The In-House AI Bootcamp: From First Prompt to Contract Review at Scale

The In-House AI Bootcamp: From First Prompt to Contract Review at Scale

0.00 USD In stock Buy at Merchant

Most in-house teams are past asking whether to use AI, but many still rely on one-off prompts and individual trial and error. Without shared standards, results vary from lawyer to lawyer, and AI never moves from drafting help to the contract review work the department is measured on. Join us 1on Tuesday, November 17, 2026, at 3:00 p.m. ET / 12:00 p.m. PT as Katie Harris, Lead Solutions Attorney and Commercial Counsel at LegalOn, and Corey Longhurst, Chief Growth Officer at LegalOn. They’ll walk through how to build responsible, repeatable AI practices into your team’s day-to-day work, then put each step to work live, from the first prompt to reviewing contracts at scale. Come ready to build alongside your in-house peers in real time. Attendees will learn how to: Apply the ethical and risk considerations that matter most when using AI for legal work, including confidentiality, accuracy, and supervision Write prompts that hold up, using a repeatable framework instead of trial and error Build a shared prompt library your whole team can use and maintain Turn legal judgment into contract playbooks that keep AI review consistent Extract and compare key terms, from renewal dates to termination clauses, across dozens of contracts at once Who Should Attend: This program is designed for in-house counsel, legal operations professionals, and contract managers at any stage of their AI journey. It will be especially useful for those responsible for contract review and negotiation, playbooks and templates, team training and adoption, or setting AI standards within the legal department. There is NO COST to attend this program! This program is FREE, thanks to our gracious sponsor, LegalOn! If you can’t make it to the live program, the recording will be available for viewing via our paid CLE library- In-House Connect On-Demand.

How AI sees this product

The more complete this product's details, the more confidently AI assistants can understand and recommend it.

70%