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Karl Mehta Profile picture
@karlmehta
Jul 21, 2025 • 15 tweets • 5 min read • Read on X
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BREAKING: Norway's $2 trillion wealth fund ran a 12-month AI experiment.

They gave Claude access to their entire investment workflow.

Result: 213,000 hours saved. 20% productivity boost.

But what they found hiding in the data changed everything:

A Thread 🧵 Image
Image
Meet Nicolai Tangen, CEO of NBIM - the world's largest sovereign wealth fund.

700 employees managing $2 trillion in assets.

In 2022, he made a strategic decision that would reshape their entire operation.

But first, he had to address significant organizational resistance... Image
Tangen began systematically advocating for AI adoption across his 670-person team.

The challenge? Most investment professionals viewed AI as potentially disruptive to established workflows.

Traditional analysts were spending days on tasks that seemed impossible to automate.

Then Claude was introduced...
The first major breakthrough came with their Snowflake data warehouse integration.

Portfolio managers could suddenly query complex datasets using natural language.

What previously required technical SQL expertise now took seconds.

But this was just the initial phase... Image
Next, they implemented automated earnings call analysis.

Claude could process hours of executive commentary and extract key insights efficiently.

Risk managers were analyzing significantly more companies in the same timeframe.

Meanwhile, something important was happening behind the scenes...
NBIM monitors news for 9,000 companies across 16 languages.

Before Claude: Teams of analysts, days of manual work.
After Claude: Minutes of automated analysis with structured insights.

The efficiency gains were substantial, but they discovered an unexpected pattern...
The Investment Simulator revealed a critical insight:

Human portfolio managers were making predictable behavioral decisions that impacted returns.

AI could identify these patterns with 95% accuracy.

The fund was experiencing losses due to cognitive biases...
Here's where Tangen made his most decisive move:

"It can't be voluntary. If you don't use AI, you will never be promoted."

He implemented mandatory AI adoption across all 700 employees.

The organizational response was mixed... Image
But the measurable results were compelling:

• 20% productivity gains (213,000 hours saved annually)
• $100 million in trading cost savings
• 95% accuracy in voting decisions
• 49 million transactions optimized globally

The business case was clear.
The voting system became particularly effective.

They input 40-50 page executive compensation documents into Claude with their guidelines.

AI recommendations achieved 95% accuracy.

Even their notable "no" vote on Elon Musk's $56 billion Tesla package was AI-assisted.
Today, 100% of NBIM employees use Claude.

They're targeting $400 million in annual cost savings.

The fund that once struggled with efficiency is now leading AI adoption in asset management.

The key lesson wasn't just about technology... Image
It was about understanding human decision-making.

The AI didn't just automate processes - it identified costly behavioral biases.

Portfolio managers learned their emotional decisions were predictable and measurable.

AI became their analytical partner, not their replacement.
Tangen's framework for other executives:

"Don't make AI voluntary. Measure everything. Start with specific use cases."

He's now implementing selective hiring - prioritizing AI-skilled staff for new positions.

The strategy is clear: Build capabilities systematically. Image
P.S. If you're an SMB company in the healthcare or BFSI sector…

I've built an AI platform that helps you spot problems in your business before they happen.

Curious which insights could save you millions?

You can book a demo here, and we'll map it out: predixtions.com
Thanks for reading.

If you enjoyed this post, follow @karlmehta for more content on AI and politics.

Repost the first tweet to help more people see it:

Appreciate the support.

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More from @karlmehta

Karl Mehta Profile picture
May 1
Andrew Huberman just broke down why sugar cravings are usually not a willpower problem.

They are often a blood-sugar, sleep, and reward-circuit problem first.

Here are 7 science-based levers that make cravings easier to control:

1. Bad sleep makes cravings louder the next day.
Not just because you're tired.

Short or fragmented sleep changes appetite, blood sugar control, and the reward value of sweet foods.

So the willpower failure often started the night before.
2. A lot of sugar doesn't arrive as dessert.

It arrives in foods and drinks that are easy to consume fast, with very weak braking signals.

And this is where people get fooled:

Sweet and easy to overconsume are not the same problem, but they often travel together.
Read 12 tweets
Karl Mehta Profile picture
Apr 29
7 signs your brain is losing its backup capacity (You won't notice it as memory loss at first):

1. You only do things you're already good at.
Stanford neuroscientist David Eagleman just went on Diary of a CEO.

The key idea: your brain is not protected by "being smart."

It is protected by cognitive reserve: extra pathways when older ones weaken.
The wildest example: the Religious Orders Study.

Some nuns had Alzheimer's pathology at autopsy.

But they did not show the expected memory problems while alive.

Their brains had backup roads.
Read 13 tweets
Karl Mehta Profile picture
Apr 27
He predicted:

• AI vision breakthrough (1989)
• Neural network comeback (2006)
• Self-supervised learning revolution (2016)

Now Yann LeCun's 5 new predictions just convinced Zuckerberg to redirect Meta's entire $20B AI budget.

Here's what you should know (& how to prepare): Image
@ylecun is Meta's Chief AI Scientist and Turing Award winner.

For 35 years, he's been right about every major AI breakthrough when everyone else was wrong.

He championed neural networks during the "AI winter."

But his new predictions are his boldest yet...
1. "Nobody in their right mind will use autoregressive LLMs a few years from now."

The technology powering ChatGPT and GPT-4? Dead within years.

The problem isn't fixable with more data or compute. It's architectural.

Here's where it gets interesting...
Read 18 tweets
Karl Mehta Profile picture
Apr 25
Every person over 30 blames aging for their stiff, painful back.

Turns out, it is not your chair or your age.

It is 3 support systems that stop doing their job after years of sitting.

Here is the simple rebuild path:
Back pain is not always a "tight back" problem.

Sometimes the back is just the part screaming loudest.

The real issue is often lower down and deeper:

1. stiff hips
2. sleeping glutes
3. a core that cannot brace under load Image
That matters because your lower back was not built to do every job.

It should transfer force.
It should stabilize.
It should move when needed.

But if your hips stop moving and your glutes stop helping, the spine starts compensating.

And this is where people get stuck: Image
Read 15 tweets
Karl Mehta Profile picture
Apr 14
A massive Swedish study followed 30,000 women for 20 years.

Sun exposure tracked. Mortality tracked.

The researchers were stunned by what they found.

Here's what avoiding the sun actually does to your lifespan: Image
This was the Melanoma in Southern Sweden cohort.

29,518 women.
20 years.

Not a mood survey.

A mortality study: Image
And the first result was brutal.

In the 2014 paper, the mortality rate among women who avoided sun exposure was approximately twofold higher than in the highest sun-exposure group.

That is not a rounding error: Image
Read 12 tweets
Karl Mehta Profile picture
Apr 1
Columbia and NYU researchers tracked 11,000 people for 20 years.

Urine tests before. Urine tests after.

When they switched to clean water, their risk of dying from cancer and heart disease dropped 50%.

Here's what was in their water the entire time: 🧵 Image
Image
The study was run by Columbia University in Araihazar, Bangladesh.

622 adults. All drinking from wells above the arsenic safety limit.

Each was given a water filter.

Researchers tracked urinary arsenic, a direct biomarker of what's inside your body. Image
Within a single week, median urinary arsenic dropped from 117 µg/L to 51 µg/L.

A 56% reduction in the toxin load inside their body.

From one change. In 7 days.

But the real question was: does that actually change health outcomes? Image
Read 14 tweets

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