The ethical guide to surviving AI layoffs
You don't need to sell hype to keep your job
What would you do to stop AI from replacing you, even if it were unethical?
Mo Bitar’s hilarious video painted the current state of AI hype in both tech and AI Twitter/YouTube, where the only way to keep your job was to sell hype to your employer.
Make it known that you’re the expert in AI and find ways to replace others before they replace you, so that your trigger-happy employer doesn’t add you to the layoff list.
You have to sell that you’re all in on AI, even when you’re a skeptic of it, just to be in the good books of your employer.
You have to constantly stuff AI buzzwords down people’s throats that you don’t even know how they work, just to stay relevant.
But, what if there’s another way to use AI in your job that keeps you safe without becoming another obnoxious co-worker?
You don’t need to know everything about AI
Being AI-native was never about using every single feature that launches every day.
The engagement farmers will constantly tell you that you’ll be left behind if you don’t try them, but it’s just a major distraction.
Most of the models and new tools that are hyped online won’t be relevant in the next few months.
I’ve never tried a Ralph loop before, and I don’t intend to, until I’m sure that I can give clear instructions to the AI to achieve the outcome I want.
Falling into the AI Tool Trap puts you into another hamster wheel that you can’t escape:
A new feature gets released
Everyone hypes it up on Twitter and YouTube
You fall for the hype and try using it
You spend more time troubleshooting than doing anything meaningful
You get frustrated and revert to your old workflows
Which is ultimately just a huge waste of time.
So ignore all the buzzwords that everyone is throwing around.
Harness, context engineering, model quantisation, none of that matters to you now.
Instead, just focus on this:
Build practical workflows with AI to automate the tasks you hate doing
While automation seems like a dream that everyone wants to achieve, we don’t want to give AI the wheel so it runs our lives entirely.
There are still things that we enjoy doing, and AI’s main aim is to automate the tasks that we absolutely hate.
The soul-sucking, draining, repetitive tasks that we do day in, day out, that are mindless, and we wish someone could do them for us.
Those are the tasks that we should be outsourcing to AI, while we have more cognitive load to focus on the tasks that we enjoy doing.
So instead of building a flashy tool with the sole purpose of impressing your employer (who couldn’t care less), build with AI to achieve these 2 outcomes:
You prove your value by making or saving more money
The more directly tied to revenue your job is, the more valuauble are to your employer.
If you can prove that whatever tool you build with AI makes or saves money for the business, you will be safe.
And it all starts with this:
Find one painful bottleneck that stops the company from making or saving more money in your workflow, and build a solution with AI to remove the bottleneck.
There’s no need for any hype when you have substance and real outcomes (instead of burning tokens and raising the expenditure of your company).
What if you could become AI-native in less time?
You can build practical workflows with AI, even if you have zero technical experience like me.
After spending the past 4 months with the sole purpose of getting good at AI, I have built a system that helps me automate all the tasks that I hate doing.
This is what I’ll be sharing more of in The AI-Native Sprint, a 90-minute crash course that gives you a clear path for busy 9-to-5 professionals to become AI-Native.
If you’d like to join us, sign up for the waitlist here: