Work Smarter, Not Harder: Top 5 AI Prompts Every Legal Professional in New York City Should Use in 2025

New York City lawyers need prompts, not miracles: carefully written AI prompts turn generic generative models into jurisdiction-aware drafting assistants that respect privilege, reduce repetitive work, and surface local case law fast - critical when New York accounts for roughly 187,656 attorneys and time is a billable currency.

Industry data shows growing individual use and clear productivity gains (54% use AI for correspondence; 65% of users save 1–5 hours weekly), yet accuracy, privacy, and firm governance remain top concerns (see the Legal Industry Report 2025).

Strategic prompting and prompt-testing are the fastest way to capture those gains while managing risk; Thomson Reuters projects AI can save roughly 240 hours per lawyer per year when used responsibly.

For practical training on prompt design and safe deployment, consider a focused course like AI Essentials for Work bootcamp (Nucamp) - learn prompt-writing, tool selection, and workplace safeguards.

“This isn't a topic for your partner retreat in six months. This transformation is happening now.”

Prompts were chosen and stress‑tested to mirror real New York practice: priority went to tasks that save time (contract drafting and review, summarization, legal research, and litigation‑strategy prompts) and to templates that explicitly name jurisdiction and date ranges - advice drawn from Spellbook's prompt playbook and research best practices (Spellbook guide to AI prompts for lawyers, Spellbook legal research tips for attorneys).

Each candidate prompt underwent iterative refinement on representative documents and research queries, with human reviewers verifying sources and cross‑referencing outputs against authoritative databases; the NDA risk‑spotting benchmark cited by Spellbook (94% AI accuracy vs.

85% for experienced lawyers) informed pass/fail thresholds for risk‑flagging prompts. Safety and governance checks included data‑handling notes, template libraries, and a final attorney sign‑off step so that every ready‑to‑copy prompt returns jurisdiction‑aware language, clear citations or source paths, and an explicit reminder that AI outputs require lawyer review - so teams in NYC can scale routine work without sacrificing control.

AI is an assistant, not a replacement for lawyers.

Spellbook prompt: ask for a New York‑governed NDA that names parties, defines “Confidential Information,” limits use to a stated Purpose, enumerates exclusions, and proposes both a reasonable fixed confidentiality period and trade‑secret survivorship language - for example, instruct the model: “Draft a New York NDA (one‑way or mutual) that (1) identifies Disclosing/Receiving Party, (2) provides a narrow but inclusive definition of Confidential Information, (3) lists standard exclusions, (4) sets duration options (1–5 years; perpetual only for trade secrets), (5) includes injunctive relief and governing‑law clause for New York courts, and (6) inserts the employee Notice of Immunity where applicable.” This reduces risky open‑ended language (New York courts resist open‑ended NDAs) and aligns with attorney‑crafted templates - see the attorney‑crafted New York NDA template (updated March 6, 2025) for clause language and downloads and consult state‑specific limits & S3457 status when choosing duration.

Use the prompt to output clear placeholders for facts, a citation note to the chosen template, and an explicit lawyer‑review reminder so the draft is instantly usable in NYC practice without assuming enforceability.

“Confidential Information” means any information that is proprietary or unique to the Company and that is disclosed by the Company to the Recipient during the term of this Agreement, including the following: trade secret information; matters of a technical nature such as processes, devices, techniques, data and formulas, research subjects and results; marketing methods; plans and strategies; information about operations, products, services, revenues, expenses, profits, sales, key personnel, customers, suppliers, and pricing policies; and any information concerning the marketing and other business affairs and methods of the Company which is not readily available to the public.

When using Casetext's CoCounsel for New York contract review, prompt it like a senior associate: name the jurisdiction and date range, upload the agreement, and ask for a prioritized list of “high‑risk” clauses with specific citations, a plain‑language summary for a client memo, and proposed redlines that include alternative New York‑law wording and a short rationale tied to case law or statutes; CoCounsel's training on GPT‑4 and Thomson Reuters content plus Westlaw/Practical Law integration means it can both surface relevant authorities and compare a document against checklists, flagging non‑standard indemnities, unusual forum‑selection language, and employee‑protection gaps so partners can triage review time (pilot results show review time reductions up to ~63%).

For safe use in NYC practice, include an explicit instruction to "do not assume enforceability - cite sources and list assumptions," and route all redlines for partner sign‑off; CoCounsel's enterprise controls (end‑to‑end encryption and zero‑retention options) help address confidentiality concerns while delivering research‑grade citations.

Learn more about CoCounsel features and upcoming agentic workflows at Thomson Reuters and in the product preview.

"OpenAI's GPT-4 passing the Uniform Bar Exam (top 10%) reinforces how incredible Casetext's CoCounsel – powered by GPT-4 – really is."

For New York client briefings, prompt ChatGPT (GPT‑4+/O1) to produce a jurisdiction‑tagged, plain‑language executive summary plus a contract‑at‑a‑glance table that lists parties, duties, fees, deadlines, rights, and key representations - explicitly name “New York, include governing‑law/date range,” and ask for sourceable citations and prioritized risk flags so partners get both a client‑ready memo and proposed NY‑law redlines for review; this approach mirrors the sample contract‑summary prompt in MyCase's attorney prompts and Volody's “plain language summary” template and keeps outputs usable in NYC practice when paired with the NYC Bar's confidentiality and disclosure guidance (scrub client identifiers and get consent before using open models) (see MyCase's prompt examples and Volody's ChatGPT prompts for lawyers).

The practical payoff: dense agreements become negotiation‑ready briefings that highlight what a client must act on now versus what can wait, speeding decisions without skipping lawyer verification.

“Please create a concise and well-organized summary of the key points and legal implications contained in [legal document, case, or article].”

Google's NotebookLM is a practical, jurisdiction-aware research assistant for NYC practitioners: create a notebook from up to 50 uploaded sources (PDFs, Google Docs, transcripts or pasted text), then ask it to synthesize case law, build timelines, generate FAQs, or even produce a two‑speaker podcast from those materials in minutes - ideal for turning dense New York court records or agency files into client‑ready briefings and team timelines.

Its retrieval‑style, source‑grounded workflow (a form of RAG) helps reduce hallucinations and surface verifiable citations, while conversational Q&A lets teams clarify ambiguous facts and iterate on scope.

Use NotebookLM for rapid case‑law synthesis and paralegal triage, but retain a human‑in‑the‑loop and follow firm privacy rules: data‑privacy and bias concerns persist, so scrub client identifiers and verify authorities before filing.

Read the NYLI NotebookLM FAQ for hands‑on tips and see the Future of Law podcast coverage for real‑world examples and workflow ideas.

For New York litigation teams, Claude (Anthropic) is best used as a “weakness finder” and strategy engine: upload long case files (Claude supports very large contexts - useful for an 85‑page brief or 200+ pages of medical records), then prompt it to produce a prioritized list of factual and legal vulnerabilities, short‑form cross‑examination scripts, targeted discovery requests, and jurisdiction‑aware redlines that cite supporting authority or list assumptions for partner review; apply structured prompt engineering (role/system prompts, explicit output format, example shots, and chain‑of‑thought steps) to improve reliability and traceability - see practical setup and use cases in the Rankings.io Claude guide and prompt‑engineering best practices at Walturn.

A single, well‑scoped prompt that names “New York” and the desired deliverables (e.g., “rank weaknesses by impact on liability and admissibility; provide citations or source paths; flag assumptions”) turns long, messy records into immediate tactical options while keeping a human in the loop and avoiding blind reliance on AI.

“You're not replacing attorneys - you're extending what they can do in half the time.”

Close this playbook with three concrete, low‑risk moves New York practitioners can do this week: (1) adopt an AI governance checklist and vendor review before scaling - see Practical Law's AI Governance Checklist for a jurisdiction‑aware template you can adapt; (2) implement the NYC Bar's ethics guardrails on confidentiality, verification, and client disclosure (summarized for practitioners at Clearbrief) and schedule the 30/60/90 governance milestones (convene a board in 30 days, adopt policy in 60, complete training in 90) to translate guidance into firm practice; and (3) deploy the ready‑to‑copy prompt bank in this article - spellbook NDA/employment drafting, a Casetext CoCounsel contract‑review prompt, a GPT‑4+ contract‑summarization prompt for client briefings, a NotebookLM notebook for New York case synthesis, and a Claude litigation weakness‑finder prompt - each with an explicit “lawyer review required” reminder and a scrubbed data policy.

For hands‑on prompt training and workplace AI safeguards, consider the AI Essentials for Work bootcamp (Nucamp) to build repeatable prompts, governance checklists, and human‑in‑the‑loop workflows that preserve client trust while cutting routine hours.

“You're not replacing attorneys - you're extending what they can do in half the time.”