Andrés Ponce de León R.

lIΔ & ʌvʌ’s dad | @ITAM_mx - @UChicago | Co-founder & CEO @entropia_ai

[Shane Ross @RossDynamicsLab]

This opening of a math lecture goes hard

[Kyle Harrison @kwharrison13]

I don’t think people appreciate how often most aspects of human life look like single biological organisms from the right angle.

Manhattan adjusted where distance = drive time.

[Y Combinator @ycombinator]

Brex co-founder and CEO Pedro Franceschi believes most people still underestimate how much AI will change the way companies are built. AI isn't just another tool, it's a new foundation for building products, teams, and companies.

In this episode of @LightconePod, @pedroh96 explains why we're only months into a platform shift as significant as the invention of electricity, why the CEO needs to be the chief AI officer, and why founders should rethink what's possible when intelligence is available on demand.

01:13 – How Pedro Became AI-Pilled
04:08 – The Electricity Analogy
05:21 – Free the Claw
06:56 – Making AI Safe for Enterprise
10:57 – Why Most Companies Are Behind
13:09 – AI Teammates, Not Chatbots
14:22 – The Case for Tokenmaxxing
18:24 – The Company of One
20:54 – The One Thing AI Can't Replace
28:06 – Building Customer World Models
32:58 – Rebuilding Brex Around AI
39:02 – The CEO Must Be the Chief AI Officer
43:50 – Building Company AGI
51:43 – Why We're Still So Early

[Yi Ma @YiMaTweets]

For intelligence, compression is not the goal. It is a means to an end. The true goal is to gain information that helps reduce uncertainty, which is entirely measurable. For any particular data of interest, to obtain a most informative representation of its distribution (also called memory or knowledge), an intelligent system tries to learn the most effective and efficient compressing operations (say layers of a network). This is what I have been saying: We learn to compress, and we compress to learn! This is precisely the main theme of our new open book.

[Department of State @StateDept]

No fear in the arena.

[Department of State @StateDept]

Happy Birthday, Mr. Secretary.

[Yann LeCun @ylecun]

Those are orthogonal concepts.
- World models trained on highly diverse data become foundation models: their encoders can be used for a wide variety of downstream tasks.
- "World" refers to two things: (1) predicting the evolution of a complex system or environment, (2) predicting the evolution of a system under control and its effect on the environment (action-conditioned world model) which is a necessary component of planning.

[Slack @SlackHQ]

In 2 years there will be more agents using Slack than people.

That's not a prediction. It's a roadmap.

Q1 FY27:

• Slack MCP: 1 million users in the first 6 weeks
• Slack AWUs: up 350% QoQ
• Slack in nearly half of Salesforce's $1M+ wins this quarter (+80% YoY)

Slackbot is now an MCP client. Create a NetSuite PO. Update a Jira project. Summarize a Salesforce case. No switching tools.

The future of work isn't in a browser tab.

Welcome to Agentic Slack. ⚡

[César A. Hidalgo @cesifoti]

Why I Made a Journal for AI-Generated Papers

Announcing a Journal for AI-Generated Papers was a bold move. Some loved it. Others thought it was a joke. But as the one building the journal, I should explain why.

First, let’s start with ...
https://t.co/khp5mnneiP

[Marc Andreessen 🇺🇸 @pmarca]

Many highly successful people are saying.

[Matt Shumer @mattshumer_]

Massively useful Codex trick for 10x better frontend:

You can ask Codex to use Claude as a sub-agent to have Claude handle frontend/design work.

Just say “Use claude -p with an excellent, well-scoped, but un-opinionated (UI/UX-wise) prompt anytime you need a design change).”

[Nassim Nicholas Taleb @nntaleb]

Catholicism survived so long because it is inherently self-correcting.

[ADRIAN | PROFESOR IA @TUPROFESORIA]

@grok el cuerpo humano es literalmente un montón de código legacy JAJAJA

[Greg Brockman @gdb]

the model alone is no longer the product

[The White House @WhiteHouse]

TWO KINGS. 👑

[Teng Yan @tengyanAI]

something i've noticed: AI agents create a weird new kind of burnout. esp for young people.

a lot of ambitious 22 year olds are going to think the answer is simple:
- spin up more agents
- ship more code
- sleep less
- outwork everyone

and for a while, it will feel incredible.
you can keep multiple agents running, feed them tasks, review outputs, fix mistakes, make decisions, and keep the whole loop moving.

the problem is that the work no longer drains you through typing. it drains you through judgment.
More attention.
More context switching.
More verification.
More decisions per hour.

so instead of 8-10 normal productive hours, you might get 4-5 extremely intense hours before your brain is fully cooked. and you feel numb until you sleep properly and reset

some of my friends are already burnt out. they don't say it out loud but i can tell.

the agent can keep working 24/7.
the human still has a hard limit

[signüll @signulll]

the future interface is probably three layers:

1. ambient intent capture

voice, location, calendar, screen context, messages, habits, biometrics, etc. the system understands what you’re trying to do before you explicitly “open” anything or augments your intent deeply.

2. agentic execution

the actual work happens through agents operating software, apis, browsers, documents, email, calendars, workflows, payments, support systems, whatever. most “computer use” becomes machine to machine clerical labor.

3. ephemeral verification ux

humans still need to inspect, compare, approve, edit, reject, or enjoy things. that’s where gui survives but as disposable, task specific surfaces generated for the moment.

[Pedro Domingos @pmddomingos]

Don't reward coders (or anyone) for using AI. Set goals that they couldn't achieve without it.

[Garry Tan @garrytan]

I came back to code because AI made it possible for me to build at a level I couldn't before.

I'm not coding despite being CEO of YC. I'm coding because this is the most important technological shift since the internet and I'd be an idiot to experience it from the bleachers.

I'm 45, running the most important startup institution in the world, and I can ship production software at 2am. That's not a distraction from the job.

That is the job understood correctly.

[Patrick Collison @patrickc]

I'm lucky enough to have a great doctor and access to excellent Bay Area medical care. I've taken lots of standard screening tests over the years and have tried lots of "health tech" devices and tools.

With all this said, by far the most useful preventative medical advice that I've ever received has come from unleashing coding agents on my genome, having them investigate my specific mutations, and having them recommend specific follow-on tests and treatments.

Population averages are population averages, but we ourselves are not averages. For example, it turns out that I probably have a 30x(!) higher-than-average predisposition to melanoma. Fortunately, there are both specific supplements that help counteract the particular mutations I have, and of course I can significantly dial up my screening frequency. So, this is very useful to know.

I don't know exactly how much the analysis cost, but probably less than $100. Sequencing my genome cost a few hundred dollars.

(One often sees papers and articles claiming that models aren't very good at medical reasoning. These analyses are usually based on employing several-year-old models, which is a kind of ludicrous malpractice. It is true that you still have to carefully monitor the agents' reasoning, and they do on occasion jump to conclusions or skip steps, requiring some nudging and re-steering. But, overall, they are almost literally infinitely better for this kind of work than what one can otherwise obtain today.)

There are still lots of questions about how this will diffuse and get adopted, but it seems very clear that medical practice is about to improve enormously. Exciting times!