Getting an AI to write code is easy, but getting it to write bulletproof code is a different beast entirely.
I recently found a clever technique that solves the “happy path” problem where AI ignores edge cases. The original poster, u/Glass-War-2768, shared a method on Reddit that forces the model to act as a critic before it acts as a creator. This approach, dubbed “Defensive Prompting,” ensures your code is robust from the very first draft.
Here is the exact prompt provided by the author:
Here is my project spec. Before writing code, list 3 scenarios where this logic would crash. Then, write the code with those 3 safeguards built-in.
Why this works
This prompt leverages a specific type of Chain of Thought reasoning. By asking the AI to “break the spec” first, you force it to shift context from generation to analysis.
- Context Switching: It moves the AI from a helpful assistant trying to please you (which often leads to oversimplified code) to a critical engineer looking for flaws.
- Pre-computation: It identifies the necessary error-handling logic before it starts writing the syntax, ensuring those safeguards are integrated naturally rather than tacked on later.
Variations to try
You can adapt the author’s logic for different domains:
- Security Audit: “Before coding, list 3 potential security vulnerabilities (like SQL injection) in this logic, then write the code to prevent them.”
- Performance Check: “Identify where this script might hit memory limits with large datasets, then write the optimized version.”
Best Use Cases
- API Integrations: Handling 404s, timeouts, or malformed JSON responses.
- User Input: Catching unexpected characters or empty fields.
- Data Pipelines: Managing corrupt files or missing headers during import.
This is a smart way to reduce debugging time. Check out the full discussion on Reddit to see how others are using it.
Frequently Asked Questions
Q: How does the "Failure First" method change the AI’s approach?
It basically forces the model to switch hats and think like a QA engineer before it becomes a developer. Instead of jumping straight into coding, the AI actively hunts for edge cases and crash scenarios, ensuring the logic is battle-tested from the start.
Q: Will this really help reduce bugs in my projects?
Absolutely! This approach is great for stopping those annoying bugs that usually only show up during the testing phase. By identifying potential failure points upfront, the AI builds safeguards directly into the code, saving you time on debugging later.
Q: Why is this considered better than standard prompting?
Many users find this to be a total game changer because it prioritizes defensive coding over speed. Standard prompts often miss "break the spec" scenarios, but this method ensures the AI considers how the logic might fail before it even writes a single line.
The ‘Failure First’ Method for coding agents.
by u/Glass-War-2768 in PromptEngineering