: What is a “Token” in AI parlance?

Lawyers need to know what “tokens” are in ai jargon!

In artificial intelligence, a “token” is a small segment of text—such as a word, subword, or even punctuation—that AI tools like ChatGPT or other large language models (LLMs) use to understand and generate language. In simple terms, tokens are the “building blocks” of communication for AI. When you type a sentence, the system breaks it into tokens so it can analyze meaning, predict context, and produce a relevant response.

For example, the sentence “The court issued its opinion.” might be split into six tokens: “The,” “court,” “issued,” “its,” “opinion,” and “.” By interpreting how those tokens relate, the AI produces natural and coherent language that feels human-like.

This concept matters to law firms and practitioners because AI systems often measure capacity and billing by token count, not by word count. AI-powered tools used for document review, legal research, and e-discovery commonly calculate both usage and cost based on the number of tokens processed. Naturally, longer or more complex documents consume more tokens and therefore cost more to analyze. As a result, a lawyer’s AI platform may also be limited in how much discovery material it can process at once, depending on the platform’s token capacity.

lawyers have an ethical duty to know how tokens apply when using ai in their legal work!~

But there’s a second, more important dimension to tokens: ethics and professional responsibility. The ABA Model Rules of Professional Conduct—particularly Rules 1.1 (Competence), 1.6 (Confidentiality of Information), and 5.3 (Responsibilities Regarding Nonlawyer Assistance)—apply directly when lawyers use AI tools that process client data.

• Rule 1.1 requires technological competence. Attorneys must understand how their chosen AI tools function, at least enough to evaluate token-based costs, data use, and limitations.

• Rule 1.6 restricts how client confidential information may be shared or stored. Submitting text to an AI system means tokens representing that text may travel through third-party servers or APIs. Lawyers must confirm the AI tool’s data handling complies with client confidentiality obligations.

• Rule 5.3 extends similar oversight duties when relying on vendors that provide AI-based services. Understanding what happens to client data at the token level helps attorneys fulfill those responsibilities.

a “token” is a small segment of text.

In short, tokens are not just technical units. They represent the very language of client matters, billing data, and confidential work. Understanding tokens helps lawyers ensure efficient billing, maintain confidentiality, and stay compliant with professional ethics rules while embracing modern legal technology.

Tokens may be tiny units of text—but for lawyers, they’re big steps toward ethical, informed, and confident use of AI in practice. ⚖️💡

🚨🎙️📘 Three Days Left: The Lawyer’s Guide to Podcasting releases NEXT WEEK! 🥳🥳🥳

View fullsize

Inside title page of The Lawyer’s Guide to Podcasting, releasing January 19, 2026.

“The Lawyer’s Guide to Podcasting” will be released on Monday, January 19, 2026, through Amazon!!!

Designed for legal professionals, this book walks through every step of launching and sustaining an effective, ethically sound podcast that supports your practice and professional reputation.​

You will learn:

• Show formats

• Equipment needed

• Show hosting platforms to use

• Growing your audience

• Maintaining Professional Ethics

• Maybe earn some $Money$ too!

Want the release link the moment it’s live?
Email Admin@TheTechSavvyLawyer.Page with subject “Book Link.” I’ll send it on launch day. 🚀

Word of the Week: "Constitutional AI" for Lawyers - What It Is, Why It Matters for ABA Rules, and How Solo & Small Firms Should Use It!

Constitutional AI’s ‘helpful, harmless, honest’ standard is a solid starting point for lawyers evaluating AI platforms.

The term “Constitutional AI” appeared this week in a Tech Savvy Lawyer post about the MTC/PornHub breach as a cybersecurity wake‑up call for lawyers 🚨. That article used it to highlight how AI systems (like those law firms now rely on) must be built and governed by clear, ethical rules — much like a constitution — to protect client data and uphold professional duties. This week’s Word of the Week unpacks what Constitutional AI really means and explains why it matters deeply for solo, small, and mid‑size law firms.

🔍 What is Constitutional AI?

Constitutional AI is a method for training large language models so they follow a written set of high‑level principles, called a “constitution” 📜. Those principles are designed to make the AI helpful, honest, and harmless in its responses.

As Claude AI from Anthropic explains:
“Constitutional AI refers to a set of techniques developed by researchers at Anthropic to align AI systems like myself with human values and make us helpful, harmless, and honest. The key ideas behind Constitutional AI are aligning an AI’s behavior with a ‘constitution’ defined by human principles, using techniques like self‑supervision and adversarial training, developing constrained optimization techniques, and designing training data and model architecture to encode beneficial behaviors.” — Claude AI, Anthropic (July 7th, 2023).

In practice, Constitutional AI uses the model itself to critique and revise its own outputs against that constitution. For example, the model might be told: “Do not generate illegal, dangerous, or unethical content,” “Be honest about what you don’t know,” and “Protect user privacy.” It then evaluates its own answers against those rules before giving a final response.

Think of it like a junior associate who’s been given a firm’s internal ethics manual and told: “Before you send that memo, check it against these rules.” Constitutional AI does that same kind of self‑checking, but at machine speed.

🤝 How Constitutional AI Relates to Lawyers

For lawyers, Constitutional AI is important because it directly shapes how AI tools behave when handling legal work 📚. Many legal AI tools are built on models that use Constitutional AI techniques, so understanding this concept helps lawyers:

• Judge whether an AI assistant is likely to hallucinate, leak sensitive info, or give ethically problematic advice.

• Choose tools whose underlying AI is designed to be more transparent, less biased, and more aligned with professional norms.

• Better supervise AI use in the firm, which is a core ethical duty under the ABA Model Rules.

Solo and small firms, in particular, often rely on off‑the‑shelf AI tools (like chatbots or document assistants). Knowing that a tool is built on Constitutional AI principles can give more confidence that it’s designed to avoid harmful outputs and respect confidentiality.

⚖️ Why It Matters for ABA Model Rules

For solo and small firms, asking whether an AI platform aligns with Constitutional AI’s standards is a practical first step in choosing a trustworthy tool.

The ABA’s Formal Opinion 512 on generative AI makes clear that lawyers remain responsible for all work done with AI, even if an AI tool helped draft it 📝. Constitutional AI is relevant here because it’s one way that AI developers try to build in ethical guardrails that align with lawyers' obligations.

Key connections to the Model Rules:

• Rule 1.1 (Competence): Lawyers must understand the benefits and risks of the technology they use. Knowing that a tool uses Constitutional AI helps assess whether it’s reasonably reliable for tasks like research, drafting, or summarizing.

• Rule 1.6 (Confidentiality): Constitutional AI models are designed to refuse to disclose sensitive information and to avoid memorizing or leaking private data. This supports the lawyer’s duty to make “reasonable efforts” to protect client confidences.

• Rule 5.1 / 5.3 (Supervision): Managing partners and supervising attorneys must ensure that AI tools used by staff are consistent with ethical rules. A tool built on Constitutional AI principles is more likely to support, rather than undermine, those supervisory duties.

• Rule 3.3 (Candor to the Tribunal): Constitutional AI models are trained to admit uncertainty and avoid fabricating facts or cases, which helps reduce the risk of submitting false or misleading information to a court.

In short, Constitutional AI doesn’t relieve lawyers of their ethical duties, but it can make AI tools safer and more trustworthy when used under proper supervision.

🛡️ The “Helpful, Harmless, and Honest” Principle

The three pillars of Constitutional AI — helpful, harmless, and honest — are especially relevant for lawyers:

• Helpful: The AI should provide useful, relevant information that advances the client’s matter, without unnecessary or irrelevant content.

• Harmless: The AI should avoid generating illegal, dangerous, or unethical content, and should respect privacy and confidentiality.

• Honest: The AI should admit when it doesn’t know something, avoid fabricating facts or cases, and not misrepresent its capabilities.

For law firms, this “helpful, harmless, and honest” standard is a useful mental checklist when using AI:

• Is this AI output actually helpful to the client’s case?

• Could this output harm the client (e.g., by leaking confidential info or suggesting an unethical strategy)?

• Is the AI being honest (e.g., not hallucinating case law or pretending to know facts it can’t know)?

If the answer to any of those questions is “no,” the AI output should not be used without significant human review and correction.

🛠️ Practical Takeaways for Law Firms

For solo, small, and mid‑size firms, here’s how to put this into practice:

Lawyers need to screen AI tools and ensure they are aligned with ABA Model Rules.

1. Know your tools. When evaluating a legal AI product, ask whether it’s built on a Constitutional AI–style model (e.g., Claude). That tells you it’s designed with explicit ethical constraints.

2. Treat AI as a supervised assistant. Never let AI make final decisions or file work without a lawyer’s review. Constitutional AI reduces risk, but it doesn’t eliminate the need for human judgment.

3. Train your team. Make sure everyone in the firm understands that AI outputs must be checked for accuracy, confidentiality, and ethical compliance — especially when using third‑party tools.

4. Update your engagement letters and policies. Disclose to clients when AI is used in their matters, and explain how the firm supervises it. This supports transparency under Rule 1.4 and Rule 1.6.

5. Focus on “helpful, honest, harmless.” Use Constitutional AI as a mental checklist: Is this AI being helpful to the client? Is it honest about its limits? Is it harmless (no bias, no privacy leaks)? If not, don’t rely on it.

🎙️📘 Quick reminder: The Lawyer’s Guide to Podcasting releases NEXT WEEK!

View fullsize

Inside title page of The Lawyer’s Guide to Podcasting, releasing January 19, 2026.

If you want a podcast that sounds professional without turning your week into a production project, this book is built for you. It’s practical. It’s workflow-first. It keeps ethics and confidentiality in view. 🔐⚖️

✅ Inside you’ll learn:

• How to choose a podcast format that fits your goals 🎯

• A simple, reliable setup that sounds credible 🎤

• Recording habits that reduce editing time ⏱️

• Repurposing steps so one episode powers your content plan ♻️

📩 Want the release link the moment it’s live? Email Admin@TheTechSavvyLawyer.Page with subject “Book Link.” I’ll send it on launch day. 🚀

📖 WORD OF THE WEEK YEAR🥳: Verification: The 2025 Word of the Year for Legal Technology ⚖️💻

all lawyers need to remember to check ai-generated legal citations

After reviewing a year's worth of content from The Tech-Savvy Lawyer.Page blog and podcast, one word emerged to me as the defining concept for 2025: Verification. This term captures the essential duty that separates competent legal practice from dangerous shortcuts in the age of artificial intelligence.

Throughout 2025, The Tech-Savvy Lawyer consistently emphasized verification across multiple contexts. The blog covered proper redaction techniques following the Jeffrey Epstein files disaster. The podcast explored hidden AI in everyday legal tools. Every discussion returned to one central theme: lawyers must verify everything. 🔍

Verification means more than just checking your work. The concept encompasses multiple layers of professional responsibility. Attorneys must verify AI-generated legal research to prevent hallucinations. Courts have sanctioned lawyers who submitted fictitious case citations created by generative AI tools. One study found error rates of 33% in Westlaw AI and 17% in Lexis+ AI. Note the study's foundation is from May 2024, but a 2025 update confirms these findings remain current—the risk of not checking has not gone away. "Verification" cannot be ignored.

The duty extends beyond research. Lawyers must verify that redactions actually remove confidential information rather than simply hiding it under black boxes. The DOJ's failed redaction of the Epstein files demonstrated what happens when attorneys skip proper verification steps. Tech-savvy readers simply copied text from beneath the visual overlays. ⚠️

use of ai-generated legal work requires “verification”, “Verification”, “Verification”!

ABA Model Rule 1.1 requires technological competence. Comment 8 specifically mandates that lawyers understand "the benefits and risks associated with relevant technology." Verification sits at the heart of this competence requirement. Attorneys cannot claim ignorance about AI features embedded in Microsoft 365, Zoom, Adobe, or legal research platforms. Each tool processes client data differently. Each requires verification of settings, outputs, and data handling practices. 🛡️

The verification duty also applies to cybersecurity. Zero Trust Architecture operates on the principle "never trust, always verify." This security model requires continuous verification of user identity, device health, and access context. Law firms can no longer trust that users inside their network perimeter are authorized. Remote work and cloud-based systems demand constant verification.

Hidden AI poses another verification challenge. Software updates automatically activate AI features in familiar tools. These invisible assistants process confidential client data by default. Lawyers must verify which AI systems operate in their technology stack. They must verify data retention policies. They must verify that AI processing does not waive attorney-client privilege. 🤖

ABA Formal Opinion 512 eliminates the "I didn't know" defense. Lawyers bear responsibility for understanding how their tools use AI. Rule 5.3 requires attorneys to supervise software with the same care they supervise human staff members. Verification transforms from a good practice into an ethical mandate.

verify your ai-generated work like your bar license depends on it!

The year 2025 taught legal professionals that technology competence means verification competence. Attorneys must verify redactions work properly. They must verify AI outputs for accuracy. They must verify security settings protect confidential information. They must verify that hidden AI complies with ethical obligations. ✅

Verification protects clients, preserves attorney licenses, and maintains the integrity of legal practice. As The Tech-Savvy Lawyer demonstrated throughout 2025, every technological advancement creates new verification responsibilities. Attorneys who master verification will thrive in the AI era. Those who skip verification steps risk sanctions, malpractice claims, and disciplinary action.

The legal profession's 2025 Word of the Year is verification. Master it or risk everything. 💼⚖️

ANNOUNCEMENT (BOOK RELEASE): The Lawyer’s Guide to Podcasting: The Simple, Ethics-Aware Playbook to Launch a Professional Podcast (Release mid-January, 2026)

Anticipated release is mid-january 2026.

🎙️📘 Podcasting is still one of the fastest ways to build trust. It works for lawyers, legal professionals, and any expert who needs to explain complex topics in plain language.

On January 19, 2026, I’m releasing The Lawyer’s Guide to Podcasting. This book is designed for busy professionals who want a podcast that sounds credible, protects confidentiality, and fits into a real workflow. No studio required. No tech overwhelm.

✅ Inside the book, you’ll learn:

• How to pick a podcast format that matches your goals 🎯

• The “minimum viable setup” that sounds professional 🎤

• Recording workflows that reduce editing time ⏱️

• Practical ethics and risk habits for public content 🔐

• Repurposing steps so one episode becomes a week of marketing ♻️

📩 Get the release link: Email Admin@TheTechSavvyLawyer.Page with the subject line “Podcasting Book Link” and I’ll send the link as soon as the book is released. 📩🎙️

How To: Redact PDF Documents Properly and Recover Data from Failed Redactions: A Guide for Lawyers After the DOJ Epstein Files Release “Leak”

Lawyers must redact documents correctly!

The legal world is buzzing this week. The Department of Justice released the Jeffrey Epstein files on December 23, 2025. The New York Times reported on the disaster in their article, https://www.nytimes.com/2025/12/23/us/politics/epstein-files-redactions-doj.html. The DOJ attempted to hide names. They failed. They used improper redaction techniques. Tech-savvy readers simply copied the text from under the black boxes. They pasted it into Word. The names appeared instantly.

This is a nightmare for any attorney. You never want to be the "sender" in this scenario. You also need to know what to do if you are the "receiver." This “How to” guide explains the technology. It also covers the ethics. We will keep it simple.

The Mistake: Why "Black Boxes" Are Not Redactions

Digital documents have layers. Think of a PDF like a sandwich. The text is the meat in the middle. The white background is the bread. When you use a drawing tool to place a black rectangle over a name, you are just adding a topping. You are putting a slice of cheese on top of the meat.

The meat is still there.

The computer still sees the text. It just displays a black shape over it. This is what happened with the DOJ files. They likely used a "highlighter" tool set to black. Or they used a "shape" tool. This hides the visual text. It does not remove the data.

How to Properly Redact Documents

lawyers do you know how to redact documents properly?

You must remove the data. You cannot just hide it. You need to burn the “meat” in the sandwich (you are creating a “hole” in the document). Here is the process for Adobe Acrobat Pro. Most legal PDF software works similarly.

1. Use the Dedicated Redact Tool
Do not use the "Comment" tool. Do not use the "Draw" tool. Look for the tool named "Redact." It is usually in the "Protect" or "Tools" menu.

2. Mark for Redaction
Select the text you want to hide. The tool will outline it in red. This is a warning. It tells you, "I am about to delete this." It has not happened yet. You can still undo it.

3. Apply the Redaction
This is the critical step. You must click "Apply." The software will warn you. It will say this cannot be undone. Confirm it. The software now punches a hole in the digital paper. It fills that hole with black pixels. The text data is gone.

4. Sanitize and Remove Hidden Information
You are not done. Files have metadata. This includes author names. It includes edit history. It includes bookmarks. Acrobat will ask if you want to "Remove Hidden Information." Always say yes. This scrubs the invisible layers.

5. Save as a New File
Save the file with a new name. Use a suffix like "_REDACTED." Keep your original safe. Open the new file. Try to select the black box. Try to search for the hidden word. If you cannot find it, you are safe.

How to Recover Information from Improperly Redacted Files

Sometimes you receive a file. It looks redacted. You suspect it was done poorly. Here is how you can check.

Method 1: The Copy and Paste Trick
This is the easiest method. It works on the DOJ files.

• Open the PDF.

• Press Ctrl + A (Windows) or Cmd + A (Mac). (Or with your cursor, highlight the document area in question.) This selects all text.

• Look at the redacted area. If you see blue highlighting shadow behind the black box, the text is there.

• Press Ctrl + C (Copy).

• Open Microsoft Word.

• Press Ctrl + V (Paste).

• Read the text. The black box will likely disappear. The "hidden" words will appear.

Method 2: The Search Trick

• Open the PDF.

• Press Ctrl + F to open the search bar.

• Type a word you think is redacted.

• If the viewer jumps to a black box, the text is still there.

Method 3: Adobe "Remove Hidden Info" Check

• Open the file in Acrobat Pro.

• Go to the "Redact" tool.

• Look for "Sanitize Document" or "Remove Hidden Information."

• Run the scan.

• The report will list "Hidden Text" or "Overlapping Objects." This confirms data is hiding behind the visuals.

The Ethics: ABA Model Rules

Technology is easy. Ethics are hard. What happens when you send a bad file? What happens when you receive one?

For the Sender (The DOJ Scenario)
You have a duty of competence. ABA Model Rule 1.1 and 1.1 Comment 8 require you to understand your tools. You must know how to redact. Failing to use the software correctly is a competence failure.

You also have a duty of confidentiality. ABA Model Rule 1.6 requires you to protect client info. Sending a "masked" PDF instead of a "redacted" one violates this duty. It is a breach. You effectively handed the other side the keys to the safe.

For the Receiver (The Attorney Who Finds the Info)
You received the Epstein files. You copy-pasted. You found the names. Now what?

Lawyers, you have ethical obligations to redact documents competently.

ABA Model Rule 4.4(b) governs this. It addresses "Respect for Rights of Third Persons." It states: “A lawyer who receives a document... and knows or reasonably should know that the document was inadvertently sent shall promptly notify the sender.”

This is the key. Is a failed redaction "inadvertently sent"? Most ethics opinions say yes. The sender meant to hide it. They failed. They did not intend to send you the hidden text.

Do you have to stop reading?
The Model Rules do not explicitly say "stop reading." They only require you to notify the sender. However, many state jurisdictions go further. Some states require you to stop reading immediately. Some require you to delete the file.

The "Metadata" Exception
There is a nuance. ABA Formal Opinion 06-442 discusses metadata. It generally allows lawyers to look for hidden metadata. It views metadata as part of the file. However, "un-redacting" specific text is different. It is clearly privileged or sensitive.

The Bottom Line for the Receiver:

1. Stop if you realize it is a mistake.

2. Notify opposing counsel immediately. "I received your production. It appears the redactions are transparent. Please advise."

3. Do not use it until the issue is resolved. A judge will likely disqualify you if you exploit an obvious error.

Do not be the DOJ. Learn your tools. Sanitize your documents. And if you catch the other side making a mistake, follow the rules. It helps to keep your license safe. ⚖️ 💻

TSL Labs 🧪Bonus: 🎙️ From Cyber Compliance to Cyber Dominance: What VA's AI Revolution Means for Government Cybersecurity, Legal Ethics, and ABA Model Rule Compliance!

In this TSL Labs bonus episode, we examine this week’s editorial on how the Department of Veterans Affairs is leading a historic transformation from traditional compliance frameworks to a dynamic, AI-driven approach called "cyber dominance." This conversation unpacks what this seismic shift means for legal professionals across all practice areas—from procurement and contract law to privacy, FOIA, and litigation. Whether you're advising government agencies, representing contractors, or handling cases where data security matters, this discussion provides essential insights into how continuous monitoring, zero trust architecture, and AI-driven threat detection are redefining professional competence under ABA Model Rule 1.1. 💻⚖️🤖

Join our AI hosts and me as we discuss the following three questions and more!

1. How has federal cybersecurity evolved from the compliance era to the cyber dominance paradigm? 🔒

2. What are the three technical pillars—continuous monitoring, zero trust architecture, and AI-driven detection—and how do they interconnect? 🛡️

3. What professional liability and ethical obligations do lawyers now face under ABA Model Rule 1.1 regarding technology competence? ⚖️

In our conversation, we cover the following:

• [00:00:00] - Introduction: TSL Labs Bonus Podcast on VA's AI Revolution 🎯

• [00:01:00] - Introduction to Federal Cybersecurity: The End of the Compliance Era 📋

• [00:02:00] - Legal Implications and Professional Liability Under ABA Model Rules ⚖️

• [00:03:00] - From Compliance to Continuous Monitoring: Understanding the Static Security Model 🔄

• [00:04:00] - The False Comfort of Compliance-Only Approaches 🚨

• [00:05:00] - The Shift to Cyber Dominance: Three Integrated Technical Pillars 💪

• [00:06:00] - Zero Trust Architecture (ZTA) Explained: Verify Everything, Trust Nothing 🔐

• [00:07:00] - AI-Driven Detection and Legal Challenges: Professional Competence Under Model Rule 1.1 🤖

• [00:08:00] - The New Legal Questions: Real-Time Risk vs. Static Compliance 📊

• [00:09:00] - Evolving Compliance: From Paper Checks to Dynamic Evidence 📈

• [00:10:00] - Cybersecurity as Operational Discipline: DevSecOps and Security by Design 🔧

• [00:11:00] - Litigation Risks: Discovery, Red Teaming, and Continuous Monitoring Data ⚠️

• [00:12:00] - Cyber Governance with AI: Algorithmic Bias and Explainability 🧠

• [00:13:00] - Synthesis and Future Outlook: Law Must Lead, Not Chase Technology 🚀

• [00:14:00] - The Ultimate Question: Is Your Advice Ready for Real-Time Risk Management? 💡

• [00:15:00] - Conclusion and Resources 📚

Resources

Mentioned in the Episode

• ABA Model Rule 1.1 - Competent Representation (including technology competence requirement) - https://www.americanbar.org/groups/professional_responsibility/publications/model_rules_of_professional_conduct/rule_1_1_competence/

• Department of Veterans Affairs (VA) Cybersecurity Initiative - https://www.va.gov/oit/cybersecurity/

• DevSecOps Pipelines - Security integration in software development - https://www.devsecops.org/

• FedRAMP (Federal Risk and Authorization Management Program) - https://www.fedramp.gov/

• FISMA (Federal Information Security Management Act) - https://www.cisa.gov/topics/cyber-threats-and-advisories/federal-information-security-modernization-act

• Google Notebook AI - AI discussion generation tool - https://notebooklm.google.com/

• HIPAA (Health Insurance Portability and Accountability Act) - https://www.hhs.gov/hipaa/index.html

• NIST Cybersecurity Framework - https://www.nist.gov/cyberframework

• Red Teaming - Ethical hacking and security testing methodology - https://www.cisa.gov/red-team-assessments

• Zero Trust Architecture (ZTA) - Federal mandate for security verification - https://www.cisa.gov/zero-trust

Software & Cloud Services Mentioned in the Conversation

• AI-Driven Detection Systems - Automated threat detection and response platforms

• Automated Compliance Platforms - Dynamic evidence generation systems

• Continuous Monitoring Systems - Real-time security assessment platforms

• DevSecOps Tools - Automated security testing in software development pipelines

• Firewalls - Network security hardware devices

• Google Notebook AI - https://notebooklm.google.com/

• Penetration Testing Software - Security vulnerability assessment tools

• Zero Trust Architecture (ZTA) Solutions - Identity and access verification systems