Enrico Schaefer shows how to build a GPT assistant for legal work like contract drafting and demand letters. The key: feed it detailed background material upfront, clear instructions, and specific goals. Treat it like a human assistant, not a magic box.
Chapters
Let's kind of dive in and take, take a look at some practical examples. I might build a GPT assistant for a client matter, such as contract drafting. And I'm now going to have to make some decisions about how to build this GPT assistant. And it's going to involve uploading the background information, the project and contract details. All the AI transcripts using Fireflies.ai that I use to record every call that I've had with that client about that project. Now I've got this structure for a GPT assistant that's got the right context, got the right background information in order to do the job. Other times I build a GPT for a specific task, such as drafting a mediation summary. Or responding to a particular set of discovery requests, or writing maybe a demand for arbitration or a settlement demand. And the magic happens when I take the time upfront to design each GPT assistant carefully. I don't just give it a vague prompt or instruction. I give it everything it needs to deliver A+ results. Think about this as the training and knowledge that you give a real-world Human assistant in order to do some specific job. If you hire an assistant off the street and you give them a task and you've provided them no context, no knowledge, no training, and no instruction, how well are they going to do? You need to provide the same level of clear, detailed instructions to your GPT that you hopefully would to a human assistant. who you've invested time and money in, in order to get the job done. You need to provide the relevant context and upload the right information. And you need to tell the GPT assistant where the end zone is. What is the goal of this GPT? And if you spend the time to do these things, this effort pays off every single time.
