My Journey as an AI Orchestrator

Two years ago, I was a out-of-practice engineer.

After years in product, sales, marketing and program management, I returned to engineering.

I was mocked. Irrelevant by "colleagues". 

But I've delivered productivity tools for the business seamlessly embedded into Teams or Google Workspace. It boosted productivity in core business workflows by 10x for use cases suc has legal content analysis and creation, marketing dashboards or E-Commerce system audits.

And when the AI got stuck, I forced it back on track with experience—by directing it to implement a different logic or by writing pseudo-code myself, which it then translated into executable code.

And I’m not alone.

Take this entrepreneur: https://twitter.com/leojr94_; He hit $200 MRR with AI direction, outpacing overfunded startups despite challenges.

I’ve seen it firsthand for the past two years:

1. AI flattens execution.

2. Anyone can churn something out.

3. The market doesn’t care about “AI users.”

This is why the **World Economic Forum in Future of Jobs Report 2023** predicts Manual labor and routine skills are projected to **drop to just 24%** of core job activities by 2030.

That includes:

- Checklist-based roles

- Passive execution mindsets

- prompt-droppers who don’t think.

The passive users will at risk:

- They drop sloppy prompts and call it “work”

- Swallow weak outputs without blinking

- Outsource their brains, hoping AI will think for them

But Top contributors will be AI orchestrators:

- They articulate their request with pinpoint focus

- Slice complex problems into tangible wins. 

- Shred and remix AI outputs for exceeding expectations

AI orchestrator role requires learning but is accessible with effort.

That’s why you must pilot one AI task today and deliver, or get left behind.