AI is fine. Your prompt is just bad.

AI is fine.

Your prompt is just bad.

Gemini 3 Pro just dropped. Best benchmarks ever. GPT-5.2 is out. Claude Opus 4.5 broke new records. Grok 4. DeepSeek V3.

Every week there's a new "best model" topping the leaderboards.

But here's what nobody talks about: most people still can't write a decent prompt.

It doesn't matter which model you pick.

Bad input equals bad output.

Every single time.

The real skill isn't choosing the right AI. It's knowing how to talk to it.

Think about it... Lovable, Cursor, v0, Claude Code, they're all just interfaces generating good prompts for you.

The magic isn't the model. It's what you feed it.

And prompting goes way deeper than "be specific."

There's structure: how you format inputs, mega prompts with detailed context, back-and-forth refinement to iterate on results.

Sometimes adding "research" or "think harder" to your prompt is enough.

There's architecture: RAG to pull relevant data, tool usage to extend capabilities, agent workflows to chain multiple steps.

There's system design: breaking complex problems into chunks the AI can actually handle, defining clear boundaries, managing context windows.

This is engineering, not typing.

The people getting real value from AI aren't model-hopping every release. They're building systems around prompts that work.

They're versioning their prompts.

Testing different approaches.

Treating prompt design like they treat code.

Most commercial models today will solve your problem.

The bottleneck is you.

Stop chasing the next model release.

Start learning how to use the one you have.

What's the prompting technique that changed things for you?