10 Prompts I Actually Use (And Reuse)
After months of using GPT-5 for development, strategy, and reflection, I noticed that certain prompts keep coming back.
They aren’t theoretical — they’re from my real history, the ones that keep saving me time or giving me clarity.
1. “Drop-in replacement”
“Give me a drop-in replacement for this function/code block.”
Why: I don’t want half-baked snippets. I want something I can paste in and run. This prompt drives GPT to give me complete, production-ready code.
2. “Map this to X”
“Convert this PHP associative array to a JS map.”
Why: Constant cross-language work means I need quick translations, not explanations. Asking for “map” or “object” by name sets the shape I want.
3. “Simplify this pattern”
“Bring this back a bit, simplify the syntax, cut errors.”
Why: When code or diagrams get bloated, I use GPT as a refactoring lens — not to add more, but to compress.
4. “Sequence diagram in MD”
“Give me a sequence diagram in markdown for this flow.”
Why: I think visually. Turning messy flows into a diagram I can drop into docs keeps me and others aligned fast.
5. “Service design level”
“Let’s talk at the service design level before I code this.”
Why: Pausing to model the why/what before the how saves me from tangling myself later. GPT’s structured reasoning helps me zoom out.
6. “Useful defaults”
“Give me a seed MDX with this title, summary, tags.”
Why: I don’t want to reinvent metadata or headers. One line gets me a publishable doc skeleton.
7. “Rewrite in my voice”
“Make this sound like me — direct, not corporate.”
Why: GPT helps me tune tone for clients or teammates. It’s faster to have it rewrite than to self-edit.
8. “What should I focus on next?”
“From this codebase/context, what’s the critical path for the MVP?”
Why: Context-switching is hard. This prompt gives me a focus check when I feel scatterbrained.
9. “Turn into steps and states”
“Convert this flow into states, staged state, and applied state logic.”
Why: My apps often juggle staged vs applied filters. GPT helps me model state machines cleanly before I write them.
10. “Explain why this isn’t working”
“Here’s the API response vs my request. Why is it failing?”
Why: Debugging with GPT is like having a senior dev next to me — it spots mismatches faster than scrolling logs myself.
Reflection
Looking back, the best prompts are not clever phrasing tricks. They’re consistent scaffolds I use to:
- Get runnable output fast.
- Reframe messy work into cleaner forms.
- Push myself to think in systems, not just lines of code.
The magic isn’t in novelty; it’s in repetition.
These prompts became habits.