Ask an AI to “find the tax regulations for China” and you get a tidy list with a short note on each rule. Ask it the same thing with your case, your goal and your unknowns attached, and you can get a starting point for the analysis itself. The model is the same in both cases. The prompt is what changed.
The key idea
A one-line request describes one action: find the regulations. It doesn’t say why you need them, what problem you’re solving or what the result is for. So the AI does the one thing you asked for, and you do the rest yourself.
That rest is the hard part. Which provisions apply to your situation? Are there cases or official interpretations? How do the rules, the facts and the examples fit together? If you’re still doing all of that by hand, you’ve only used the AI to find and organize information.
Anthropic’s prompting guidance makes a related point. Context, a defined outcome and clear instructions help the AI give a more targeted answer.
The contrast: old way vs new way
The old way: “Please help me find and organize the laws and regulations related to taxation in China.”
The answer focuses on what information exists. You get a list and some summaries, and the connecting work is left to you.
The new way: Explain the situation, how far the AI should go, and what you might be missing.
The answer focuses on how that information relates to your problem. The AI has a chance to link the regulations to your facts, flag conditions that affect applicability, and point to examples.
The question is still research in both cases. The second version tells the AI what the research is for.
The three parts to include
- 🧭 Context: why am I doing this? Describe the case, the business activities involved, the facts you already know and the ones that are still uncertain.
- 🎯 The task: how far do I need it to go? Finding the regulations may be the main job. You can also ask it to relate them to the case, look for relevant examples, note conditions that affect applicability, and organize everything for its intended use.
- 🔍 Extra perspectives: what might I have missed? Once the main task is done, ask for research directions you overlooked. If it sees a major problem with your approach, ask it to say so.
Practical steps: a template you can copy
Here is the research version, adapted from the Reddit post:
Context: I’m researching a case involving Chinese tax regulations. The background is [describe the business or case]. The known facts include [key facts]. I need to turn the research into [intended output, such as an internal analysis].
Main task: Please find current tax laws and regulations that may be relevant. Include official sources, identify the status of each regulation, and note the date of your search. If you cannot verify something, say so rather than guessing.
Additional tasks: This research is one part of a larger assignment. After the main task, please [further analysis, connections or synthesis].
Working principles: Complete the main task first, then point out research directions I may have missed. If essential information is missing, or you spot a major issue with my approach, flag it first.
And a version that works outside legal research:
Context: I’m working on [task]. The background is [relevant information]. My goal is [desired outcome], and the result will be used for [audience or purpose].
Main task: Please help me [the immediate task] and present the result as [desired format].
Additional tasks: Once the main task is complete, please also help me [further analysis, connections or synthesis].
Working principles: Complete the main task first, then point out angles I may have overlooked. If essential information is missing or you notice a major problem with my approach, flag it first.
A few notes on using it:
- Fill in the facts you’re unsure about too. Telling the AI what’s uncertain helps it avoid assuming.
- Name the end use (internal memo, client summary, decision brief). It shapes the format and the depth.
- Keep the “say so rather than guessing” line. It’s a cheap guard against confident nonsense.
The caveat
More context doesn’t make an answer automatically correct. Laws and cases still need checking against reliable sources, their current status, and the circumstances where they apply. The better prompt gets you a better starting point. It doesn’t replace the verification.
Try it
Take one question you’ve asked an AI recently that came back as a flat list. Rewrite it with the three parts above and run both versions side by side. Compare how much connecting work you still have to do.
The open question from the original poster is a good one: how do you give an AI enough context without making prompts needlessly long? One approach is to keep a reusable template like the one above and fill in only the parts that change. How do you handle it?
How do you get AI to do more than just find information?
by u/Dayspring0069 in PromptEngineering