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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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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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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