Learning Machines
Lawyers are learning to work with artificial intelligence. Artificial intelligence is learning to work with law. This blog explores how — through pedagogy, practice, policy, and the ethical questions that connect them.
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When the Client Brings the AI
The NYC Bar’s Formal Opinion 2025-6 addresses what happens when clients use their own AI tools to record and transcribe conversations with their lawyers. Read alongside Heppner, the opinion establishes one clear duty (warning clients of AI-related privilege risks) and suggests two further responses (providing privilege-preserving alternatives and redesigning communication channels) that the rules do not yet require but that the foreseeability shift Heppner introduces makes worth taking seriously.
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Colorado Wrote an Exemption for a Tool That No Longer Exists
Colorado's SB 26-189 exempts AI tools used solely to 'summarize, organize, translate, draft, route, or present information for human review.' That exemption was drafted for a model of AI use—ask a question, get an answer, review the answer—that the legal technology market has already moved past. The tools law firms are buying don't summarize information for lawyers. They make the analytical choices that determine what gets summarized, in what order, and with what emphasis.
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The Tool Was Never the Hard Part
A former Latham associate reproduced the core features of Harvey and Legora in two weeks and released the code for free. The commentary has focused on what that means for pricing and capability. But Mike is a ceiling story, and the profession's AI problem is at the floor.
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The Agent Is Not Exercising Judgment
Legal technology vendors are marketing AI 'agents' that plan, reason, and execute multi-step workflows. These tools can handle information-gathering tasks well, including within legal practice itself. But the line between collecting material for a lawyer's evaluation and substituting for that evaluation is the line between appropriate delegation and a supervisory problem under Rule 5.1 — and the vendors' incentives push firms to cross it.
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The Disclosure Patchwork
Illinois says courts should not require lawyers to disclose AI use. Florida circuits mandate it on the face of every filing. Hundreds of federal judges have issued individual standing orders, no two identical. The profession has spent three years arguing about whether disclosure is necessary without asking what disclosure is for — and the answer has less to do with catching errors than with enabling the people who review AI-assisted work to do their jobs.
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The Verification Problem Is Getting Worse
U.S. courts imposed at least $145,000 in sanctions for AI-generated citation errors during Q1 2026 alone, across cases in New York, Kansas, the Sixth Circuit, and Oregon. The sanctioned lawyers share a striking common feature: none of them had functioning AI verification practices in place. That finding complicates the profession's preferred response to AI risk, but not in the way you might expect.
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Every Course Needs Learning Outcomes by August
The ABA's revised accreditation standards require law schools to establish measurable learning outcomes for every course, align them to programmatic outcomes, and build formative assessments into the first year — all by the 2026-2027 academic year. Most schools are not staffed for this work. An LLM can help with the drafting. It cannot help with the judgment calls that make the drafting worthwhile.
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Colorado Wants to Regulate Your AI — and You Are the Deployer
Colorado's AI Act takes effect on June 30, and its deployer obligations apply to anyone who uses AI as a substantial factor in consequential decisions — including law firms. 'Legal services' is one of the statute's eight enumerated categories. Most of the legal profession has not grappled with the fact that it is on the regulated side of this law.
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The Errors Are More Interesting Than the Apology
Sullivan & Cromwell’s AI-contaminated bankruptcy filing has drawn coverage for the firm’s apology. The three-page errata is more revealing: errors that suggest AI corrupted correct citations during editing, a compliance program that failed despite being rigorous, and a supervision obligation the firm’s letter concedes without naming.
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The Trained Volunteer Lost. The Chatbot Should Worry.
A federal court dismissed Upsolve's challenge to New York's unauthorized-practice-of-law rules, holding that trained non-lawyers cannot give individualized legal advice — even for free, even with safeguards, even with disclaimers. The opinion never mentions AI. But it describes AI legal tools more precisely than any opinion that has.
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New York Wants to Ban Your Chatbot From Answering Questions
New York Senate Bill S7263 would impose civil liability on chatbot proprietors whose systems provide 'substantive' responses in areas reserved for licensed professionals — and declares that disclosing the chatbot's non-human status is not a defense. The bill's impulse is understandable, but its mechanism confuses information with advice and would suppress exactly the kind of public legal education that existing law permits.
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Building Infrastructure with AI: A Case Study
A law professor with no engineering background used Claude, Cowork, ChatGPT, and Gemini to design and deploy a self-hosted news aggregation pipeline over a weekend. The project worked — not because AI eliminated the need for technical skill, but because the skills it required turned out to be the ones lawyers already have.
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The Model Will Not Push Back
Hallucination gets the headlines, but sycophancy may be the more dangerous failure mode for lawyers. An LLM that systematically validates your reasoning instead of challenging it functions as a mirror, not a counsel. And mirrors make poor advisors.
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Delegate the Task, Not the Judgment
LLMs are good at generating options, structuring information, and doing legwork. They are not good at deciding what matters. The most common mistake lawyers make with AI is not using it on the wrong task — it is asking it to exercise judgment they should be exercising themselves.
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What Your AI Forgets Mid-Sentence — And What to Do About It
LLMs degrade predictably as their context windows fill — losing track of middle-document content, dropping earlier conversation history, and producing confident output built on incomplete inputs. For lawyers using these tools on long documents, the question is not whether it happens but how to structure your work to prevent it.
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You Probably Have a Duty to Warn Your Clients About ChatGPT
Heppner established that consumer AI conversations are not privileged. But the case also raises an uncomfortable question for practicing lawyers: if a known hazard to the privilege now exists, do you have a duty to warn your clients about it? The answer, under existing ethics rules, is almost certainly yes.
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The API Is Not a Compliance Strategy
Using an LLM through an API rather than a consumer chatbot improves your data-handling posture — sometimes dramatically. But an API alone does not satisfy FERPA, HIPAA, or any other regulatory framework, and treating it as though it does mistakes a technical control for a legal one.
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Your AI Conversations Are Not Confidential — And a Federal Court Just Said So
A comparison of Anthropic's data-handling policies across Claude's consumer and commercial tiers — and why the distinction now carries real legal consequences after the SDNY's decision in United States v. Heppner.
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