Aug 18 (edited) • General discussion
Prompt Engineering
Prompt engineering is the practice of designing, structuring, and refining prompts (the text or instructions you give to a large language model like GPT) to achieve the most accurate, useful, and reliable outputs.
Since LLMs don’t “know” your intent unless it’s clearly expressed, prompt engineering is essentially about:
Making instructions precise
Providing the right level of context
Structuring queries to reduce ambiguity
Iteratively testing and refining
Think of it as teaching the AI how to think in your direction by shaping the input.
Key Techniques
Instructional clarity – Be direct about what you want.
Role prompting – Ask the model to act in a specific role.
Context injection – Provide examples, rules, or background info.
Output formatting – Specify the format (table, JSON, bullet points, etc.).
Iterative refinement – Adjust based on the AI’s first response.
Examples
1. Simple vs. Engineered Prompt
Weak prompt: “Explain machine learning.”
Engineered prompt: “Explain machine learning in simple terms as if teaching a 10-year-old, using a real-life example and keeping the explanation under 150 words.”
The engineered one sets audience, style, and scope.
2. Role Prompting
Prompt: “You are a career coach. Give me 3 concise tips for preparing for a job interview in data engineering.”
This makes the AI tailor its response to a specific persona.
3. Few-shot Prompting (using examples)
Prompt:
Translate the following English phrases to French:
1. Good morning → Bonjour
2. Thank you → Merci
By giving examples, you “prime” the model to follow the same pattern.
4. Output Formatting
Prompt: “Summarize this research article into: (a) one-sentence summary, (b) bullet list of 3 key findings, and (c) one open research question.”
This avoids vague summaries and forces a structured output.
5. Chain-of-Thought / Step-by-Step Prompting
Prompt: “Solve this math problem step by step before giving the final answer: (9.6 – 10) / (1.2 / √30).”
This encourages the model to reason explicitly before answering.
Prompt to generate a picture
Example : A symbolic digital illustration showing two contrasting paths. On one side, a person is running toward a glowing “finish line” but looks tired, empty, and unfulfilled. On the other side, another person is walking step by step along a winding path, glowing with joy and focus on the present moment. The background shows time flowing (sunrise to sunset) to symbolize circumstances and life’s journey. Style: modern, minimal, inspirational — with vibrant contrasts of dull grays for the finish line side and warm glowing colors for the process side.
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Prompt Engineering
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