You don’t need a new prompt

Do not index

You don’t need:

Latest GPT update Latest Nvidia GPU Longest prompt

You just need more context and data.

That's the secret no one's talking about.

No amount of prompt engineering can give you better results than more context and more data.

Everyone's obsessed with "prompt engineering" these days:

Magic keywords to insert

Special formatting tricks

Secret commands and jailbreaks

But the real pros know something different. 👇🏻👇🏻

What Prompt Engineering really is

It's not complicated:

Definition: Getting the most out of an AI model through clear communication

Core skill: Explaining tasks clearly to something that knows a lot but lacks your specific context

Best approach: Explain the task as if to a competent newcomer who just joined your team

The biggest misconception - Most people overcomplicate it.

What Actually Works →

The techniques that deliver results are surprisingly simple:

Be specific about context

Provide explicit "clues"

Ask the model for help

Use examples strategically

Focus on task description, not fancy "tricks"

Here’s the best part:

"The hardest thing to do is untangle in your own brain all the stuff that you know that the LLM does not know and write it down."

This ability to identify and articulate your implicit knowledge is what separates average from excellent prompt engineers.

But Here's The Real Truth 💡

While everyone's fighting over prompt techniques, the real competitive edge is elsewhere:

First-party data + SOTA models = unbeatable results.

I won’t discuss this in too much detail because of obvious reasons 👀

This is exactly why:

Outrank delivers blog posts that actually grow traffic - we have data on what content actually ranks, not just what looks good.

SuperX generates posts that get engagement - We are using real-world performance data, not theoretical best practices.

And this is very important.

When everyone has access to the same AI models:

Prompt tricks give you a 10% edge

Unique data gives you a 10x edge

That's why we've built our products around proprietary datasets and training algorithms that no one else has.

The bottom line:

Stop obsessing over:

The latest GPT update

That new prompt technique

"Secret" AI hacks

Start obsessing over:

Collecting unique data

Building proprietary systems

That's the only sustainable advantage in an AI world.

Hit reply and let me know - are you using AI the right way?

Tweet of the week

Corporate bros will hate this. But this is surprisingly true.

Competence >> anything.

Until next time,

Keep building 💻

Tibo