What this prompt does
This prompt turns rough pseudocode into idiomatic, production-ready code in a target language. It casts the assistant as a senior [language] engineer and feeds it four context variables — [language], [conventions], [error_style], and the [pseudocode] to convert. The deliverables are deliberately tight: idiomatic code that follows your conventions, input validation only at real boundaries, error handling in your chosen style, tests for the happy path and every error path, sparse comments only where behavior is non-obvious, and a one-line note on any assumption made.
The structure works because it pins down the two things that usually go wrong when an AI converts pseudocode. First, it bans speculative abstraction — the prompt explicitly says "add no abstraction that the task does not require," which stops the model from wrapping a simple function in three layers nobody asked for. Second, the [error_style] variable (for example, "wrapped errors with %w, no panics in library code") forces a consistent, language-appropriate failure model instead of a grab-bag of try/catch and silent returns. Naming [conventions] keeps the output close to what a senior would actually merge.
When to use it
- Turning whiteboard sketches or design-doc pseudocode into shippable code
- Translating an algorithm from one language's idioms into another's
- When you want tests written alongside the implementation, not bolted on later
- When you've been burned by AI over-engineering simple functions
- When error handling needs to follow a specific house style
- When you want assumptions surfaced explicitly rather than buried in the code
Example output
You get a working code file (or set of functions) in [language], accompanied by a test suite that covers the happy path and each error path separately. Comments appear only where behavior isn't obvious, so the code reads cleanly instead of being buried in narration. At the end there's a short assumptions note flagging anything the model had to guess — input shapes, edge cases, or library choices — which doubles as a checklist of things to confirm before merging. The output is meant to be close to merge-ready, not a sketch, but you should still run the tests and verify they actually exercise the boundaries you care about.
Pro tips
- Make
[error_style]explicit and language-correct; "wrapped errors with %w" produces very different code than "exceptions with custom types" - Fill
[conventions]with your real house rules (context-first APIs, naming, formatting) so the output matches your codebase - Read the error-path tests first — they reveal whether the model actually understood the failure modes
- If you see an abstraction you didn't ask for, push back; the prompt forbids it but models still drift
- Keep
[pseudocode]focused on one unit of work; converting a whole module at once dilutes quality - Treat the assumptions note as a checklist of things to verify before merging
