👑𝐁 𝐈 𝐋 𝐋 𝐘

AI ENGINEER | DIGITAL SOLUTIONS CONSULTANT.
Jesus is Lord👑👑👑 || C.E.O at @bibrtech

[流氓兔🐰 @LiumangtuCrypto]

建议兄弟们都去看这部Netflix高分纪录片

《聪明生活经济学》

看完彻底刷新金钱认知。

[Di⭕s🀄 @Dioslev]

A must listen for ALL MEN 🛑

[👑𝐁 𝐈 𝐋 𝐋 𝐘 @BillyBrightson]

@AgyekumYeboah Read “how to Ikigai” for more about this topic

[Ricardo @Ric_RTP]

Microsoft just banned its own engineers from using AI.

The tool was literally costing MORE than the humans it was supposed to replace.

They lied to you about AI adoption and now the whole narrative is blowing up:

Microsoft gave thousands of engineers access to Claude Code six months ago and encouraged them to use it.

Engineers loved it and adoption exploded. But then the invoices arrived.

Token-based pricing means every query, every code review, every debugging session costs money. At scale across 100,000 engineers, the numbers became so large that Microsoft issued an internal order to cancel nearly all Claude Code licenses by end of June and force everyone onto their own cheaper tool instead.

The company that invested $5 billion in Anthropic just told its own people to stop using Anthropic's product because it costs too much.

Uber's story is even worse...

Their CTO Praveen Neppalli Naga told The Information that the budget he planned for the full year was "blown away already" by April.

Uber had rolled out Claude Code in December 2025. By March, 84% of their 5,000 engineers were using it with 70% of all committed code coming from AI systems.

Heavy users were burning $500 to $2,000 per month each. Naga himself spent $1,200 in a single two-hour demo session.

The company had even built internal leaderboards ranking engineers by how much AI they used. They literally gamified the spending and then ran out of money.

Now look at what Nvidia's own VP of applied deep learning Bryan Catanzaro said to Axios last month. Direct quote:

"For my team, the cost of compute is far beyond the costs of the employees."

This is a VP at the company that SELLS the chips saying that using AI is more expensive than paying humans.

Think about what this means for the entire AI narrative.

Every CEO on every earnings call for the past two years has said the same thing:

AI will make us more efficient, reduce headcount, and cut costs.

The stock market rewarded every company that said it.

Fired workers, stock goes up. Announced AI adoption, stock goes up.

But the actual companies deploying AI at scale are discovering the math doesn't work. The MORE employees use AI, the HIGHER the bill.

Goldman Sachs forecasts a 24x increase in token consumption by 2030 as companies adopt AI agents. Gartner just published a report showing that even though individual token prices will drop 90% by 2030, total enterprise AI costs will go UP because agents consume exponentially more tokens per task than basic tools.

Meta built an internal dashboard called "Claudeonomics" to track which employees use the most AI. Amazon started pushing engineers to "tokenmaxx," their internal term for consuming as many AI tokens as possible.

Both companies are spending hundreds of billions on AI infrastructure this year alone.

And Microsoft, the company that bet its entire future on AI, just told 100,000 engineers to stop using the tool they liked best because the per-token bills got out of control.

The companies building AI are telling investors it saves money. The companies using AI are finding out it costs more than the humans it was supposed to replace. And even the company that makes the chips just admitted it through its own VP.

This is the gap nobody on Wall Street is pricing in.

$725 billion in AI infrastructure spending this year across Big Tech. And the first companies to actually deploy these tools at scale are already pulling back because the economics don't work.

What do you think?

[Jaynit @jaynitx]

Steve Jobs literally predicted the iPhone, the Internet, AI and the next 50 years of technology in a single speech from 1983:

[👑𝐁 𝐈 𝐋 𝐋 𝐘 @BillyBrightson]

https://t.co/dURZtK8fpj

[Claude @claudeai]

Introducing Claude Managed Agents: everything you need to build and deploy agents at scale.

It pairs an agent harness tuned for performance with production infrastructure, so you can go from prototype to launch in days.

Now in public beta on the Claude Platform.

[Josh Kale @JoshKale]

This is big... Anthropic just announced a model so powerful they won't release it to the public out of fear over the damage it will cause 😨

Claude Mythos Preview found thousands of zero-day exploits in every major operating system and web browser...

The numbers are hard to believe:
> $50 to find a 27-year-old bug in OpenBSD, one of the most security-hardened operating systems ever built

> Under $1,000 to find AND build a fully working remote code execution exploit on FreeBSD that grants unauthenticated root access from anywhere on the internet

> Under $2,000 to chain together multiple Linux kernel vulnerabilities into a complete privilege escalation exploit

For context: these are the kinds of findings that previously required elite security researchers working for weeks.
Anthropic engineers with no formal security training asked Mythos to find exploits overnight. They woke up to working code the next morning.

The results were so impressive Anthropic assembled Apple, Google, Microsoft, Amazon, NVIDIA, and seven other organizations into Project Glasswing:

A $100M defensive coalition. They're not releasing this model publicly. Instead, they're racing to patch the world's infrastructure before models like this proliferate.

[Quinn @Crtquinn]

How GOD MADE ME A MILLIONAIRE TRADER

A CHINESE TRADER SHARED HIS FULL STORY

WORTH WATCHING 💯

[yaw. @yabbanx]

Created by a Ghanaian. Amazing!

[👑𝐁 𝐈 𝐋 𝐋 𝐘 @BillyBrightson]

And he is serious about it

[👑𝐁 𝐈 𝐋 𝐋 𝐘 @BillyBrightson]

@ajeezayGH What is poisonous about this. This is too exaggerated 🤦🏼‍♂️

[Naval @naval]

It’s not about junior vs senior, it’s about “good with AI” vs “not good with AI.”

[Rohan Paul @rohanpaul_ai]

Andrej Karpathy on what makes Elon Musk unique.

Elon keeps teams small, highly technical, and removes low performers very quickly.

He pushes for intensity, avoids useless meetings, and stays deeply connected with engineers.