eDiscovery Document Review - Chain of Thought
Using chain of thought reasoning to improve the richness and quality of the output
Welcome to the AI Case Studies section, where the rubber meets the road. Here, we dive into real-world examples of AI-powered legal work, showcasing not just the impressive final outputs, but also the iterative process that got us there.
In each case study, you’ll see:
But these case studies are more than just static examples - they’re your backstage pass to the messy, often magical process of co-creating with AI. You’ll get to see the back-and-forth, the refining of prompts, the gradual shaping of raw AI-generated text into polished, powerful final products.
Why show our work? Because we believe that the real power of AI lies not in any single output, but in the human-machine interplay that produces it. By peeling back the curtain on that process, we aim to demystify AI and empower you to harness it in your own legal practice.
So dive in, get inspired, and start envisioning how AI could turbocharged your own work. And if you’re eager to learn more about prompt engineering and iterative collaboration with AI, be sure to check out our [Tutorials & How-Tos] section.
The future of legal work is here - and it’s a glorious, messy, thrilling fusion of human ingenuity and artificial intelligence. Let’s explore it together.
Using chain of thought reasoning to improve the richness and quality of the output
Writing a memo with AI