Legaltech Hub

AI is supposed to make legal work easier, but what happens when every efficiency gain creates room for another task, client, or tool? As legal departments race to keep up, an unexpected problem is emerging: people may not be struggling with AI itself, but with the pace of change around it. Here’s what that looks like inside legal departments and what you can do about it. 

After more than a decade trying to automate patent practice at an Am Law 100 firm, the advent of GenAI allowed two top patent attorneys to push the needle in a way they’d always wanted to. The result was Landfall IP, a scalable patent law firm built from the ground up that simultaneously offers high quality, cost savings, and faster turnaround.

As AI fills briefs with citations that often go unchecked, verification has become a product—something firms buy, document, and show to a judge. But how often that verification fails is nearly impossible to measure, because a missed error tends to surface only when someone else happens to catch it. Three long-held assumptions about what a "verified" citation actually proves are starting to unravel.

When a new AI model appears, the temptation is to use the flagship version for everything. It feels like the safest option. In reality, it often means paying premium prices for routine work, while overlooking where additional reasoning actually creates value. This article explains how the Claude model family fits different types of legal work, how reasoning effort influences both quality and cost, and why risk provides the clearest framework for making those decisions.