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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How Lawyers Should Prompt in 2026
Anthropic, OpenAI, and Google all updated their prompt engineering guidance in late 2025 and early 2026, and a striking amount of the advice from 2023 and 2024 now degrades the newer models. This post lists the changes practicing lawyers should know about, with concrete prompt patterns drawn from the three vendors’ current documentation.
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Client-Side AI Recording and NYC Bar Formal Opinion 2025-6
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 firms should weigh in light of the foreseeability shift Heppner introduces.
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SB 26-189's Obsolete Exemption: Statutory Categories and Moving Technology
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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Open-Source Legal AI and the Institutional Floor
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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Agentic AI and the Boundaries of Professional 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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Citation Sanctions in Q1 2026: The Verification Problem, Quantified
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.
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Revised Standard 314: Learning-Outcomes Requirements and the August Deadline
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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Deployer Obligations Under the Colorado AI Act
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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Anatomy of an AI-Contaminated Filing: The Sullivan & Cromwell Errata
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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