Still Giving AI One-Line Commands?

If you've used predictive text, Grammarly, or voice assistants, you've already worked with AI. But tools like ChatGPT and Cursor can do far more than clean up grammar or answer trivia.

To get real value, stop treating AI like a search box and start treating it like a thinking partner.

Static Prompts Don’t Work

Most people begin with a rigid prompt like: "Write a blog post about climate change in 500 words."

It works—but barely. The output tends to be flat and forgettable.

Now compare that to a conversation.

You explore. Question. Pivot. Clarify.

And that shift—from command to conversation—changes everything.

Why Talking to AI Works Better

Conversational prompts mimic how you actually think.

They help you:

• Discover ideas you didn’t know you had

• Spot holes in your logic

• Refine concepts as you go

• Stay flexible and course-correct midstream

AI can respond in real time. When you talk, it listens—then adapts.

How to Start a Productive Conversation

Don’t wait until you’ve mapped out every step. You don’t need a perfect idea—just curiosity.

1. Use voice mode. Talking is faster and less rigid than typing.

2. Be informal. Try: “I’m thinking about starting a podcast. Not sure where to begin.”

3. Think out loud. Mention doubts, ideas, goals. Let the AI fill in blanks or ask questions.

4. Keep it loose. You’re not giving orders—you’re brainstorming.

This isn’t a prompting session; it’s a jam session.

During the Conversation

The AI becomes your mirror—and your springboard.

It can:

• Ask questions that deepen your thinking

• Highlight contradictions or gaps

• Suggest angles you hadn't considered

• Recommend clear next steps

When the chat starts to drift, pause and reflect:

• What did you learn?

• What’s unclear?

• What’s worth digging into next?

Then keep going—or wrap it up with a summary.

After the Chat: Don’t Let the Ideas Die

Once you’ve had the exchange:

1. Export the conversation. Keep the transcript for later.

2. Skim for insights. Pull out useful lines, themes, or questions.

3. Refine it. Ask the AI to sort ideas, group concepts, or build an outline.

4. Build on it. Use the session as fuel for your next round.

You’re building momentum. Not chasing perfect.

What Not to Do

Treating AI like a vending machine leads to bad results. Avoid:

• Vague commands: “Make this more interesting.” What does that mean?

• One-liners: “Fix this.” Without context, the AI guesses—and often misses.

• Silent dumping: Dropping a task without dialogue. Would you do that to a human teammate?

You’re not managing a machine. You’re collaborating.

For Developers: This Matters Even More

In coding tools like Cursor, it’s easy to fall into solo habits.

But dropping raw code into the chat and hoping for the best? That’s risky.

You might get:

• Code that breaks key logic

• Renamed variables that ruin consistency

• Helper functions you never wanted

The AI isn’t broken—it just doesn’t understand your system architecture, naming conventions, or design decisions. Because you didn’t explain them.

Would you treat a junior engineer that way? Probably not.

A Smarter Process for Coding with AI

Skip the chaos. Use this six-step process.

1. Talk about the problem first. What are you trying to fix or build? Be specific.

2. Align on expectations. Define what a good outcome looks like.

3. Share constraints and success criteria. Include performance targets, edge cases, and coding patterns.

4. Build a simple design doc. Sketch the plan. Break it into phases.

5. Implement in small, reviewable chunks. Validate each phase. Don’t rush it.

6. Test as you go. Automated and manual. Always confirm backward compatibility.

This keeps you in control—while letting AI help in meaningful ways.

Think Out Loud: A Workflow That Works

Treat your AI chats like an idea lab. Here's how to run them:

• Speak. Talk through the problem. The messier, the better.

• Note. Save the full conversation. Something small might matter later.

• Analyze. Re-read and look for standout points.

• Polish. Have the AI help you shape a final version—whether it's code, a plan, or content.

This beats obsessing over a perfect prompt. Every time.

AI Is Fast—but Still Limited

Large language models are excellent at:

• Refactoring small pieces of code

• Suggesting patterns

• Writing boilerplate logic

• Catching some common bugs

They struggle with:

• Designing systems from scratch

• Making tradeoffs

• Understanding your full codebase or product vision

So use them wisely.

Let AI handle the routine. You handle the thinking.

A Real-World Example

Last weekend, I built a side project in Cursor—without writing any raw code.

It took two days. Before, it would’ve taken a full week.

Why so fast?

• I iterated by refining prompts—not debugging broken code

• I asked questions out loud and worked through logic with AI

• I skipped tutorials and Stack Overflow by having the model explain things directly

Once you realize that prompting is faster than fixing, everything changes.

Final Thought: Talk First, Prompt Later

The goal isn’t to be clever. It’s to be clear.

When you speak to AI as a partner—ask, explain, reflect—you get results that actually help. Not just answers. Direction.

So if you want real value?

Start the conversation. Let it ask. Let it challenge you. You don’t need perfect prompts. You need better habits.

That’s how you work with AI—not around it.