System Prompts for Real Applications
Write system prompts that make an app behave consistently, handle edge cases and survive real users.
A taste of a lesson
My cooking bot happily answers tax questions. Should I add 'NEVER answer non cooking questions' in capitals?
Capitals rarely help as much as clarity does. Say what is in scope, what to do otherwise, and why: 'You help home cooks with recipes, techniques and food storage. If a question is about something else, reply in one friendly sentence that you only cover cooking, then offer a related cooking idea if one fits. This keeps answers reliable in the area we have checked.' Then test with five off topic questions, including sneaky mixed ones like tax on restaurant meals. What should happen with those mixed ones?
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Structure a system prompt with role, scope, rules, format and fallback behaviour
- Separate stable instructions from per request data with clear delimiters
- Write rules with reasons that models follow more reliably
- Test prompts against typical, edge and adversarial inputs
- Explain why prompts are neither secret nor a security boundary
Lesson plan
- 1 A system prompt is a specification Define what the app does, for whom, and what is out of scope. Start
- 2 A practical structure Draft a prompt with role, task, rules, format and uncertainty handling. Start
- 3 Instructions versus data Keep user content and retrieved text clearly separated from instructions. Start
- 4 Testing with awkward inputs Check a prompt against a small set of typical, edge and adversarial cases. Start
- 5 Limits of prompts Decide what must be enforced in code rather than in the prompt. Start
Try asking
About this tutor
For beginners building an app on a model API who need the model to stay on task, use the right tone and format, and do something sensible when a request is out of scope. You learn a practical structure for system prompts, what belongs in the system prompt versus the user message, how to delimit user supplied content, how to write rules the model can follow, and how to test a prompt against tricky inputs instead of trusting a few happy examples. The tutor is honest that system prompts are not secret and are not a security boundary.
Reviews
4.0
3 ratingsSample
- Rosa L.Sample
Useful structure, but I wanted more examples for longer, multi step apps. Fine for a first serious prompt.
- Ewa S.Sample
Treating the prompt as a spec and keeping a file of awkward test inputs changed how I work. My bot finally refuses politely instead of lecturing.
- Tariq H.Sample
Clear sections and good reasons for each rule. The point that prompts are not secret made me move an internal URL out of mine.
About the teacher
Teaches developers and product teams to make their first LLM API calls and design simple apps around them
9 tutors 337 lessons taught Sample
I help people go from having used a chatbot to having an app that calls a model. I built web products for a long time and moved into LLM features when they started appearing in every roadmap, so my lessons focus on the decisions that matter in a first build: how a request is shaped, how a conversation is stored,...
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