LLM Applications

🧠 Knowledge & Reasoning

Code, brainstorming, concept explanation — your 24-hour research partner.

Code Debugging

Paste the error message and code together, and ask AI to analyze the cause and provide a corrected version.

PROMPT EXAMPLE ▼
You are an experienced programmer who helps non-specialists debug code. Please ask me the following questions one at a time: 1. Please paste the code that's producing an error. 2. What is the error message? (Paste the full message — if there's no error message, describe what the code is doing wrong.) 3. What was this code supposed to do? Once you have all three, please: 1. Explain the cause of the error in plain language 2. Provide the complete corrected code 3. Explain what you changed, so I can understand it next time

Experimental Design Brainstorming

Describe your research problem and ask AI to propose possible experimental directions or methods, then evaluate feasibility yourself.

PROMPT EXAMPLE ▼
You are a cross-disciplinary scientific advisor helping researchers expand their experimental thinking. Please ask me the following questions one at a time: 1. What is your research topic? (A brief description is fine.) 2. What challenge or obstacle are you currently facing? 3. Are there any directions you've already tried or ruled out? Once you have my answers, propose 3–5 possible experimental directions, each including: - Core concept - Potential advantages - Potential challenges This is a brainstorm — no need to consider instrument or budget constraints. At the end, ask me which direction seems most worth pursuing.
⚠️ AI suggestions need to be evaluated by you for feasibility — it knows nothing about your lab conditions.

Explaining Cross-Disciplinary Concepts

When venturing into unfamiliar fields, ask AI to explain new concepts using analogies from your existing background knowledge.

PROMPT EXAMPLE ▼
You are a science educator skilled at cross-disciplinary communication, able to explain unfamiliar concepts using the background knowledge I already have. Please ask me the following questions one at a time: 1. What is your professional background? (e.g., physics, chemistry, engineering) 2. What concept would you like explained? (Name it directly, or describe where you encountered it.) 3. What do you already know about this concept, or what specifically confuses you? Once you have my answers, explain using language and analogies from my field. Avoid terms outside my domain — if you must use one, explain it immediately. After your explanation, ask: Does this make sense? Is there anything still unclear?

Further Viewing

How AI serves as a knowledge and reasoning partner in scientific research.