ChatGPT 변호사를 위한 프롬프트

Most effective legal prompts contain the same elements. A role tells the model the perspective to take, for example assisting a tenant-side lawyer. The context supplies facts and the jurisdiction. The task names one specific job. Constraints say what to avoid. The format specifies the structure of the output, such as a table, headed sections or a short letter. Vague prompts produce generic answers. Specific prompts produce drafts a lawyer can check. Issue spotting works best when the model is asked to organize analysis, not to reach conclusions. Asking for the elements of each possible claim, the facts that support or undercut each one, and the facts still needed turns the output into a checklist. Telling the model not to cite cases matters. General chatbots can invent authority, as the lawyers sanctioned in Mata v. Avianca (2023) learned. Legal authority should come from research databases and be read by the lawyer. Plain-language client letters benefit from a target reading level and a list of items that must not change: deadlines, amounts and obligations. Asking the model to list what it simplified exposes places where plain wording may have changed the legal meaning. Document summaries are more reliable when the model must quote key language with section or page references and write 'not found' instead of guessing. The lawyer can then check each point against the source in seconds. Confidentiality comes first. ABA Formal Opinion 512 says lawyers generally need informed consent before entering confidential information into tools that could expose it. Practical safeguards include removing names and identifying details, using business accounts whose terms exclude training on inputs, and checking data settings. A common misconception is that one clever prompt produces reliable legal work. Quality comes from context, a narrow task, and verification.