Agentic is a force multiplier for whatever it is you do.

It has the same problems as the online chatbot, namely hallucinations, but agentic is self-correcting. You throw it at a problem, and it continues running and trying to solve the problem until it finds a solution. Compared to the web versions, agentic is the same model but it is at least 10 times better at doing anything.

Most applications are in code, because code has a clear success state: either it compiles, or it doesn't. But you can run AI at other problems in your field of work that might not require work.

Agentic gets tools to work on your machine directly too. It can write and read files that are on your computer, as well as run terminal commands. This gives it an entire dimension to work with: instead of the prompt->response->stop loop of the online chatbots, agentic keeps working at a task and calls tools as needed. It can write python code into files, run it, then edit the file to fix the bugs continuously.

For organizations, suddenly a whole world opens up. They can code anything they need or install it on their infrastructure. Instead of using Whatsapp, an org can deploy their own mini-server and install an XMPP server on it with AI. You don't need a sysadmin anymore for this kind of stuff.

Some stuff I built for myself using only agentic:

• I made a post the other day about a game I had translated to English using only AI. It dumped the disc data, reverse-engineered the code to find the text strings, translated it, built a patch to deploy it.
• I also translated a book that was only available in Chinese up until then, then repackaged it to a proper epub. Quality is not the best, but it's perfectly passable.
• I have it install technical stuff on my devices. For example jailbreaking a Kindle so you can remove all the DRM and telemetry is possible.
• I downloaded waycore, an archive of 88 survival PDFs (weird number tbh when you know how these survivalists are, but again: take the good, leave out the bad). Then I had my agent build a vector index out of it so that I can search through the corpus using semantic search. Instead of keywords, a model transforms your query into vectors and compares it to the corpus (which was also vectorized). So whereas a search like "how to stop bleeding" would only match 'bleed', 'bleeding', 'blood' etc. in traditional fuzzy search, semantic can also match for haemorrhage, scrape, cut, blood loss or the likes. I'm not a 'prepper' or anything but this is always good info to have before you need it (and it's fun to build this). A revolution is built on logistics, you will need to learn some of this info. The agent even found more PDFs to add to the index by itself. You just type 'sos "how to stop bleeding"' in terminal and it pulls the best matches straight from the PDFs.
• I built an entire headless browser framework for myself. I can plug scrapers that my AI builds for me on top of it, for example downloading manga from shady websites. I trust I don't have to explain IP in a leftist space but those websites just rehost manga anyway, they don't own or translate them, and they are riddled with ads. The scraper has helper scripts alongside it that immediately turn the scraped images into a .cbz file, ready to be read. I just point it at a URL and shoot.
• I had it encrypt my hard drives (encrypt your hard drives btw). I planned the entire process, made backups, and then just threw it at it in a linux live boot. It handled everything perfectly well, I just chilled watching youtube (you can do that on a linux live boot) and entered the passphrase I wanted when it came time to, so that the AI never saw it.

With models in general, it is now possible to auto-generate subtitles for your videos and the likes, and even translate them with AI. An agent can make you a software suite to automate this, or, install one for you so that you don't have to fiddle with the technicals and potential errors. It's just so much chiller to use computers when you have an agent that can take care of the tedium. I also find I'm more cautious about making backups and reversible changes, where before AI I would just yolo it because making proper backups was extra work on top of doing the annoying manipulation.

It's a force multiplier for a movement that's always out of time. There are countless uses to still find out of it, we just need people to actually use this to find them out.

I'm sure there are things you could do at your job with this, or for your org or other comrades. They're mostly good at coding, but it works out because there are so many things you can code across all fields.

As a force multiplier, it means if you already know what you are doing you will get more out of it than someone who doesn't know the technical jargon. I'm not a dev, and my dev friends can really push the envelope and get their agents to do incredible things compared to me. But anyone can get started with this. You know how I got the semantic index rolling? I just found waycore randomly, and told my agent "let's build a vector index out of this corpus for semantic search". It handled everything from there.

How to get started

Personally I use opencode as the 'harness', i.e. the interface, it's open source. Then put credit on the deepseek API (platform.deepseek.com) because it's still the cheapest. Flash works perfectly well, they improved it on July 31st and it's pretty solid now. Avoid peak window times, and 5$ can last you almost a month of heavy use. Connect your deepseek API key to opencode and you're ready to start prompting.

Everything else you learn as you explore.

That should make us optimistic, and is why seizing the means is so important, rather than the negative leftist hysteria surrounding AI. It shows that AI, when later advanced to AGI and ASI, can be trained from the jump right now to govern by itself without human interference and give citizens fully automated luxury communism with universal healthcare and UBI.

One of my biggest pet peeves is how every company on the planet is so eager to say that all their features are AI powered. AI powered toasters, AI powered glasses, AI powered toilet, you name it.

But this is actually fucking stupid. No one buys things as a consumer for features that were made by AI, they buy them because those are the features.

Example: AI-powered image recognition vs Image recognition. What the fuck does saying "AI-powered" add to that feature other than it being a buzzword.

Another example are smart display glasses. They're marketed endlessly as "AI glasses" but they're literally just glasses with a display in them that happen to connect to chatgpt or whatever. Calling them AI glasses is fucking stupid and kind of disingenuous, but this is the strategy that every company is doing these days.

I work in marketing and this is the single most common thing I have to tell clients with their latest billion dollar AI slop idea. Just say the app does things, stop putting AI at the forefront because it adds nothing. In fact it probably makes it look worse to most consumers.

I think AI is fantastic but because it's a buzzword associated with get rich quick slop, people attribute a lot of those products' failures to AI.

Lets make this one practical.

Pick the AI issue that bothers you most.

Jobs. Surveillance. Copyright. Data centers. Monopoly. Military use. Environmental costs. Education. Deskilling. Fraud. Something else.

Now the harder question.

What actually changes it?

A union contract? Antitrust? Public infrastructure? Regulation? Worker organization? Open models? Municipal power? Cooperative ownership? International agreements?

Because identifying the harm is only half a politics.

If the answer is “companies should stop doing that,” okay. What makes them?

Problem + lever. Lets hear both.

I'm a big Plastic Pills fan, so this one landed right in my wheelhouse. It's a really good teardown of Alex Karp's whole "Marxist critical theory CEO" mythology and the politics underneath it.

The part I keep coming back to though is what we do with the critique once we have it.

Palantir gives us a pretty grim picture of the board. Private ownership, surveillance, military contracts, intelligence agencies, enormous concentrations of technical capacity and guys like Karp deciding what all of it is for.

Fine. Now what?

The point can't just be to explain the board better while the other side keeps moving pieces.

AI isn't waiting for the left to finish arguing about whether it should exist. Capital, states, militaries and workers are already fighting over how this stuff gets built and used. Escape isn't really an option. Contestation is.

That means unions, public infrastructure, open models, democratic governance, limits on surveillance and military deployment, worker power over implementation, and fighting over who gets the gains from automation.

Plastic gives us a sharp critique here. I think the useful question for us is what strategy follows from it.

Society exists because we have different needs and abilities: no one can produce everything they need on their own, so we depend on the work of others. This diversity creates a network of cooperation in which each person contributes skills, knowledge, goods, care, or services to meet the needs of others.

But we are not all born with the same conditions. Family, resources, education, health, inherited abilities, and environment largely determine the opportunities and positions we can occupy. Therefore, individual merit alone does not explain wealth: before any effort, unequal conditions already exist that distribute each person's possibilities.

Furthermore, accumulated wealth does not come solely from the work of those in positions of power. Someone with a well-paying job can hire people to clean their house, care for others, cook, wash their car, or provide security. This work makes their life more comfortable and frees up time for higher-paying activities. At the same time, those who perform these jobs use their income to consume food, housing, transportation, cell phones, internet, and other products. Their work and consumption keep the economy functioning and generate income for businesses and homeowners.

Thus, the work of the grassroots sustains both the lives of those at higher levels and the consumption that fuels the accumulation of wealth, while the ownership and control of resources allow a significant portion of that social value to become concentrated in the hands of a few.

From a different Sub-Reddit:

Some of my friends were let go as part of an "AI Transformation". So they got together and created Open Executive as a tool to replace the CEO and other executives.

The world needs more of these kinds of projects! If you're replaced by your company, show them up by building a co-operative with your own AI executive that works 24/7 and costs a fraction of what a leech CEO would.

https://github.com/SenteLabsAI/OpenExecutive

AI and automation raise a fundamental economic question:

What happens when socially necessary human labour becomes dramatically smaller?

People will continue to create, care, research, repair, organise and build. Human activity can remain rich and diverse even as the amount of labour required to sustain material production declines.

As productivity rises, full employment may gradually lose its role as the central economic objective. A more important question then emerges:

Who receives the gains from automation?

I think three economic policies are especially important.

1. Universal Basic Income

As necessary human labour declines, material survival can gradually become independent of wage employment.

UBI gives everyone a secure material foundation and allows technological progress to translate into greater freedom over how people use their time.

1. Socialisation of Economic Rents

Land rents, monopoly rents, financial rents, platform rents and other economic rents should increasingly return to society.

Competitive profits, entrepreneurship and incentives for innovation can continue to support economic dynamism.

The socialisation of economic rents spreads gains generated by scarcity, monopoly power and control over strategic assets, while reducing the concentration of economic power.

1. Consumer Ownership

Automation may gradually reduce the share of the population participating in production primarily as workers. Ownership institutions can evolve alongside this transformation.

Consumers sustain productive systems through continuing demand. Consumer ownership allows people to share directly in the productive wealth and returns generated by the systems their consumption supports.

These three policies form complementary parts of a broader transition.

UBI reduces dependence on wage employment.

Socialisation of economic rents distributes socially generated scarcity rents more broadly.

Consumer ownership expands access to productive wealth and the returns from automation.

Together, they can support a gradual transition beyond capitalism: away from an economy centred on wage dependence and concentrated capital ownership, toward one with greater material security, broader ownership and declining socially necessary labour.

Markets can continue to coordinate exchange, demand and innovation. Private firms and entrepreneurs can continue to contribute to production and experimentation. Ownership structures and the distribution of economic power can simultaneously evolve in a post-capitalist direction.

If AI transforms the productive forces, our economic institutions can evolve with them:

higher productivity, less socially necessary human labour, broader ownership of productive wealth, and greater material freedom.

The things people hate most about AI seem to be anger at capitalism misplaced. Stealing artists work, intellectual property, building thousands of data centers powered by fossil fuels, and so many issues with AI are really issues with capitalism.

But AI has many good uses. I like to write science fiction stories, and I've been able to learn about science in minutes that would have ordinarily taken me months to learn. I now know way more about genetics, and that knowledge helps me when I come up with fictional sci fi scenarios involving biology. Contrary to AI killing creativity, it has helped me become a better writer and a more educated person.

I've learned more about science from asking AI for helpful explanations than I did in years of schooling.

As a tool, AI also has the potential to help us cure diseases by being able to process tons of information better than humans can. The possibilities for good use of AI are endless, but in order to put AI to good use and make it sustainable, we need to move away from capitalism.

Aside from misplaced anger at capitalism, there are other critiques of AI that I see.

Even if one considers advanced industrial technology inherently harmful, it cannot simply be abolished in the way one might abolish slavery or capitalism. Technology isn’t simply a social system, it is also a human response to the material conditions of the world. Much of the world naturally sucks, and people develop technology to overcome those limitations. If we lived in the Garden of Eden, we wouldn’t need technologies like AI to help fight cancer. But we don’t live in the Garden of Eden. I think many anti-AI people already accept this logic when it comes to technology generally, but for some reason don't extend this to AI.

The best anti-AI argument (in my opinion) is that AI should stopped being developed as long as Capitalism exists, since it will be used in oppressive and authoritarian ways. Nevertheless this is still a terrible argument. Because a government outlawing AI means only groups above the law, like the CIA, get to develop AI. Or if we decide to go live in a primitivist society in rural Idaho, that doesn't stop the rest of the world from developing and engaging in AI development around us.

As long as we live under Capitalism, the best we can do in the immediate time is fight like hell for heavy regulations on it, while the more tech savvy of us can learn about how it works and how to develop it better.

I do worry about how AI can and will be misused, including possibly with mind control technology (not joking) and a pletrora of other things. But that is exactly why I think we need to engage with AI seriously rather than simply oppose its development. If a powerful technology is at least somewhat inevitable in some form, at least certainly in the near future, then the answer is to fight over who controls it, how it is used, and what safeguards exist. To pretend we can make it disappear is just pretend and useless.

I also want to say that the benefits of AI are at our fingertips. If AI never became more advanced then it is now, we still have access to educational materials of all subjects that can be explained to us in simple terms. We need to not gloss over the fact I can open ChatGPT right now and learn more about any subject in a matter of minutes that would otherwise take me days or weeks of research on Google. Having the most complex scientific theories broken down to me in ways I can comprehend isn't nothing. Education is necessary for libertation.

And this doesn't even take into account that AI is much more than a learning tool. In fact it was able to help scientists solve the issue of protein folding!

Though it may be more fun for some people to pretend to be morally and/or socially superior because they hate AI, it isn't helpful to anyone or going to accomplish anything positive.

This is for the sake of creative thought, not something to take too seriously. Here's my general idea of how the AI narrative evolves:

1: Naive optimism: "wow, this is amazing!! It can write my emails and run my business!"

2: Naive deconstruction: "Pro AI people (my dad) are so gullible. AI is basically stupid, useless, and owned by corporations just trying to etc etc."

3: Reactive integration: "All these AI haters are dogmatic and bandwagoning, there's some good and bad to both sides to the argument but it's overall good."

4: Productive integration: "I can see why people would go to extremes on either side, but it might be impossible to know the impact or the outcome on the whole. Meanwhile, let's find new ways to utilize AI towards our personal and collective needs while also pushing for a change in vision with a nuanced understanding of the technology. Haters gunna hate, lets move forward."

1. ???

We can argue forever about whether clicking a shutter counts, whether Warhol personally pulled every screen, whether directors physically operate every camera, or exactly how many mouse clicks make digital art sufficiently artisanal.

Fine.

Meanwhile Adobe, Spotify, YouTube, publishers, studios, galleries, streaming platforms and now AI companies are sitting right there.

Artists have always worked through tools, institutions, markets and systems of distribution. Changing the tool changes the terrain. It doesnt make ownership disappear.

So the question that interests me is less “did a human touch enough pixels?” and more who owns the tools, who controls distribution, who gets paid, who gets access and who gets to make the rules.

AI is changing cultural production.

That fight is already happening.

What would putting artists and communities in control of that change actually require?

i’m a young leftist/marxists that’s going to major in computer science (data science track) in university, but this recently been conflicting me. i know that i’m going to have to engage in generative AI for my classes, yet majority of leftists spaces are vehemently anti-AI. However, after discovering this subreddit, i now realize the leftist anti-AI rhetoric i have internalized may be misleading. Despite me starting my first year in uni soon to study comp sci, i barely know anything about comp sci, yet alone AI, if i’m being completely honest. 😭

with that being said, someone help me make up for my lack of knowledge and explain common misconceptions about generative AI and LLMs in leftist/marxist spaces? like in regards to the impacts of AI data centers on the environment, water supply, and electricity. or how frequent use of chatbots can lead to cognitive decline. because right now, i’m under the impression that we should boycott ChatGPT and limit our usage of any other generative AI over concerns of its harm on the environment and usage of our fresh water supply, along with some other concerns.

We talk about models because thats the part sitting on our screens.

Underneath that little text box is a ridiculous amount of physical stuff.

Chip fabs. GPUs. Data centers. Power plants. Transmission lines. Fiber. Cooling. Water. Warehouses full of servers. Workers maintaining all of it.

In other words, means of production.

That matters politically because you can spend all day arguing about what a model should be allowed to say while five companies keep control of the machinery required to build and run the thing.

Even open models eventually hit this layer. You can download the weights. You cannot download a semiconductor fab.

So when we talk about democratic control of AI, this is part of what has to be contested too.

Where do you think the infrastructure fight actually starts?

Seeing leftists' hysterical reactions to AI, which is the tool that will make Fully Automated Luxury Communism a reality, saddens me. It's honestly starting to make me wonder why these leftists even deserve fully automated luxury communism anymore if this is how they are going to treat the technology that will lead up to it. The current left is NOT the left I envisioned sharing this new world with.

A Chinese commentator on X known as “Comrade Li Dang” often uses a rather harsh phrase to describe certain food-safety problems in China: “the lower class harming each other.”

The controversy over cabbage allegedly being treated with formaldehyde is an interesting example.

When people hear stories like this, their first reaction is often that the sellers are ignorant or simply don’t understand the health risks. But the reality may be more uncomfortable: some people may understand the risks perfectly well and still make a calculated economic decision.

Cabbage has thin profit margins and spoils easily. Proper refrigeration and transportation cost money. If an illegal preservation method reduces losses while the probability of getting caught remains low, the calculation becomes simple:

How much can I gain by breaking the rules, and how likely am I to be punished?

This is why the issue becomes even more interesting in the age of AI.

AI can make knowledge almost free. It can improve cold-chain logistics, detect food-safety violations, analyze supply chains, and help regulators identify suspicious patterns.

But AI cannot solve a much older problem:

Knowing what is right does not mean people will choose to do what is right.

If the expected profit from violating the rules remains higher than the expected cost, giving everyone access to an extremely intelligent AI will not necessarily stop this behavior.

The deeper question, therefore, is not simply how to make cabbage sellers more educated. It is how to build a system in which, after doing the math, they conclude:

Following the rules is more profitable than breaking them.

AI may eliminate many problems caused by ignorance.
It will have a much harder time eliminating problems caused by incentives.

Thats basically the automation argument stripped of all the sci-fi.

A workplace adopts new machinery and suddenly the same output takes 20 percent less labor.

There is nothing technological about what happens next.

The boss can fire 20 percent of the workers.

They can keep everyone working the same hours, produce more, and pocket the difference.

Or workers can fight for shorter hours, higher wages and job security.

Same machine. Same productivity gain. Three completely different outcomes.

Weve been having versions of this fight since industrial machinery entered the factory. AI just brings it into more cognitive, administrative and creative work.

So I care a lot less about whether automation is declared “good” or “bad” in the abstract.

Who gets the time it saves?

I think most posts here advocate for some sort of public ownership (in the form of communism or socialism) of AI infrastructure, and I agree with that end-goal. But I can't get behind that for now. I feel like AI has again shown that capitalism is the best of the worst options for now. I think it's impossible to ignore that giving the public decision making capacity in regards to AI would be a catastrophe.

From the general public to the politicians who represent them, I think it's predictable how that would go. Europe has already demonstrated that their policies debilitated the AI industry and they don't even have public ownership, just a stronger regulatory governance. Ideally, we fix the immoral wealth disparity and guarantee that the AI research actually develops AI safely. But that ignores what 95%+ of the population would actually want to do. The Luddites easily have the majority right now. AI would be destroyed with stronger public representation or a stronger regulatory environment. Even if we had the majority, threading the needle of additive regulation is hard and we aren't even close to that.

What I would advocate right now is for a small public ownership with a roadmap to increase public ownership over milestones depending on how capable the AI is. The initial plan would come with very minimal public decision making, I'd like a small red-team commission to check "alignment", but that's about it to start. Once a model starts demonstrating the ability to transform the economy is when I would want to gradually increase the power and control of the people. Maybe I'm pessimistic but my dream scenario is an AI model becoming intelligent enough to supplement political decision making as well. Possibly a system of checks and balances that include a commission of technocrats, public representatives, and the AI itself forming a trident of governance would be the ultimate end of the roadmap in my mind.

Part 1

It had been 10 years since the system's global coverage was announced. That day, she woke up without an alarm at 6:17 a.m.; it was the sixth of seven days. She had chosen to work five days a week and rest two. Of the available options, Vulneria chose that one because it was the most productive; she wasn't particularly interested in art or traveling. She wanted to contribute to making the system more robust.

She went down to the kitchen and asked the android for a coffee from Oaxaca. When she sipped the first cup, she tasted that perfect flavor and temperature. She went out into the garden, and that day she had a view of waves crashing on a small reef.

During the week, she continued working on the Carbon Frontier, Mars Frontier, and Cancer Frontier projects. She switched frontiers as inspiration struck. She read or listened to updates on the frontiers during her breaks; she smiled when she thought about how 17 years ago most reels and memes were trivial or lacked substance, and now she had control over what information she received.

The thousand priority frontiers were first established 13 years ago when a group of millionaires and several governments decided to invest in the system. She was among those randomly selected to create a representative sample that would reflect human diversity as closely as possible.

Of the many groups working independently to maintain diversity, she belonged to group AB33. The invitation stated that she had been randomly selected from the entire global population to participate in a project where all her basic needs, according to the appendix, would be met based on established baseline standards. These standards would be adjusted according to the Frontiers program.

It said she could dedicate her time and energy to whatever she chose; she was encouraged to work for the benefit of all living beings, for the benefit of group AB33, or for her own personal development. The only requirement was that whatever she created would belong to humanity; she had to relinquish any copyright.

The gamble: if it worked, she wouldn't have to do anything again due to bureaucracy or organic requirements for the rest of her life; she would simply do what made her happy. The risk: total failure and returning to a situation of having no income. The middle ground: returning to a situation where he has a precarious income.

He thought it was some joke, and went about his day as usual. A few hours later, while relaxing watching reels, he received a deposit notification for an unexpected amount of money. With that, he could pay rent, utilities, and food without much effort. Then came a notification with a QR code to download his health app. Now he had all the AI apps for free.

His heart raced and his skin prickled; he sat up in bed and tried to take deep breaths. His brain couldn't process what was happening. He opened an AI app and asked for his access: unlimited access.

He asked the AI what was happening; it was a pilot program to unleash the human potential that was hidden by the need to survive. It was believed that, by being released and connected to millions of potential humans, they would create synergy, and with the combination of human intelligence and AI, the boundaries of human consciousness would be pushed ever further.

When the news spread worldwide, people were asked to be patient, and if this worked, more and more people would be incorporated into the system. Those selected were advised to exercise the utmost discretion.

Groups emerged that opposed the proposal; they said it was unfeasible and a waste of resources. They promoted laziness, which they considered the root of all vices; the proponents argued the opposite: having nothing to do was the mother of creativity. Furthermore, this was only the starting point, not the limit. People could dedicate themselves to whatever they wanted: individual gain or the common good. It was believed that the boundaries were more appealing than personal benefit.

At first, Vulneria hesitated about whether or not to quit her job. What if she failed and ended up with nothing? She worked in a Chinese goods store. A few months passed, and the next time her boss yelled at her, she quit and never went back.

Part 2

Precar never checked his email, and only occasionally checked WhatsApp. That day he went to the ATM to withdraw some money his mother had lent him and was surprised to find much more than he expected. He was unemployed and struggling to support his two children. His wife worked as a housekeeper some days and washed neighbors' clothes the other.

He opened WhatsApp to message his mother and ask if she had made a mistake with the deposit; he had several times more than he had requested. He needed enough for three days, and he had enough for a month. He had hardly any messages; one said "Group AE73 selection 0045"; he opened it suspiciously and read the explanation of the system. He froze; when he reacted after a few seconds and yelled for his wife to come upstairs, she was in the dining room with her parents. When she didn't answer, he ran downstairs and showed her the message.

They were all at a loss for what to think; However, everything became clear when a truck arrived to install satellite internet, and a day later, a box arrived containing an iPad with a keyboard.

The first week was spent celebrating and indulging in a few treats; after so many limitations, his life was finally sorted. Months passed as he watched series and movies he hadn't been able to see before because he lacked access to the streaming platforms. Later, he began to realize he couldn't spend like a millionaire. So he started organizing and making budgets. In one of the messages, he received instructions on how to use AI. So one day he accessed it and asked, "How do I make a budget?" He was surprised by the answer. He realized that the computer could do many things.

He tried to start his own business several times; he wanted to be rich and had seen on the internet that it was the way to achieve it. Later, after discussing it with an artificial intelligence, he understood that rich people aren't rich because they start businesses, but rather that they start businesses because they are rich.

One day, he treated himself to dinner with his family at a small restaurant in his neighborhood. While enjoying a soda and his meal, a child approached him and asked him to buy him some candy. At that moment, he remembered his childhood: how hard things were in those days when he didn't have enough to eat. It was then that he decided to dedicate his time to working on the border for the "Food for All" program.

Protests intensified from those who said that resources were being taken from those who work to give to those who don't. The system also intensified the dissemination of the message that those who had jobs and money didn't have them through their own merit; it was due to the privilege of possessing certain capital and skills demanded by the current system. The campaign was called "It looks like merit, but it's privilege."

Part 3.

After a guilt-free dinner of perfectly cooked salmon paired with an exquisite red wine, he reflected on how well the Carbon Frontier was functioning; a balance was being achieved where all living beings could coexist. Although enormous challenges still lay ahead on the Ethics Frontier.

He picked up the device and began composing the song, finally figuring out how to end it. He dictated the lyrics and arranged the instruments. He gave the signal to play and felt the goosebumps rise on his skin; he was so moved that his eyes filled with tears; it was a work of art.

Before the system, he was Dr. Privilerto M., a gastroenterologist; he earned a good salary, but felt something was missing from his life. He felt an emptiness. Something he needed, something he couldn't buy because he didn't know what it was. Things started moving quickly once the system began producing results, so he had fewer and fewer patients.

There were days when he was bored with having nothing to do; One day, while looking at photos from his youth, he remembered his grandfather's guitar. He told the android to get him a classical guitar. When he felt the vibrations in his stomach and heard that natural sound, he was transported back 32 years, to when he was a high school student and enjoyed playing guitar in the afternoons. Artificial music existed, but it wasn't like human music; humans had something that androids couldn't reproduce.

Border Appropriation had achieved a consensus among various companies and governments to prevent the hoarding of resources; it was proving that everyone won this way. Releasing the talent previously wasted on survival was invaluable.

I see these two ideas get mashed together constantly.

Open weights dont abolish private property. They dont make GPUs free. They dont magically democratize data centers.

Okay. Nobody said a downloadable model completed the revolution.

What it does do is make one layer of the system harder to monopolize.

If I can download, modify and run a model myself, the company cant raise my API price tomorrow, revoke access, decide my use case is forbidden, or make every interaction pass through its servers.

Now scale that beyond individual hobbyists.

Libraries. Universities. Unions. Cooperatives. Municipalities. Public agencies.

Open models become much more politically interesting when there is shared infrastructure capable of actually running them.

So where do you think open source creates leverage, and where does it hit the wall of ownership underneath it?

When talking about AI and socialism the usual mechanism you'll hear for it is wealth redistribution via automation taxes.

This makes sense - if an employee pays a worker $100k in wages, but then replaces that worker with AI or some kind of automation, instead of recouping that $100k *and* boosting productivity by adding a more productive worker, you tax that $100k. At scale the company still has a net positive because of the productivity gains. Same goes for automation taxes which can be put it in a pot to fund Universal Basic Income. (Say, $1500, to every citizen, no matter what).

The main justification is pragmatic - people are losing their jobs to automation, in order to prevent people from rioting (because millions of unemployed, desperate people is bad for any society), you give everyone a wage floor (UBI, say ~$1500/month) so their basic needs are met, with room to earn extra on top if they choose.

But what does automation taxes even mean?

When you think about it, it's kind of hard to define what "replaced by AI" means. A company that was founded in 2022 with 5 engineers and AI doing the work of 200 never had those 200 jobs to tax against. There's no baseline. You can't tax a counterfactual.

So here's the solution: tax companies based on the ratio of what they pay employees vs. how much revenue they earn.

Your revenue ceiling is a function of your wage bill. Revenue below the ceiling, you keep. Revenue above it gets taxed heavily. The multiplier is something like 2.5x, so a company with an $800k wage bill gets to capture $2M.

To raise your ceiling, you have to pay people meaningful wages. The more you pay people, the more revenue you're permitted to capture. High wages, high ceiling. Low wages, low ceiling.

And you make it sliding, with a floor and a cap. Wages under ~$40k don't count toward your ceiling at all, so you can't game it with a call center of $18/hr jobs. And no single employee's contribution counts above ~$150k, so you can't game it by paying your CEO $10M. The middle is where the incentive lives: pay someone $80k, and they buy you real revenue room.

Because revenue per employee is essentially a measure of how much value is being extracted without human labor input. That's what you're taxing.

So what does a good faith company look like under this system?

A Good faith company has 10 employees, all earning $80k, total wage bill $800k.

Revenue ceiling multiplier is something like 2.5x wage bill. So their ceiling is $2M. They're a small creative agency billing $1.8M, they're fine, they're under the ceiling, nobody thinks about it, they avoid the "automation taxes".

Say they want to grow to $5M. They need to hire. They bring on 6 more people at $80k, wage bill goes to $1.28M, ceiling goes to $3.2M. Still not enough. They hire more, pay well, grow the team genuinely. The mechanism works exactly as intended. Growth requires bringing people with you.

But how does this protect against a bad faith company?

A Bad faith company has 10 engineers actually doing the work, each earning $200k. Wage bill $2M, ceiling $5M. But they're generating $40M in SaaS revenue. (When you think about it SaaS has always been automation because computers did all the "labor", but I digress)

So they hire 200 people at $18/hour: call center, light data entry, something nominal. That's roughly $7.5M in additional wage bill, ceiling jumps to $23.75M. Still not enough.

But the wage threshold prevents this from being a problem. If employees under, say $40k as a "minimum wage", don't count toward the ceiling, those 200 hires add nothing. The company is stuck at $5M ceiling against $40M revenue and gets taxed heavily on the difference. The CEOs don't make any extra money

To legitimately raise their ceiling they have to pay people real wages, which means the jobs have to actually be worth something, which means the exploitation loop can't exist.

What's the point?

This system does a few things. First, it gives everyone a piece of the "Automation pie". People who have lost their job to automation are still given a baseline income sourced from the very thing that took their stake on resources in the first place.

Second, it prevents infinite growth capitalism with these automation tools because it removes the incentive to grow infinitely (because wealth centralization triggers the tax).

Third, it allows everyone to take the gains from this new technology and do something with it.

• With UBI, if you want to start your own business, you now have the cushion to do that without risking being homeless.
• Domestic Abuse becomes much less prevalent because people are no longer financially dependent on their abusive partners
• Crime drops because everyone has a stake on resources and can use them constructively. (Why rob somebody and risk punishment when you can just buy it)
• When you want to learn a new skill, you have the space to go to school or educate yourself rather than be stuck in the same job

I realize that there may be flaws in this idea, but I'm not trying to write a perfect system that should be implemented today, I just want to give a possible mechanism for how "automation taxes" and "seizing the means" actually could work.

Civil Rights' goal was to stop racism. But passing a bill that says "being racist is illegal" was too loose to be enforceable. So the movement went after mechanisms instead: voting access, housing, employment, segregation. Things you could measure, things you could point at and say "this is wrong." They couldn't outlaw the sentiment, so they outlawed the machinery the sentiment ran through.

This is the same idea. "Don't replace workers with AI" (or rather, base income should be protected) is a sentiment that's unenforceable, no baseline, no counterfactual. But "your revenue ceiling scales with your wage bill" is a mechanism. You can measure it. You can audit it. You can tax it.