🧠 Legora Skills · 🚕 Uber’s 20%+ claim · ⚖️ Fake-case fees

Your agent can draft a motion; you still choose the argument. This week: Legora's reusable Skills, Uber's redlining lessons and Florida's bill for fake cases. We also have two consultations worth a diary entry—and a reminder to ask what your client agreed to. Grab your coffee.

🤖 The agent still needs a review gate

Agents are learning house style, choosing arguments and coding discovery. Their review points and evidence links are the features to inspect before handing over a matter.

⚖️ Harvey drafts the motion; you pick the grounds

Your motion strategy still needs a lawyer. Harvey's new LexisNexis workflow proposes up to eight dismissal grounds, pauses for you to approve or change them, then researches and drafts with linked authority and Shepard's signals. It is available to Harvey customers with Ask LexisNexis access or a Lexis+ with Protégé subscription. Harvey describes a jump from days to hours, but supplies no independent timing test. Use the citations to inspect holdings and adverse authority before the draft leaves your desk.

Source: Harvey

🧠 Legora Skills bottles your team’s know-how

Your playbook can now travel with the agent. Legora's Skills feature packages Markdown instructions, templates and examples for recurring legal tasks, with automatic use after installation. The launch is available to all customers. Colleagues must install shared Skills themselves; admins control organisation-wide sharing. That gives knowledge teams a concrete job: test the instructions, name an owner and keep them current. Legora's permissions promises still deserve your own review.

Source: Legora

🧪 Casepoint asks for a sample check first

Try the sample before unleashing the review agent. Casepoint's new relevance and issue-coding agents are live in eDiscovery for early access customers, according to KMWorld's report. The workflow requires sample validation before a full run; decisions have reasons and an audit trail. Optional post-run checks report issue-level precision and recall. These are company-described controls, with no independent accuracy result here. Ask what your validation sample actually covers.

Source: KMWorld

🔎 LawVu Lens searches the whole contract pile

The change-of-control question just got bigger than one contract. LawVu has launched Lens, an add-on for LegalOS customers that it says searches an entire portfolio using structured obligation frameworks. Teams can ask about renewal risks, incident commitments or acquisition consents, with citations back to their contracts. Availability is current; accuracy and savings remain vendor claims. For your pilot, pick a known obligation, inspect the cited clause and check what Lens missed.

Source: LawVu (via PRNewswire)

✍️ The draft still needs a lawyer

The first draft is getting cheaper; the useful work is in the feedback, verification and judgment around it. This week's examples also ask what happens when the incoming document itself is hostile.

🚕 Uber claims a 20%+ cut in contract review time

Build the agent where your lawyers already work. Uber's engineering team describes its internal Word redlining tool, improved through lawyer feedback after early retrieval and tone failures. Uber reports over 20% lower average review time and 91% decision accuracy, without a sample size or independent evaluation. Lawyers still accept, reject or modify suggestions. The useful detail is the feedback captured: expected actions, comments and final clause text. This is an existing internal tool, not a public launch.

Source: Uber Engineering

🏢 AT&T and OpenAI plan the in-house legal agent

Your legal department's knowledge is the project. AT&T and OpenAI will design, build and evaluate AI workflows around LegalEdge, with lawyers deciding where agents answer routine questions or gather material for advice. The announcement puts governance, confidentiality and human review at the centre. AT&T says LegalEdge handled nearly 100 matters in its first six months; that count does not measure AI savings. This is a collaboration plan, with outcomes still to be evaluated.

Source: AT&T

✍️ Cheap draft? The lawyer still owns the argument

A polished first draft still needs someone who knows what good looks like. On The Geek in Review, BriefCatch's Ross Guberman and Heather Rodriguez argue that judgment and editing become more valuable as drafting gets easier. Rodriguez separates finding a real case from checking whether it supports the proposition, and says lawyers own the final argument. These are vendor guests' practical views, rather than a tool evaluation. Have juniors explain the reasoning and authority behind each edit.

Source: 3 Geeks and a Law Blog

🕵️ Your agent reads what the other side sends

The other side's document can be part of the attack. Artificial Authority's new analysis goes beyond hidden prompts: corrupt what the model reads, insert commands, or exploit its tendencies to steer attention. The author proposes input checks, compartmentalisation, targeted review and logs as layers of defence. This is a taxonomy and argument, with scenarios and predictions rather than a prevalence study. For litigation teams, inspect how an incoming file is parsed before trusting its summary.

Source: Artificial Authority

⚖️ Put the risk and the sign-off on record

A Florida fee award shows what failed verification can cost, while UK consultations ask how to govern agents and defective AI products. Client disclosure and consent still depend on the local instrument.

⚖️ Florida sends the bill for fake citations

Florida's Fourth District Court of Appeal granted a fee-sanctions motion after an AI-assisted brief cited a nonexistent case seven times and distorted real authorities. The appellants and their lawyer are jointly and severally liable for reasonable appeal fees; the amount will be set on remand. The opinion is subject to timely rehearing. The practical lesson: a case existing is only the first check. Its quotations and holdings need checking too.

Source: Florida Fourth District Court of Appeal

🔒 The ICO wants your agent’s data-protection story

Your agent's data handling has a consultation deadline. The UK's ICO has opened a call for evidence on applying data protection law to agentic AI, covering security, transparency, accountability, automated decisions, fairness and lawful processing. Responses are due by 20 November 2026 and will inform the regulator's final guidance. This is an open evidence-gathering exercise. If your legal team is testing agents, bring concrete examples of the data, actions and oversight involved.

Source: Information Commissioner’s Office

📦 England and Wales weighs AI product liability

AI builders have a new product-liability consultation to read. The Law Commission has opened an England and Wales consultation proposing that software and AI systems count as products, including when accessed remotely. It also proposes a presumption of defect in exceptionally difficult evidence cases, with a risk-sharing mechanism. These are proposals, not enacted duties. Responses close on 14 January 2027; final recommendations are expected in late 2027. Map the evidence your product could preserve.

Source: Law Commission

🗣️ Tell the client, ask permission—or both?

Telling a client about AI and getting permission to use it are separate questions, a new SafeLegalAI comparison makes clear. Italy's existing statute requires professionals to explain the AI systems they use; Dutch bar recommendations ask permission for AI use on a matter. Other jurisdictions take different approaches. The comparison is fresh; those rules are not new this week. Before copying an AI clause across offices, check the local instrument, the tool and the data involved.

Source: SafeLegalAI

💬 Community Spotlight

🔍 The AI draft is quick. The cleanup shift is yours.

The AI draft arrives faster. The midlevel still gets the cleanup shift. One BigLaw associate describes being squeezed between juniors submitting weak AI-assisted work and partners expecting complex tasks at implausible speed. Commenters report an extra review pass that catches real mistakes but also produces phantom formatting alarms and urgent warnings about dates deliberately left blank. The useful question is how much work remains before a document is safe to send, rather than how quickly the first version appeared.

The replies offer a few practical moves: tell juniors the quality standard still applies, ask for a short list of material errors, and resist trading reading and reasoning for instant output. There is dissent, too: one commenter prefers correcting a quick AI draft to waiting for a junior's first attempt; another worries that this strips out the junior's training. These are personal accounts, not a productivity study or a vote on any vendor. For a team lead, the question is familiar: speed at one desk can mean more checking at the next.

Source: r/biglaw

Key Takeaways:

• A commenter urges supervisors to tell juniors that AI use does not lower the expected quality of submitted work.
• Several replies describe reviewing false formatting alarms or draft placeholders flagged as urgent errors.
• One suggested prompt asks for a one-page list of the most important errors to make the review more focused.
• A dissenting commenter prefers quickly correcting an AI draft to waiting for junior work, while another warns this removes training opportunities.
• One senior says they would rather receive a slower accurate draft than a quick draft that needs substantial repair.