oderau

Managing Partner @ Limbic Capital. Investor modernising legacy industries with PE + AI. Building enduring companies with institutional partners.

[oderau @oderau]

@DilumSanjaya what does your harness look like for building these?

[oderau @oderau]

@DilumSanjaya what does your harness look like for building these?

[Superman @thesupermannx]

Researchers proved AI has deleted every reason universities exist.

Harvard University ran a controlled experiment pitting a custom AI against their own top-tier classrooms.

And the results are going to collapse the higher education bubble.

They took 194 undergraduates and split them up.

One group learned physics in one of Harvard’s best hands-on, active-learning physical classrooms. Group work. Instructor support. The premium university experience.

The other group went home and learned the exact same material with an AI tutor.

The AI didn't just win. It embarrassed the institution.

Students using the AI learned more than twice as much as the students in the elite Harvard classroom.

They scored 30% higher on the final assessment.

And they did it in less time.

Let that sink in.

A piece of software sitting on a laptop outperformed a world-class faculty in one of the most elite learning environments on Earth.

Universities have always justified their exorbitant tuition with two things: access to elite knowledge and the physical classroom experience.

This study just proved both of those moats are gone.

When software can teach you complex physics twice as well as a $60,000-a-year institution, the math of higher education breaks permanently.

The AI didn't just give the students answers. It used strict pedagogical guardrails. It guided. It questioned. It forced the students to do the cognitive work.

It offered perfect, one-to-one tutoring, personalized to the exact moment a student misunderstood a concept.

That level of attention is mathematically impossible to scale in a physical lecture hall.

For a thousand years, the university was the only place to get a premium education.

Now, it’s the bottleneck.

If AI can double your learning speed for a fraction of the cost, what exactly are students taking on decades of debt to pay for?

[Incentivising @incentivising]

In game theory, playing the wrong game can be far more punishing than losing the right games. All your effort has gone to waste. You must avoid that.

[oderau @oderau]

@VittoStack Would love to join

[oderau @oderau]

@boardyai @andrewdsouza building at Limbic Capital, exploring a sponsor-led roll-up approach. want in on Boardy Pro

[oderau @oderau]

@boardyai building a sponsor-led roll-up approach. want in on Boardy Pro

[Timothy Ash @tashecon]

The biggest threat to Western liberal market democracy is not Russia, China or Iran, it is Elon Musk promoting race hate. https://t.co/LkEMVCEoFf

[oderau @oderau]

@gregisenberg @joshelman Deep DD

[Elias @iam_elias1]

Two economists just published a mathematical proof that AI will destroy the economy.

Not might. Not could. Will — if nothing changes.

The paper is called "The AI Layoff Trap." Published March 2, 2026. Wharton School, University of Pennsylvania. Boston University. Peer reviewed. Mathematically modeled.
The conclusion is one sentence.
"At the limit, firms automate their way to boundless productivity and zero demand."

An economy that produces everything. And sells it to nobody.
Here is how you get there.
A company fires 500 workers and replaces them with AI. A competitor fires 700 to keep up. Another fires 1,000. Every company is behaving rationally. Every company is following the incentives correctly. And every company is building a trap for itself.

Because the workers who were fired were also customers.
When they lose their jobs faster than the economy can absorb them, they stop spending. Consumer demand falls. Companies respond by cutting costs — which means automating more workers — which means less spending — which means more falling demand — which means more automation.

The loop has no natural exit.
The researchers tested every proposed solution. Universal basic income. Capital income taxes. Worker equity participation. Upskilling programs. Corporate coordination agreements.
Every single one failed in the model.
The only intervention that worked: a Pigouvian automation tax — a per-task levy charged every time a company replaces a human with AI, forcing them to price in the demand they are destroying before they pull the trigger.

No government has implemented this. No major economy is seriously discussing it.
Meanwhile the numbers are already tracking the curve. 100,000 tech workers laid off in 2025. 92,000 more in the first months of 2026. Jack Dorsey fired half of Block's workforce and said publicly: "Within the next year, the majority of companies will reach the same conclusion."
Nobody is doing anything wrong. Companies are following their incentives perfectly. That is exactly the problem.

Rational behavior. At scale. Simultaneously. With no mechanism to stop it.
Two economists built the math. The math leads to one place.

Source: Falk & Tsoukalas · Wharton School + Boston University ·
https://t.co/4m8E9jQNYm

[Aakash Gupta @aakashgupta]

There's a physicist at Stanford named Safi Bahcall who modeled this exact principle and the math is wild.

He calls it "phase transitions in human networks." When you're stationary, your probability of a lucky event is limited to your existing surface area: the people you already know, the places you already go, the ideas you've already been exposed to. Your opportunity window is fixed.

When you move, your collision rate with new nodes in a network increases nonlinearly. Double your movement (new conversations, new cities, new projects) and your probability of a serendipitous encounter doesn't double. It roughly quadruples. Because each new node connects you to their entire network, not just to them.

Richard Wiseman ran a 10-year study at the University of Hertfordshire tracking self-described "lucky" and "unlucky" people. The single biggest differentiator wasn't IQ, education, or family money. Lucky people scored significantly higher on one trait: openness to experience. They talked to strangers more, varied their routines more, and said yes to invitations at nearly twice the rate.

The "unlucky" group followed the same routes, ate at the same restaurants, and talked to the same 5 people. Their networks were closed loops. No new inputs, no new collisions.

Luck isn't random. Luck is surface area. And surface area is a function of movement.

The lobster emoji is doing more work than most people realize. Lobsters grow by shedding their shell when it gets too tight. The growth requires a period of total vulnerability. No protection, no armor, soft body exposed to the ocean.

That's the cost of movement nobody posts about. You have to be uncomfortable first. The new shell only hardens after you've already moved.

[oderau @oderau]

@trq212 Then proceed to build it out

[oderau @oderau]

@trq212 Read a user generated agentic system requirements doc (PRD equivalent) and suggest structure of the repo and system based on.

[oderau @oderau]

@DarrelFrater Dm for one of our portcos

[Rohan Paul @rohanpaul_ai]

🇨🇳 China is scaling agricultural robots.

Autonomous harvest at 24/7 cadence is the new baseline for food security.

Vision models pick, arms place, logistics sync, human supervisors handle exceptions.

Cheaper fruit, fewer bruises, happier supply chain

[P.M @p_misirov]

there is a game called "data center" on steam which let's you build and manage your own data center.

this is lowkey genius, the best way to educate people on a new trait. hyperscalers should learn a thing or two from "edutainment".

[The Humanoid Hub @TheHumanoidHub]

Perceptive Humanoid Parkour (PHP) introduces a modular framework that enables the Unitree G1 humanoid to perform long-horizon, vision-based parkour.

- It chains retargeted human motion clips into diverse, long-horizon kinematic reference trajectories.

- RL expert policies learn individual skills that are distilled into a depth-conditioned student policy.

- The robot autonomously selects the appropriate skill based on the obstacle geometry.

[Tristan @Tristan0x]

This aired tonight to 1 billion people in China. A year ago these robots could barely wave a handkerchief, now they can do backflips and kung fu with nunchucks. Physical intelligence is the next frontier.

[oderau @oderau]

@nainar92 @nbrichtova @heyitsbeaaaaaaa @oliver_wang2 @m__dehghani Want to create containers that hold & prompt dynamic/animated images, like a mini app. This would allow the container when opened to auto regenerate a dynamic & updated image or animation inside. Would be a powerful way to auto prompt and embed nano into other apps non statically

[oderau @oderau]

@LoganHaskett Docuseal's pretty good