gustavo

agency is all you need

[Dustin @r0ck3t23]

Jensen Huang just killed the AI jobs panic.

Not with a forecast. With a pattern.

Huang: “The fact of the matter is PCs made us more busy. The internet made us more busy. Mobile devices made us super busy.”

Every tool that promised to free us expanded what we could reach instead.

The PC did not give accountants their afternoons back. It gave them ten times the clients.

The internet did not slow anything down. It erased the geographic limit on what one person could build.

The smartphone did not hand you time. It handed work your coordinates and never let go.

None of them reduced what we did. All of them raised what we could.

AI will not be different.

It will not give you rest. It will give you a thousand things you couldn’t have built before.

The people waiting for relief are reading the wrong pattern.

This was never about less. It was always about expanding what one person can attempt.

The panic runs on one assumption.

That labor is surplus.

Huang: “We are millions of truck drivers short. We are tens of millions of manufacturing workers short.”

The economy is not drowning in surplus labor. It is bleeding from the absence of it.

Robots are not arriving as invaders. They are arriving as reinforcements to a system already failing without them.

The collapse was already underway. The machines just showed up to a building already on fire.

Huang: “They’ll hire more people to manage more robots, hire more people, manage more agents.”

The raw work is leaving human hands. The direction of it is not.

Every company deploying agents still needs someone deciding what they’re pointed at.

The question is not whether AI replaces you.
The question is whether you learn to command it before someone who already has.

Every tool that promised less work delivered more world.

AI will be the largest expansion of that pattern in history.

You are not losing your job to a machine.

You are losing it to someone who learned to run one.

[Anthony Pompliano 🌪 @APompliano]

I have changed my mind on how AI will impact jobs in America.

Previously, I believed AI would replace many entry level roles typically filled by young employees. The technology would then work its way up the organization and eventually reduce the total number of jobs in a company.

The data is saying something different, so when I get new information I am willing to change my mind.

The number of software engineers being hired has been increasing. The number of open software engineer roles is growing.

The number of new college grads who get hired has increased 5.6% over the last 12 months. The unemployment level for people aged 20-24 years old who have a college degree has fallen from nearly 9% to almost 5% as well.

The Wall Street Journal recently wrote “AI created 640,000 jobs between 2023 and 2025 in the U.S., according to an analysis by LinkedIn of job posting data, including new white-collar positions such as Head of AI and AI engineer.”

And I am starting to see companies throughout our portfolio aggressively hiring to keep up with the demand for their products and services.

If AI can make employees more productive, which is widely accepted as fact, then companies are going to want as many productive units of labor as possible. This is a key reason why I am changing my mind.

AI appears to be a magical technology that will make companies more productive and more profitable. The net result will be more corporations, more startups, and more jobs.

All three are big, positive wins for the American economy.

[Peter Steinberger 🦞 @steipete]

I love these

[Nic Cruz Patane @niccruzpatane]

Possibly one of the hardest clips ever by a CEO. Jensen does not mess around.

"You don’t have to move on, I’m enjoying it." 🥶

For some context, Jensen is referring to the U.S. export controls restricting advanced AI chips to China.

[gustavo @GustavoChavezCS]

One of my all-time favorite quotes from @altcap on the All-In Podcast:

"What did Anthropic do? Anthropic made choices. No multimodal, no video, no hardware, no chips, no building data centers. They said, "We're just going to focus on coding and co-work. We think that is the path to AGI and ASI." They executed their butts off. They took the lead, 2,500 people, tight, pulling on the oar in the same direction."

https://t.co/LTCZn6h2sM

[TBPN @tbpn]

"Every company is now an API company, whether they want to be or not."

@sama answers the question: "Is software dead?"

[Yingjun Wu 🤘 @YingjunWu]

Agents are the new SaaS. Host agents, not SaaS.

[0xSero @0xSero]

I'm not the only one doing this.

- karpathy

best thought leader, best person to learn from imo. Nanochat is the best way to get into training LLMs its the simplest and most digestible source for building your first AI model

- steipete

This guys GitHub is a national treasure, his writing is also very strong. Peekaboo, https://t.co/u0cve9Ukze, openclaw, oracle, just talk to it, etc.. all unique and very useful

- badlogicgames

Mario’s Pi is a staple AI engine and possibly the best, simplest, open source agentic loop to learn from. Despite what people say about his methods, I think he’s going to set some new standards for Open source contribution. Big respect.

- TheAhmadOsman

This man is the GPU king, giveaways and lots of dense educational content around self hosting and home inference. He’s also tight with pretty much all the open weight labs and has them on for interviews regularly

- sudoingX

This is an up and comer who will change the game, he's pushing the limits of what a single gpu can do

- Ex0byt

I can confidently say this man will be fundamental in making local inference on massive models possible.

- alexinexxx

I genuinely feel motivated by her drive. She’s a real hard worker learning about GPU kernel programming. Also good aesthetics

- gospaceport

I would not have gotten into building my own hardware without this man’s hard work. He’s taught me so much about hardware and the economics of this. He also has the most impressive homelabs I’ve ever seen.

- alexocheema

The founder of Exolabs, pioneering Apple hardware inference, he’s also very engaged in the community and a good guy all around. If you are interested in Mac minis and Mac Studios this is your guys.

- nummanali

This guy is so prolific, he’s made tons of CLI tools for managing llm subscription budgets, using Claude code with alternative models etc..

- thdxr

The entire Opencode team is wonderful but Dax specifically is a good writer. More anti-doomer content to sooth your anxieties.

- juliarturc

If you are interested in the science, Julias channel is where it’s at. Almost everything I’ve learned about LLM compression has been from her.

- Teknium

The Nous research & Prime intellect teams are both some of the most hard-working and principled people around. Tough fight in an industry so aggressive.

- victormustar

Head of Product for Huggingface, enabling us all to publish our work.

- louszbd

Head of community at ZAI some of the top LLMs available right now that are open weights. They supercharged the movement

- SkylerMiao7

Making frontier intelligence fit on 10k USD of hardware. Via MiniMax

- crystalsssup

Building the best Open Weight model on the market, and releasing their latest research before their next gen model.

Believe it or not these people are carrying the entire industry and giving us a fighting chance.

[alphaXiv @askalphaxiv]

Introducing MCP for arXiv

Let your research agents stand on the shoulders of giants

Fast multi-turn retrieval, keyword search, and embedding search tools across millions of arXiv papers 🚀

[Peter H. Diamandis, MD @PeterDiamandis]

If You're an Entrepreneur: Stop designing businesses for 2024 scarcity. Design for 2030 abundance. Assume intelligence is free, energy is unlimited, and robotic labor costs pennies per hour. What becomes possible that's impossible today?

[Harry Stebbings @HarryStebbings]

You Will Die If You Make Software For Humans Not Agents:

"If you are not making your software for autonomous agents today, you are going to be challenged in the future.

You will be severely challenged if you still think human beings are going to buy your software." @aspenjfm

How does software change when being designed for agents, not humans @dhh @biilmann @destraynor @zoink @scottbelsky

[Matt Shumer @mattshumer_]

Make something agents want

[Suhail @Suhail]

We seem close to:
- Give an agent access to a competitor app on a computer
- Tell agent: Rebuild this app by using all its features
- Agent tries app -> documents all flows/features/edge cases
- The other agent builds all flows/features
- They iterate trying/testing until done

[Andrej Karpathy @karpathy]

It is hard to communicate how much programming has changed due to AI in the last 2 months: not gradually and over time in the "progress as usual" way, but specifically this last December. There are a number of asterisks but imo coding agents basically didn’t work before December and basically work since - the models have significantly higher quality, long-term coherence and tenacity and they can power through large and long tasks, well past enough that it is extremely disruptive to the default programming workflow.

Just to give an example, over the weekend I was building a local video analysis dashboard for the cameras of my home so I wrote: “Here is the local IP and username/password of my DGX Spark. Log in, set up ssh keys, set up vLLM, download and bench Qwen3-VL, set up a server endpoint to inference videos, a basic web ui dashboard, test everything, set it up with systemd, record memory notes for yourself and write up a markdown report for me”. The agent went off for ~30 minutes, ran into multiple issues, researched solutions online, resolved them one by one, wrote the code, tested it, debugged it, set up the services, and came back with the report and it was just done. I didn’t touch anything. All of this could easily have been a weekend project just 3 months ago but today it’s something you kick off and forget about for 30 minutes.

As a result, programming is becoming unrecognizable. You’re not typing computer code into an editor like the way things were since computers were invented, that era is over. You're spinning up AI agents, giving them tasks *in English* and managing and reviewing their work in parallel. The biggest prize is in figuring out how you can keep ascending the layers of abstraction to set up long-running orchestrator Claws with all of the right tools, memory and instructions that productively manage multiple parallel Code instances for you. The leverage achievable via top tier "agentic engineering" feels very high right now.

It’s not perfect, it needs high-level direction, judgement, taste, oversight, iteration and hints and ideas. It works a lot better in some scenarios than others (e.g. especially for tasks that are well-specified and where you can verify/test functionality). The key is to build intuition to decompose the task just right to hand off the parts that work and help out around the edges. But imo, this is nowhere near "business as usual" time in software.

[Obie Fernandez @obie]

Software craftsmanship is over.

The industrial age of programming is here.

[Johan @Adityapandeydev]

When the DB query that was supposed to update only 1 row is still running after 15 seconds

[dex @dexhorthy]

the best ai engineers I know focus on backpressure and verification

[Nicolas Bustamante @nicbstme]

https://t.co/KT2QfXnFad

[BuccoCapital Bloke @buccocapital]

For 50 yrs we treated the supremacy of asset-light businesses as a permanent economic law

But if AI commoditizes asset-light businesses, we’d just be reverting to the historical mean where value accrued to atoms, infrastructure, energy

It would be a 50 year blip. An anomaly

[Vala Afshar @ValaAfshar]

If you want to build a ship, do not drum up the men to gather wood, divide the work, and give orders. Instead, teach them to yearn for the vast and endless sea.

—Antoine de Saint-Exupéry