AI doesn't have to be a second full-time job
You don't have to burn your free time just to get better at it
Your employer is telling you to become AI-native. Every post online is warning you to use AI now, or you get left behind.
But when you try out the latest model or the latest tool, you get frustrated.
Everyone makes it seem so easy. Just give Claude these prompts and you’ll become a 10x employee.
But how do you actually do that?
In the end, you burn all your time trying to figure out a tool that you won’t use in 2 months.
And you’re back to square one.
But this was never the way to learn AI.
Everyone wants to sell you on their latest feature
You’re constantly faced with over-sensationalised news whenever it comes to AI, because they generate the most clicks.
“Claude is replacing a new industry today, ChatGPT is killing all designers”.
The same, boring news that makes you feel completely inadequate about yourself if you continue consuming it day in, day out.
They do this to force you into chasing the latest feature or tool because they proclaim how amazing it is.
But sooner or later, you burn out if you’re constantly stuck in this hamster wheel of trying everything new.
You think that the only way to get ahead is to be up-to-date, but no one cares whether you used Opus 4.7 or an old model to produce an output.
The output has to be meaningful enough to justify the amount of time and money you’re spending on it.
And if you’re building something flashy just to impress others, it’ll never work out in the long run.
AI is just an excellent execution machine
So instead, view AI as a tool to either help you (or your company) make more or save more money.
That’s all it is, really.
And it usually comes in the form of saving time. Saving precious time that you were spending doing the same old repetitive tasks that you hate doing.
Saving precious time that you could better use for higher-leverage tasks that AI can’t fully help you with.
AI is excellent at following orders (like I was in my previous company), and it needs someone to direct it.
If you give it bad or vague instructions, it won’t give you the output that you want or need.
But if you give it a clear workflow and the bottleneck it needs to solve, it becomes a world-class intern.
So it was never about the tools, models, or features.
All AI needs from you are these 3 things:
The OWB of your problem
To be successful at AI, you need to explain these clearly to AI:
Outcome: What do you want to achieve?
Workflow: What are the steps required to achieve that outcome?
Bottleneck: What bottlenecks are you facing in the workflow?
Give these clearly to AI in as much detail as you can, and you’ll be amazed at how much better the outputs are.
AI just needs the direction, or the ‘what’ from you.
Not everything can be outsourced to AI, and I’d prioritise giving them mindless tasks that you hate doing.
Because if your workflows are not clear and specific enough, you will spend more time troubleshooting them instead of getting anything usable.
Get better outputs with AI
Being AI-native was never about the number of tools you know, or the tokens you burn.
It’s all about giving clear instructions to AI so it can execute a task just as you would do it yourself.
And the only 2 things you should be focusing on are:
Gathering your context: Giving AI detailed information about who you are, what you do, and how you think
Building Effective Skills: Repeatable workflows that you can give AI so it executes the task based on your instructions
And after spending the past 4 months learning how to get good at AI, I built out a system that only concentrates on these, so you don’t waste your time on any other distractions.
This is what I’ll be sharing more of in The AI-Native Sprint, a 90-minute crash course that helps busy 9-to-5 professionals master AI.
If you’d like to join us, sign up for the waitlist here: