32dots HEIDELBERG AI

Prompt Engineering

Get dramatically better answers from any AI

A beginner-to-advanced ladder of prompting techniques, each taught through a weak → strong prompt pair: be specific, give context, assign roles, show examples, structure with tags, think step by step, and ground answers in your sources. 18+ copy-ready examples.

After this chapter you can
Turn a vague request into a specific, well-scoped prompt
Use roles, examples, and delimiters to control the output
Apply chain-of-thought and prompt chaining to multi-step tasks
Ground answers in your sources to avoid made-up facts
Beginner Say what you actually want
Be specific Vague prompts get vague answers. Name the exact output you want.
Summarize this paper.
Summarize this paper in 5 bullet points for a first-year student: the research question, the method in one line, the key finding (with the number), the main limitation, and why it matters.
Make this email better.
Rewrite this email to my supervisor to be more concise and polite. Keep it under 80 words, keep the meeting request, and remove the apologetic tone.
Why it works: Naming the length, audience, and the exact things to include leaves nothing for the model to guess wrong.
Give context & audience Tell the model who it is helping and what for — the same question gets a different, better answer.
Is this result significant?
I'm a biology master's student. I ran a t-test and got p=0.04 with n=12. Explain whether this is statistically significant, what the small sample size means for how much I should trust it, and what I should check before reporting it.
Why it works: Context (who you are, the real numbers, your actual worry) lets the model pitch the depth correctly and answer the question behind the question.
Specify format & length If you need a table, a list, or a fixed length — ask for it explicitly.
Compare these three sequencing methods.
Compare Illumina, Nanopore, and PacBio sequencing as a markdown table with columns: method | read length | accuracy | cost | best use case. One short phrase per cell.
Explain CRISPR.
Explain CRISPR gene editing in exactly 3 short paragraphs: (1) what it is, (2) how the cut-and-repair works, (3) one real research use. Avoid jargon a high-schooler would not know.
Why it works: A requested structure gives you a scannable, consistent answer instead of a wall of text you have to re-read.