Would I be able to solve this problem with these files and this prompt?
Not enough context, the model may start to fill in the gaps with potentially irrelevant data that it was trained on.
Too much context, the model will need to "guess" which pieces are relevant.
Prompt
Too high-level, focus too much on what to do rather than on how to do it.
Too low-level, has too much detail and doesn't leverage the LLM:
Write a function that sorts a list of products.
Write a Python function that sorts a list of products, where each product is represented as a dictionary with at least the keys 'name' (a string), 'price' (a float), and 'rating' (a float from 1.0 to 5.0). The function should take two parameters: the list of products and a sorting key (either 'price' or 'rating'). The sorting should be in ascending order unless an optional boolean parameter descending is set…
Model
Speed vs Quality vs Cost (choose two)
Prompt with a Purpose
Every input token contributes to the final result
Use concise language to activate model "knowledge"
Understand how to leverage the models that you are working with.
Take the time to reflect on how to improve the original prompt instead of trying to "convince" the model to "change its mind".
What coding assistants do well
💻 Writing Code
Scaffolding, boilerplate, repetitive logic
Generating tests
📝 Documentation
Docstrings, inline comments, API references
🔍 Debugging & Optimization
Explaining errors & suggesting fixes
📊 Data Transformation & Scripting
Parsing and converting file formats
🧠 Learning & Research Assistance
Summarizing docs,
Explaining unfamiliar code
🦆 Code Review Assistance
What Developers Should Prioritize
🏗 Architecture Design
Decision-making, trade-offs, and scaling strategies
🧩 Critical Thinking
Debugging complex issues that require deep context
✅ High-Level Code Review
Ensuring correctness, business logic, security risks
