🚨𝘽𝙍𝙀𝘼𝙆𝙄𝙉𝙂: European Commission President Ursula von der Leyen unveiled EU–INC, a new framework that lets you launch a company in 48 hours for under €100
Starting a company across the EU today = 27 legal systems, 60+ company structures 🤯
That might be about to change…
The European Commission just introduced 𝗘𝗨 𝗜𝗻𝗰., a new optional corporate framework designed to make Europe actually function like one market.
Here’s what stands out:
→ Set up a company in 48 hours
→ Cost: < €100
→ Fully online, no minimum capital
→ One single framework across all EU countries
→ Easier share transfers & fundraising
→ EU-wide employee stock options (huge for talent)
Especially the EU-wide stock option plans, taxed only when employees actually sell (instead of when granted) is huge.
This makes it far easier for startups to attract and retain top talent, finally putting Europe closer to the US playbook.
Source/More info: https://t.co/8pI4gv0Hh7
In short: This is Europe trying to compete with the simplicity of a Delaware C-Corp 🇺🇸
And honestly… it’s long overdue.
For years, European founders had 2 choices:
1. Stay local and deal with fragmentation
2. Move to the US to scale
𝗘𝗨 𝗜𝗻𝗰. is trying to remove that trade-off.
If executed well, this could be one of the most important structural changes for European startups in decades.
What do you think?
@zachlloydtweets I’m using the GetShitDone repo (GSD) — it’s a lightweight meta-prompting system for Claude Code/OpenCode that does planning + spawns sub-agents for every task. Zero context rot and feels very similar to this /orchestrate flow.
https://t.co/PM3exTtXb9
Holy smokes @MeetOrion! First assignment organise and clean my download folder, I read/skim/download a ton of research that has piled up and now I do not know anymore what to keep and what not. Orion fixed this super simply - LOVE IT. More to come!
🇮🇪 IRISH TEACHER ARRESTED AGAIN AFTER REFUSING TO USE "THEY" PRONOUN FOR STUDENT
Back in cuffs again. Enoch Burke, the Irish teacher who’s already spent over 560 days in jail, was arrested again this morning outside Wilson’s Hospital School.
Why? He wouldn’t call a male student “they,” as demanded by the school principal.
"This is all about transgender ideology, forcing it upon every school in the country.
They want silence, not debate. But my conscience will bring me back to this gate.
I was never told I had to renounce my Christian beliefs to do this job.
They can throw me in a prison cell, but they can’t force me to lie."
Source: @EnochBurke
@akusharmaa Very cool - exactly what I was looking for - Vellum is what the world needs. How do you deal with context decay? Usually hits in 30 - 75 min with all other models. What is your way of dealing with it?
Introducing Vellum: Agents for the rest of us.
Just describe your task and get a working agents in minutes.
This is not another ChatGPT wrapper or a complex workflow builder. We spent thousands of hours to build the “brain” so you don’t have to look at error logs and learn prompting.
Vellum will ask smart questions, connect to your apps, build you a custom agent, and make improvements along the way.
Go to https://t.co/k2z9HCUM5V and test it for yourself (we’re giving away 30 credits to everyone who signs up today)
100 credits if you repost or talk about your use cases in thread
@TrumpGirlLove Not medical advice. Research seems to point protocols with pre-, probiotics, and prioritize soluble fibers and as a basis Mediterranean (natural ingredients) home cooked meals - skip all else. Omega 3 and d-vitamin as base supplements. Talk to holistic and functional medicine doc
@TrumpGirlLove Gut dysbiosis linked to PANDAS/PANS via gut-brain axis — strep especially common treatments may alter microbiota → inflammation → neuro symptoms.
Key reads:
2018 profiling study: https://t.co/zeFmVtMSyf
2025 gut-oral-brain review: https://t.co/v3HyPPNraD
Holy shit… this paper might be the most important shift in how we use LLMs this entire year.
“Large Causal Models from Large Language Models.”
It shows you can grow full causal models directly out of an LLM not approximations, not vibes actual causal graphs, counterfactuals, interventions, and constraint-checked structures.
And the way they do it is wild:
Instead of training a specialized causal model, they interrogate the LLM like a scientist:
→ extract a candidate causal graph from text
→ ask the model to check conditional independencies
→ detect contradictions
→ revise the structure
→ test counterfactuals and interventional predictions
→ iterate until the causal model stabilizes
The result is something we’ve never had before:
a causal system built inside the LLM using its own latent world knowledge.
Across benchmarks synthetic, real-world, messy domains these LCMs beat classical causal discovery methods because they pull from the LLM’s massive prior knowledge instead of just local correlations.
And the counterfactual reasoning?
Shockingly strong.
The model can answer “what if” questions that standard algorithms completely fail on, simply because it already “knows” things about the world those algorithms can’t infer from data alone.
This paper hints at a future where LLMs aren’t just pattern machines.
They become causal engines systems that form, test, and refine structural explanations of reality.
If this scales, every field that relies on causal inference economics, medicine, policy, science is about to get rewritten.
LLMs won’t just tell you what happens.
They’ll tell you why.