When and How Should Developers Use AI — Plan First or Start Generating Code?
Last week, a developer on our team opened an AI tool before writing a single line of code.
The task?
Change a button label.
A few minutes later, the AI had suggested architecture improvements, refactoring strategies, testing layers, and performance considerations… for a one-line change.
We laughed.
But it revealed something important:
Using AI isn’t the challenge anymore.
Knowing when and how to use it is.
The Real Decision: Generate Code or Think First?
Today, developers face a new daily choice:
Should I ask AI to generate code right away…
or should I use AI to help me plan first?
Starting with code feels fast. It gives you that dopamine hit of "done." But without clarity, rapid generation often leads to rework, hidden bugs, and "spaghetti code" that just happens to be syntax-perfect.
Great developers use AI differently.
They decide whether the problem needs thinking or typing.
A memorable rule of thumb my friend Neem shared—one worth keeping on your desk:
“Use AI like a whiteboard before you use it like a keyboard.”When to Use AI for Planning (Before Any Code)
Use AI as a thinking partner when the work is bigger than a quick fix:
Building a new feature or workflow
Designing database schemas or APIs
Working on authentication, payments, or security
Coordinating across multiple developers
Solving a problem that isn’t fully clear yet
Here, AI should help you:
Break down the problem
Explore multiple approaches
Identify risks and edge cases
Define a clean implementation path
In this mode, your goal isn't output; it's clarity. You want the AI to break down the problem, identify edge cases, and challenge your assumptions.
✨ What “Planning With AI” Actually Looks Like
Most developers default to "Make this." Try pivoting to "Help me design this."
❌ The "Lazy" Prompt (Do not do this for complex tasks):
Prompt: "Write a PHP script to scrape data from X website and save it to a database."
Result: You get code that works once but fails on edge cases, with no error handling or rate limiting.
✅ The "Architect" Prompt (try this instead):
Prompt:I need to build a scraper for X website. Before generating any code, act as a Senior Engineer and help me plan.
- List the potential risks (legal, rate limiting, data structure changes).
Suggest 2 different architectural approaches with trade-offs.
Ask me 3 clarifying questions to narrow down the scope.
and Do not generate code yet.
Result: You get a roadmap, risk mitigation, and a solid plan. You are now the pilot, not the passenger.
10–15 minutes of AI-assisted planning can save days of cleanup later.
When It’s Fine to Let AI Generate Code Immediately
Sometimes speed matters more than planning.
You can safely jump into AI code generation when:
The task is small and obvious
It’s a simple bug fix, rename, or UI tweak
No database, API, or architecture change is involved
You already understand the exact solution
In these moments, planning with AI adds friction instead of value.
Just generate, review, and ship.
How Good Developers Actually Use AI
The strongest engineers don’t use AI blindly.
They follow a simple flow:
Understand the problem first
Decide: planning help or code generation?
Use AI intentionally for that step
Review, test, and fully understand the output
AI works best as:
A planner for complex thinking
A generator for simple execution
Not the other way around.
A Simple Rule of Thumb
Small task (< 1 hour) → generate code.
Complex task (days of work) → plan with AI first.
This one habit prevents over-engineering on small work
and chaos on big work.
Final Thought
AI won’t replace developers.
But developers who learn when to think, when to plan, and when to generate code with AI
will move faster, build cleaner systems, and make better decisions.
And in the AI era,
judgment — not just coding speed — is the real superpower.
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