This isn’t another “how to prompt AI” post.
This is about lesser-known habits that dramatically improve the quality of code you get from LLMs.
Tip 1 — Say you’re not satisfied (immediately)
If the generated code isn’t what you expected, say it clearly and early.
Why this works
LLMs adapt within the conversation.
When you signal dissatisfaction, you push the model to:
- Reconsider assumptions
- Apply stricter reasoning
- Explore alternative approaches
Very often, the second answer is far more thoughtful than the first.
Don’t accept “almost right” code. Push back.
Tip 2 — Ask twice (even when it’s good)
Even if the solution works, try this:
“Improve this code.”
You’ll be surprised how often AI will:
- Simplify logic
- Improve naming
- Enhance performance
- Reduce edge-case risk
Iterating with AI is like having a senior reviewer on demand.
Tip 3 — Give the big picture (real context matters)
AI performs dramatically better when it understands your architecture.
Instead of:
“Write a method that does X”
Try:
“This belongs to the service layer. We use a layered architecture:
Controller → Service → Repository. Where should this logic live?”
Now the AI can:
- Place responsibilities correctly
- Avoid leaking business logic into technical layers
- Produce code that fits your design
The real power move
Instead of describing the system manually, use an AI Prompt Builder that injects real project context.
For example, tools like CppDepend’s AI Prompt Builder — a feature that generates reliable, context-aware prompts using:
- Dependencies between components
- Layer violations
- Code metrics (complexity, size, coupling…)
- Type relationships & call graphs
That context can be added to the prompt so the AI doesn’t guess — it understands your system’s structure.
Now AI isn’t just generating code.
It becomes an architecture-aware assistant working with real project data.
Tip 4 — Step away and refactor yourself
After generating multiple AI-driven methods, pause.
AI optimizes locally, not globally. You still must:
- Reorganize classes
- Merge duplicated logic
- Extract shared abstractions
- Clean design inconsistencies
AI accelerates coding.
You are still the architect.
Tip 5 — Ask AI to criticize its own code
This is one of the most underrated tricks.
After the code is generated, ask:
- “What are the weaknesses of this code?”
- “Where could this fail in production?”
- “What edge cases are missing?”
Now the AI switches roles:
Creator → Reviewer
This often reveals:
- Hidden bugs
- Performance risks
- Missing validations
- Concurrency issues
- Security gaps
You essentially get a free design review.
Final Thought
AI doesn’t replace engineering judgment — it amplifies it.
The best workflow looks like this:
Generator → Improver → Critic → Assistant
…while you remain the architect.
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