r/AgentsOfAI

Everyone's reacting to the "less people in 5 years" line. That's not the part I'd sit with.

The part that actually matters is how Uber decides — an adoption leaderboard, tracking who's using the tools and how much, feeding straight into headcount math.

That's not a hypothetical for some future reorg.

That's a live measurement system, running today, on people who have no idea they're on it.

 

I've watched that exact math play out before — in concrete and steel, not a dashboard, years before anyone called it AI.

I had the opportunity to be involved in the early design stage of an expansion project for a famous beverage manufacturing plant in Taoyuan, Taiwan – back in 2021. The beverage brand name is so famous, you'll instantly recognize it. So, I won't name it here.

Our team got to work on cool stuff - latest advanced technologies in high-density and automated racking system, bottle conveyor system, robotics, beverage packers, clean room environment, etc. – things that are expected in a high-tech. manufacturing plant nowadays.

Looking at the projected 10-year production forecast, with the given magnitude of the hardware, I would say they are planning to go big.

It's quite a sizeable expansion.

And you would think that they'd increase their headcount proportionately, right?

You'd be surprised. There IS headcount increase, but not as proportional.

It seems as though the machines were taking more centre stage than the humans. Even the office space increase wasn't even a top priority in the design. Their existing office layout can still accommodate the projected increase in manpower.

It was as if human beings are being set aside to make room for more artificial things – even though what they produce are meant to serve human beings.

Kind of ironic, isn't it?

That was back in 2021 before AI come into the picture. Now the compression is even more acute, it seems.

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Different guest, same fork in the road: does the tool serve you, or does it just get pointed at you.

The industries change.

The question underneath never does — who's holding the ledger, and whether you're the one reading it or the one being read.

A 2026 WRITER survey backs the pattern from the outside too: 75% of execs privately admit their AI rollout is mostly for show, while the people actually inside the tooling get promoted 3x more often and ship 5x more.

That's the leaderboard, confirmed from a different angle.

 

Genuinely curious where you land: is a visible adoption leaderboard a fair way to measure a team, or is it just a slower-motion version of the same cut?

 

Clip credit: 20VC with Harry Stebbings & Uber. DM for credit or removal requests.

 

The leaderboard measures usage. It doesn't measure ownership — and the difference between those two is the actual thing I built the working system around.

David Gerard runs Pivot to AI oon a server that costs him €7 a month.

Right now, something wearing a fake Chrome mask is hammering it — hopping IP addresses so he can't even block it properly, ignoring robots.txt because robots.txt was never a wall, just a sign nobody was required to read.

He's not a company.

He's not a platform.

He's one guy, doing his own sysadmin work, at 11pm, because the industry ran out of the free internet and started eating the cheap end of it instead.

Not stolen. Just... takenn, quietly, at scale.

 

I've watched this exact shape happen before — just slower, and on paper instead of a server log.

Circa 2005, Malaysia. I was Assistant Technical Manager for one of the largest construction main contractors in the country. We were compiling tender documents for a factory job — flat-flooring work, strict F-numbers, the kind of spec that keeps a forklift's raised forks from clipping the racking on a narrow run.

A subcontractor walked in to drop off her quotation. She glanced at our papers, open on the table.

And she went pale. I heard the gasp.

"这是我写的，为什么会在这里？" — This is what I wrote. Why is it here?

Word for word hers. Now sitting under our company's logo and headings.

She looked at me. I looked at her. She was waiting for an answer I didn't have.

Then her eyes flickered — a thousand thoughts passing through in a second — and she said, "没关系。我可以再写过。" — Doesn't matter. I can write it again.

And she left. Good for her.

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Every one of these stories eventually lands on the same fact: the exposure runs downhill, from the platforms with lawyers down to the servers with none.

 

If you're running anything on a boxx that isn't Amazon or Google's, drop your own scraper-traffic story below. I want to see how far downhill this actually goes.

 

Clip credit: David Gerard — full video on The Tech Report's channel. DM for credit or removal requests.

 

Rohan's not the only one who found out the hard way that "small" doesn't mean "safe" — the actual mechanism for making that stop is one honest look away.

Executives don't lack tools.

They lack a ruler.

 

That's the actual claim Ed Zitron made — not "AI is bad," but that the people signing off on AI-assisted work were never equipped to check it in the first place.

They see a document that looks finished and call it done, because "finished-looking" is the only bar they've ever had to clear.

 

For anyone whose whole job is catching the thing that looks fine and isn't — this isn't a tech story.

It's a story about who gets trusted, and why it's rarely the person who's actually right.

 

I've been on the other side of that exact gap.

Long before spreadsheets and dashboards, mine had a tape measure in it.

 

I was working as a Site Engineer for a Singaporean construction company building a primary school in Chua Chu Kang district back in 1998. Time flies. Just graduated from university. Figure I get some site experience first.

One day, I came to the project site. And I saw the newly delivered precast half-flight staircase lying on the ground next the building. I asked around to find out why wasn't it crane-lifted to position, which is between 1st and 2nd floor. And I was told the measurements were off. They couldn't fit it nicely on place.

And so, I went to work. I took my measuring tape, measure the staircase, and recorded the lengths, widths and whatnot. Then I went up to the building's 2nd floor — where the staircase was supposed to fit and meet. And I swung my measuring tape across the length of space between the positions where the 1st and last step of the staircase supposed to sit on. And took the site measurements too.

Then I went back to my office, took out the construction drawings from the drawing rack, lay it on the meeting table. And with a piece of paper, I started drawing it out. I knew full well the measurements I got will not exactly match that in the drawings, because — you know — site tolerances are still allowed and anticipated in the BS Code of Practice.

And then, through calculations, I found it. The measurements were way out of tolerance limit. No wonder the staircase can't fit. The blame squarely landed on our RC works sub-contractor. They screw up the levelling of the building.

Each of us supposed to have an "internal ruler" we rely on, to judge whether things look good or bad. For me, back then, it was Pythagoras and a fresh sheet of paper. My boss, years later, called his the same thing in different words — his "feel," thirty years deep. Kevin O'Leary's is knowing he can smell bullshit from a mile away.

So, coming back to these leadership people that Ed Zitron was attacking: don't they have their "feel" of things before shit hits the fan? Don't they use their "internal ruler" to measure it for themselves? Can't they smell bullshit from a mile away?

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Every post on this account keeps circling back to the same thing, whichever industry the clip's from: the people getting quietly pushed out are rarely the ones who got it wrong.

 

Drop your take: what's your internal ruler, and who around you doesn't have one?

 

Clip credit: Ed Zitron (Better Offline) on Adam Taggart's Thoughtful Money. DM for credit or removal requests.

 

If your ruler's ever been right and still overlooked, it's worth seeing what building past that actually looks like.

 

“你在帮人倒米吗？“

Lauren Tan didn't get replaced by her own tooling.

She got promoted by it — and nobody handed her that promotion.

She built the case for it herself, one lint rule and one CI gate at a time, until the argument was undeniable.

That's the part nobody's really talking about when they talk about AI and engineering jobs: the shift rewards the people who go looking for the leverage first, not the people who wait to be told it's safe to look.

 

That "build the case yourself" instinct is exactly what clicked for me watching my own son learn to run a team instead of carry it.

My son started playing 王者荣耀 (Honor of Kings) since he was a teenager — a 5v5 multiplayer battle arena game where you manage a roster of specialized heroes, growing and levelling up their strengths through battles and gear.

In his early gaming days I could hear him cursing and swearing from his room — bad coordination, worst teammates. There was a phrase we used for a bad teammate in my own career — 帮人倒米*, a Cantonese idiom that literally translates as helping someone tip over their own grain container, meaning ruining or sabotaging someone's livelihood.*

But the cursing became less and less. He got good at managing his heroes and coordinating with his team. He started climbing the leaderboard. People started noticing him and his team. Then, in college, he started getting invited to tournaments — cash prizes when he won, and one lagged-connection loss at a KL tournament he still suspects was foul play.

Time has changed — my dad would've killed me for wasting my teenage years on video games.

Now he's in university, still playing, still winning tournaments and cash prizes with his team.

Why I'm bringing this up: I always thought these AI agents are kind of like the heroes my son uses in the game. Your skill is in your managing these heros and how to grow them, level them up to serve your purpose. You don't go down to the battle yourself. You engage the heros to do it for you.

The skill is in the managing.

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I keep walking into the same room wearing a different name on the door — the accountant's room, the analyst's room, now the engineer's.

Every time, someone's being told the machine is coming for their hours, not their name on the work.

 

Drop your take — are you already the head chef of your own stack, or are you still doing all the cooking yourself?

 

Clip credit: MTS (Monitor The Situation) — full video on their channel. DM for credit or removal requests.

 

If encoding your own judgment into the system sounds like the actual leverage skill here, the mechanism I built around exactly this is one link away.

Browser agents are given raw HTML and have to sift through and find out what's clickable themselves, which is a huge pain and waste of tokens. 

I’m building a browser that compresses webpages before passing information to agents, cutting token use by around 32x. 

Weak local models get constrained to one grounded choice at a time so they can't hallucinate actions or element IDs. Stronger models can plan multiple steps ahead. 

Actions are also policy gated, so riskier actions like purchases always require approval. 

It works with Claude Desktop, Cursor, VS Code, and Codex CLI over MCP, or directly through a local API if your setup doesn't use MCP.

I wanted to give eyes, ears and a voice to my agent. So I bought it a Linux phone.
The phone is fully dedicated to the agent. I talk to it via Telegram on my iPhone.

It didn’t take long before the agent could use the camera, microphone and speakers to interact with what is around it. It has also gps, gyroscope and a sim card.

I travel a lot and my original idea was for it to be my personal security cam manager for my stuff (using the phone’s camera). But this thing is kinda eerie now. It can wake itself up when it wants. It uses realtime api by openai to talk and reads the conversation as it’s happening… it “sees” from the camera. And it does everything while the display is turned off (I thought Linux Touch didn’t allow background activities after being idle for a while).

The fascination for this is currently beating the spookiness of it all. So I’ll keep on using it. For privacy reasons yesterday I switched the model to a local qwen3.8-27b running on my RTX 5000 Pro at home.

The system allows managing multiple agents at scale.
It’s complex and complicated so the best to work with it is to ask your Claude or any other agent to orchestrate your business or operations on that system.
You can also use the systems father agent that will build everything for you.
Happy to hear your thoughts and to help you quickly setup your business on my platform.

Bloomberg's own reporting already answers the question this clip raises — is the "messy middle" projected or already happening?

At Commonwealth Bank of Australia, Microsoft, Uber, and Hyatt, it's already happened: sizable call-center headcount cut using automated phone and chat systems, savings already banked.

Economist Molly Kinder's point isn't a forecast.

It's a line item that's already closed.

 

I've watched this exact math play out before superior technology ever touched a keyboard.

Suncon was getting jobs overseas. One of the countries we went to was India. We were building infrastructure — roads and bridges there. I didn't go. But my seniors went stationed there. When they came back during their scheduled holidays, one of them, a project manager, told me this story.

It so happened, that building roads and bridges inland means clearing jungles and passing through villages. As they were doing it, of course they engaged local villagers to be their workers and supervisors. Well, of course building infrastructure means bringing in heavy machineries, such as excavators, bobcats, mobile-cranes, 4-wheel-drive land-cruisers, etc. You know — the usual.

But the local villagers weren't happy. They complained that all these machineries have deprived the local population of their means of making a living. They have so many mouths to feed. A lot of them are quite poor. And many of them are very hunger for work.

And so a huge argument broke out. They even spitefully challenged our project team that they vast manpower was more superior than our machinery. I was so surprised when I heard it. How can they say that? How was that even a reasonable challenge, you know. My curiosity had the best of me.

Well, the project manager came up with an idea. He said, since they're so confident of their manpower, why don't we have a competition. Let's do a challenge of moving earth from point A to point B for our excavator/mobile-crane operator versus their vast manpower.

And they accepted.

At the day of challenge, the project manager set up two huge piles of earth at point A for both teams. The local villagers' team had their "vast" manpower formed a long-ass line between A and B, and started moving earth, with their primitive buckets and whatnot.

For our team, we set up our mobile-cranes, excavators and bobcats on strategic locations. And off we go.

You can guess the result. We won by a large margin. We were obviously much faster and better at it.

After that, the local villagers concede defeat.

The math is actually quite similar here. The one with superior technology always wins. This AI-take over is no different.

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Every time I dig into one of these stories the shape repeats: the tool doesn't ask permission, it just wins the argument by moving faster than the objection can be raised.

 

Ever watched something you thought was irreplaceable lose, and lose fast? Drop your take below.

 

Clip credit: Center for Humane Technology — full video on their channel. DM for credit or removal requests.

 

If you want to see how I'm actually building leverage against this instead of just watching it happen, it's just one link away

This is coarena.ai, where you can run long horizon computer-use tasks on frontier models for free!