Jose M.

Engineer - Synthetic Biology, Computer Science, Intelligence Amplification, Automation Enthusiast, Digital Nomad

[Mario Zechner @badlogicgames]

and now i never have to look at gmail again, have an interface exactly how i want it, and all of it is accessible by my agent, inside my agent's ui.

[Jose M. @eth3rdrift]

@carllerche Ready for production? I have a new commercial site I'd like to use this for. Say the word!

[Bojan Tunguz @tunguz]

Analog techno is the thing.

[Jose M. @eth3rdrift]

@DanielLockyer What's the best way to integrate it with Codex?

[Andreas Kling @awesomekling]

Stages of grief about the effect of AI on open source.

Denial:
- AI code is slop! Nobody serious will use this.
- Open source will keep working exactly like it always has.

Anger:
- These AI slop PRs are ruining GitHub!
- Ban AI-generated code!
- If you close PRs, you're not open source anymore!

Bargaining:
- Okay, AI can write code, but only if a human reviews every line.
- Maybe adversarial AI review will make arbitrary external code intake safe again.

Depression:
- Wait, if code generation is basically free, what is a contribution anymore?
- Is GitHub-style open source culture just going away?

Acceptance:
- Open source is still open source, even if the contribution model evolves.
- Good issues, test cases, benchmarks, specifications, and ideas become the scarce inputs.
- Upstream may stop accepting arbitrary code while forking becomes much easier.

Bonus stage! Reconstruction:
- Projects redesign around maintainer-controlled agents, issue-driven development, stronger test/validation infrastructure, and new ways for contributors to earn trust.

[Eric S. Raymond @esrtweet]

Experience gives perspective. Programming is not dead, and never will be.

It's late September 2026. Sometime in September 1976, just after I entered college, I wrote and ran my first serious program. I have now been a programmer for literally 50 years.

And man, I have seen it *all*. Punched cards to glass ttys on minicomputers to workstations to the earliest micros. I've written business software, communication programs, development tools, games, language implementations, kernel device drivers, graphics libraries, a few critical pieces of infrastructure, and all manner of odd programs for which there is no taxonomy. Coded in a score of languages some of which are now forgotten. I've run over 70 open-source projects and contributed to at least as many more.

Along the way I noticed a few things, and wrote about them, and that made me famous. But I'm not here to write about that today. I'm here to write about what it means to be a programmer and a technologist with the Singularity upon us.

I have lost count of the number of times I have been told "programming is over". You kids may think this is a new claim that came into the world with LLMs. Hah! There's been that kind of talk at every step function in the quality of our programming tools. I first heard it when compilers were replacing hand-hacked assembler in the early 1980s, and I wouldn't be a bit surprised if somebody said it earlier when in-memory code replaced plugboards.

One constant amidst all this change is that the intentions in a user's head do not magically turn into executable instructions that a computer can run. Another constant is the mindset of the people who specialize in bridging the gap between wish and algorithm. A programmer is a programmer is a programmer - the tools are secondary.

"But it's different this time!" some people will say, "AIs are superhuman now!" So? What did you think the optimization stage of a compiler was, chopped liver? We've been relying on tools that exceeded human capabilities all along - we built them precisely because our meatbrains could not otherwise keep up with the demands of the job.

It's been a hell of a ride, that 50 years. I've succeeded and failed and succeeded again. Done a lot of work I'm proud of. Built at least a few things that look like they're going to last. None of that goes away because, hypothetically, an AI might have made me faster.

The work is never done, even if the tools can talk to us now. Because intentions still have to be communicated; people who specialize in that and develop right mindset to do it still have a major advantage over people who don't.

If you're feeling depressed because you spent years or decades developing hand-coding skills that are obsolete now? Buck up. You still have the most important asset - a mind that knows how to think that way.

I'm facing the winds of the Singularity with a smile. Because 50 years and I'm still standing - still shipping code that people can use, still learning, still refusing to be paralyzed by the pace of change.

The best therapy for your uncertainty? Get to work on something.

[Stephen Wolfram @stephen_wolfram]

Since all sorts of people have asked me, I decided to write down my current thoughts on "What's the Future for Pure Math Research in the Age of AI?"
https://t.co/TQxHFIirSG

[John Spencer @SpencerGuard]

This should be pushed far and wide. Watched in every college class in the U.S. Thank you @billmaher The moral confusion is gross. "It is not a genocide, it is a counterattack in a war...Gaza equals genocide is a lie, an easily provable lie (as I have argued from first hand observations in Gaza). The fact that so many democrats go along with it is to me the party's worse moment since they undid reconstruction after the civil war...words have meaning...genocide, kill or try to kill an entire people, you can't just change the definition of genocide to mean counterattack in a war where people including civilians die, that's every war..."

[Shyam Sankar @ssankar]

EA AI safetyism increasingly looks like Marxism-Leninism for the algorithmic age.

The old vanguard claimed privileged knowledge of the inevitable course of History. The new one claims privileged knowledge of the probabilistic course of Humanity.

Both use an elaborate intellectual framework to reach the same political conclusion: a small group of enlightened people must constrain everyone else for their own good.

That has never lead to anything except monumental human suffering.

[Marc Andreessen 🇺🇸 @pmarca]

What Is To Be Done?

I propose a simple plan:

Big AI companies should be allowed to build AI as fast and aggressively as they can – but not allowed to achieve regulatory capture, not allowed to establish a government-protect cartel that is insulated from market competition due to incorrect claims of AI risk. This will maximize the technological and societal payoff from the amazing capabilities of these companies, which are jewels of modern capitalism.

Startup AI companies should be allowed to build AI as fast and aggressively as they can. They should neither confront government-granted protection of big companies, nor should they receive government assistance. They should simply be allowed to compete. If and as startups don’t succeed, their presence in the market will also continuously motivate big companies to be their best – our economies and societies win either way.

Open source AI should be allowed to freely proliferate and compete with both big AI companies and startups. There should be no regulatory barriers to open source whatsoever. Even when open source does not beat companies, its widespread availability is a boon to students all over the world who want to learn how to build and use AI to become part of the technological future, and will ensure that AI is available to everyone who can benefit from it no matter who they are or how much money they have.

To offset the risk of bad people doing bad things with AI, governments working in partnership with the private sector should vigorously engage in each area of potential risk to use AI to maximize society’s defensive capabilities. This shouldn’t be limited to AI-enabled risks but also more general problems such as malnutrition, disease, and climate. AI can be an incredibly powerful tool for solving problems, and we should embrace it as such.

To prevent the risk of China achieving global AI dominance, we should use the full power of our private sector, our scientific establishment, and our governments in concert to drive American and Western AI to absolute global dominance, including ultimately inside China itself. We win, they lose.

And that is how we use AI to save the world.

It’s time to build.

[Emma Camp @emmma_camp_]

Can rent control fix the housing crisis? No. In fact, it could make things a whole lot worse.

Find out more in my latest for @WSJFreeEx

[Andy Masley @AndyMasley]

This article was basically exactly what I'd like all reporting on data centers to look like. A solid grappling with costs and benefits + interviewing locals who represent the full spectrum of opinion

[Jose M. @eth3rdrift]

If AirPods ever come with cameras, they'd be worn a lot more than any glasses ever would.

https://t.co/qqjj8U4TP2

[Deedy @deedydas]

Meritocracy in tech is precarious. It’s everywhere and nowhere at the same time.

Cynics will tell you there is none. How can it possibly be fair that the Stanford grad seemingly can raise from any VC they want but the VirginiaTech one has to struggle? If you’re from a big lab, you’re the prom queen, but if you’re from a yesteryear SaasCo, no one even picks up your resume. Warm intros through people in the know seem to dictate who is allowed to win. To even get an interview at YC or a VC gig, it feels like an elite education is a prerequisite. It can seem like the system is rigged against you.

Yet, that view would be so patently false. The valley is one of the best meritocracies in the world. It’s just not obvious when you’re young. Tim Cook went to Auburn and spent 12yrs at IBM before Compaq. Nikesh Arora, one of the highest paid execs in America, went to a “lower ranked” IIT from India. Jan Koum dropped out of San Jose State to work at Yahoo before founding Whatsapp. The CTO of Anthropic went from a no-name college most couldn’t put on a map. Dylan Patel who sits on the most influential set of data in the world, got there by pure passion. Dwarkesh was a nobody before running the most influential podcast in tech. The team that built GPT-3 isn’t exactly a Harvard reunion. Jensen was from Oregon State and Denny’s. Tobi Lutke, Palmer Luckey, Frank Slootman, John Carmack, Jeff Dean, Linus Torvalds, Satya Nadella, the examples are infinite.

How can both of these be true? At any given moment, it feels like a stratified society based on your current credentials. What the Valley offers is the fastest path to updating those credentials.

The unspoken rule of the valley is that you get infinite shots on goal, but you just have to prove yourself to buy the next shot. If you try to jump too high, you might hit a brick wall. For some, it’s easy. You went to Stanford / MIT. Everyone thinks you’re the sharpest of your generation. But opportunity is abundant and you should be risk-on. One amazing product, one viral open source repo, one phenomenal company you helped build, one highly technical blog post, one amazing career stint: all can shape your fortunes overnight.

We often forget how much of a privilege that is. In most other parts of the world, you cannot in fact work yourself into the elite strata. CEOs of companies in India or China rarely are from a non-elite university. Corporate structures there are far less accommodating to former failures. Even in New York finance, there’s a certain way you need to speak, attire you need to wear and an unspoken private club that needs to welcome you. That doesn’t exist in the Valley. Sure there are private clubs, but anyone can make it to them. But you can always buy your entrance ticket with proof of work.

In the moment, it can seem not meritocratic. This happens especially when you’re younger. Hell, it’s not perfect and luck may never strike you. But career is a long game, and a wise valley veteran once told me “if you’re ambitious and you spend 25yrs here, there’s next to no chance you’re not making it.” And I’ve seen that too. It might not be fair in the moment, and it may not be fair to everyone, but it converges very quickly to it.

[Hoover Institution @HooverInst]

Thomas Sowell is known as an economist. But is he one of America's greatest historians?

Victor Davis Hanson (@VDHanson), Niall Ferguson (@NFergus), and Coleman Hughes (@Coldxman) explore Sowell's sweeping view of history, his enduring ideas, and why a new generation is discovering his work decades after it was written.

Watch the full conversation on X:

[Greg Collins @GregCollins111]

Recently submitted my final manuscript on the idea of civil society in early black political thought. Two books I highly recommend as introductions to Washington and Du Bois are @robertjnorrell's Up from History and David Levering Lewis' W.E.B. Du Bois: A Biography.

[Alex Finn @AlexFinn]

Something strange has happened over the last 10 years

When I was a kid, every tech publication (Wired, TechCrunch, Engadget) truly loved and celebrated technology

Over the last 10 years they all collectively decided they absolutely LOATHE technology.

Every article is a hit piece. Every entrepreneur and creative thinker is being destroyed. The greatest inventors of our lives are being villainized.

A lot of people are saying it’s because we live in a clickbait culture and hate is what drive clicks, but I don’t buy it

If hate drove clicks all of these publications would be thriving. Instead, they’re all failing, going bankrupt, laying people off and on top of that I literally can’t name a single person who reads any of them

There is a such a massive opportunity right now for anyone who’s willing to start a tech publication that actually celebrates and loves technology.

I’m DYING for a version of Wired that actually covers real tech with an optimistic lens, and I know many other are too.

Might have to f around and do this myself.

[Jose M. @eth3rdrift]

The new #Siri rocks! Wait until you try it. #Apple

[Jose M. @eth3rdrift]

@uaustinorg The Pursuit of Happiness - How Classical Writers on Virtue Inspired the Lives of the Founders and Defined America by Jeffrey Rosen

[Startup Archive @StartupArchive_]

Shopify CEO Tobi Lutke explains Goodhart’s law and why he doesn’t like KPIs or OKRs

“Goodhart’s law is real. The moment a metric becomes a goal, it’s no longer a useful metric… No metric by itself is a complete heuristic for a complex business. There’s a million different tensions in a company, and you can’t keep all of them in harmony by optimizing for one thing.”

For this reason, Shopify doesn’t use KPIs or OKRs. But as Tobi explains, this doesn’t mean they don’t value data and metrics.

“We are extremely data informed. We have invested enormous amounts of money and time into systems that give us basically everything at our fingertips… But what Shopify attempts to do is just not over-fit for what’s quantifiable.”

People love optimizing for highly-quantifiable things because there’s immediate gratification that comes from seeing a number go up. But Tobi thinks that the most important aspects of a product are rarely quantifiable:

“The overlap of the most valuable things you can do with a product and the things that happen to be fully quantifiable are like maybe 20%. Which leaves 80% of a value space unaddressable by the people who only look at quantifiable things.”

He continues:

“Shopify is comfortable with unquantifiable things like taste, quality, passion, love, hate… The sort of deep satisfaction that a craftsperson feels when they’ve done a job well is actually a better proxy if you allow it to be.”

They then have robust analytics systems that tell the company if something’s wrong or a new rollout breaks something.

“We think about it as a cockpit for a pilot. The decisions are still made by pilots, and we think this leads to better results… I think there needs to be more acceptance in business of unquantifiable things… And then metrics take a support function.”

Source: @lennysan (Feb 2025)