Not to be THAT dictionary, but…
It’s ‘per se,’ not ‘per say.’
It’s ‘dog-eat-dog world,’ not ‘doggy-dog world.’
It’s ‘hunger pangs,’ not ‘hunger pains.’
It’s ‘one and the same,’ not ‘one in the same.’
It's 'buck naked,' not 'butt naked.'
Millennials are the elite generation because they cranked out 12-page essays the night before they were due. No ChatGPT. No Claude. Just lo-fi beats playing in the background, Black coffee at midnight, footnotes that were somehow correct, and pure delusion. Grade was an A minus. Period.
No cure for endometriosis. No proper management for menopause. No adequate symptomatic relief for menstrual discomfort. But let’s get handicapped sperm a wheelchair to make not so healthy babies because it would make men feel strong.
This is wild.
143 million people thought they were catching Pokémon. They were actually building one of the largest real-world visual datasets in AI history.
Niantic just disclosed that photos and AR scans collected through Pokémon Go have produced a dataset of over 30 billion real-world images. The company is now using that data to power visual navigation AI for delivery robots.
Players didn't just walk around with their phones. They scanned landmarks, storefronts, parks, and sidewalks from every angle, at every time of day, in lighting and weather conditions that staged photography would never capture. They documented the physical world at a scale no mapping company with a fleet of vehicles could have replicated on the same timeline or budget.
Niantic collected this systematically, data point by data point, across eight years, while users thought the only thing at stake was catching a rare Charizard.
The most valuable AI training datasets in the world aren't being assembled in data centers. They're being built by people who have no idea they're building them.
Boss complained that the company couldn't afford to give salary raises.
So they resorted to hiring and firing aggressively to cut costs.
This only made the matter worse.
He sought advise
"What's the average raise request you've denied?" I asked.
Boss : "About 15-20%."
"And what are you paying new hires?"
Boss : "Market rate. Usually 30% more than internal folks."
"So you won't pay someone 15% more to stay,
but you'll pay someone else 30% more to start?"
He shifted. "That's different."
"What about Sarah?" I asked.
Boss : "She asked for 18K more.
We said no. She left.
You just hired her replacement."
Boss : "Yeah. Took three months to fill."
"What did you pay the replacement?"
Boss : "85K."
Sarah was making 62K. Asked for 80K.
"Right."
"So you saved 18K by saying no,
then spent 23K more to get someone new.
Plus signing bonus?"
"10K."
"What about lost productivity while they ramp up?"
"Maybe six months to get to Sarah's level."
"That's another 30K in lost output.
Plus recruiting costs?"
He opened a spreadsheet.
"Recruiter was 17K. Training about 15K."
I wrote on his whiteboard:
- Salary increase: 33K
- Signing bonus: 10K
- Lost productivity: 30K
- Recruiter fee: 17K
- Training costs: 15K
Total: 105K
"You spent 105K to avoid paying 18K."
He stared at the board.
"How many Sarahs did you lose this year?"
"Twelve."
"So you burned 1.2 million
to save maybe 200K in raises."
A few months later, he called.
"I just approved every raise request in the queue."
"All of them?"
"Cost me 340K.
Would have cost me 2 million in replacements."
"How'd your team react?"
"Shocked. Then productive.
We're hitting numbers we haven't seen in years."
Here's the truth about retention economics:
Companies will spend a dollar to save a dime.
Then spend ten dollars to fix what broke.
We treat current employees like costs
and new employees like investments.
But retention isn't an expense.
It's the highest ROI investment you'll ever make.