A creative services company for humans, specializing in web design and development, product design, and full-stack & no-code/Webflow development. đŸ€™đŸ»

Atlanta
Joined July 2025
Have you guys gotten a shirt or lid yet? We got plenty in stock and our moms say they're tough and bussin'. righteous-creative.myshopify

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Not sure who needs to hear this but.... An LLM doesn't "understand" anything. It is a statistical model that spews out tokens based on probabilities calculated through massive matrix operations and context, not an understanding of the subject matter.
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Righteous retweeted
The cruelty has been puzzling me. Under almost every post which recounts the anguish of someone seeing AI models becoming shockingly good at their own craft, there is a stream of comments telling the poster to, essentially, accept their own obsolescence. If the poster calls for this development to slow down, the response is to stop standing in the way of progress. If the poster wants to nuance the picture of the machine god steamrolling everything, reply guys call it “cope” and “cringe”. Most recently, this has been happening in mathematics with the field’s shocked reaction to the deluge of AI-generated proofs, but similar dynamics have played out for musicians and visual artists, and to a more limited extent for programmers. These people seem to be cheering for the machines rather than humans. But I don’t think it’s as simple (or as extreme) as anti-human sentiment. The more charitable read is that most of these people really believe that this represents progress. They are excited about scientific and technical progress, and don’t want old farts like professors and other credentialed types to stand in the way. Let’s unleash machine science, and if the professors and intellectuals don’t like it, they can find something else to do! But this is a perverted idea of progress. What good is a proof of the Riemann conjecture if there is no one who understands it? And not just a single person: you need a whole community of people to understand it and then gradually think about what it might lead to. Maybe the result will contribute to a better encryption algorithm, or a better understanding of quasars, or something else. But this requires diffusion of understanding through scientific communities. A proof of the Riemann conjecture by itself is meaningless; to me, or to the vast majority of people out there, it’s just a bunch of symbols that we can’t read. The same thing can be said for other types of research: say, for example, that your AI system deciphers some cellular mechanism that could help with a cure for cancer. A whole network of experts is then needed to do all the complex science and innovation that helps translate this into a cure, test it, and so on. The paper itself would just be collecting digital dust unless the right scientific communities were there to build on it. Now, where do all these experts and their communities come from? From doing research. The only way we know of making people understand the frontiers of a field of knowledge is by trying to advance it, which must come with a real chance of succeeding and being recognized for it. It’s very hard, not to mention boring, to understand the minutiae of some arcane topic if you are not working on producing new knowledge there. If you fully automate the production of results in some discipline, you will also cut off the supply of experts who can understand it. People who have never participated in research may not understand this. If that’s you, try reading a recent paper in a field you know nothing about: category theory perhaps, or carbon nanotube synthesis, or cecidology, or loop quantum gravity. Faced with pages of mysterious scribblings, you can ask Claude or Gemini to explain the paper to you, but then the terms used in the explanations will need to be explained again, and so on. You will find that, in order to actually understand the research and its significance, you will need to understand the whole research field. Then there are those who do understand the role of expertise and the difficulty with which it is cultivated, and still ridicule those who are less than enthusiastic about the AI-driven disruption/destruction of whole research fields. Wherefore? What are they thinking, really? Let us again try the most charitable interpretation. Maybe they believe that we will not need anyone to understand that proof of the Riemann conjecture, because some complex sequence of AI systems will take us all the way from a proof in fundamental mathematics, via all kinds of research, development, and design, to a finished consumer product shipped to your door. This would imply end-to-end automation of much of the economy. I guess some people are really worried that something like this might happen, and therefore want to pre-empt it by acting as if it were already a certainty. This, I think, is the gist of statements like “everything will be AI anyway”, which I’ve seen cropping up with alarming frequency. Submit to the machine god before it arrives, a form of anticipatory grief. Abandoning agency early makes you look like you have situational awareness. “Coping” is uncool. I get it, but cynicism is always the easy choice. It’s also the cowardly choice. Let’s not be cowards. We have agency here; it is a given that technology will advance, but the exact way in which it will advance is down to all of us, and how we adopt this technology in society is something we can and must decide on together. Finally, there are those who have thought all this through, and still welcome the wholesale replacement of human cognitive work. Those for whom it would be a good thing that some sequence of AI systems does all the thinking, so we don’t have to. Who would think this? Well, clearly, someone who doesn’t much enjoy thinking. But I think it’s more than that. I think that there are people for whom the devaluation of expertise would be a good thing. Those who “have had enough of experts”, as Michael Gove said of the British people in the campaign for the Brexit referendum. Those who think these clever know-it-alls should be put in their place. They think people who have spent much of their lives specializing in some narrow topic should not be given all that respect and influence they seem to have now. This is called anti-intellectualism. And that’s where the cruelty comes from. I can’t know what’s going on in their heads, but when I see people telling mathematics professors to go get a real job, as if their jobs would somehow be less real than those of massage therapists, real estate agents, or police officers, I call that anti-intellectualism. Much the same as for people who would rather take health advice from a podcaster than from a medical doctor, or who would happily see a news show host rather than a decorated general in charge of the military. At the extreme end of anti-intellectualism, we have the Cultural Revolution and the Khmer Rouge. I hate anti-intellectualism. I think our society should incentivize people to study hard, think deeply and originally, try to push the boundaries of knowledge, and talk freely about it. I think those who spend their lives specializing in arcane topics should be respected and protected. Yes, it goes without saying, I am an intellectual. A tenured professor even, the worst of the worst from an anti-intellectual’s point of view. So you would expect me to defend the experts and intellectuals. But let me make a non-self-serving argument: humans will always compete. That’s human nature. Would you rather live in a society where the smartest people compete in understanding the mysteries of nature, developing complex technology, and producing beautiful art, or in a society where the smartest humans compete by accumulating money and/or simply by fighting each other? As I have written about before, I am worried. I am not worried that out-of-control AI will kill us all or even that it would put us all out of work. There will always be some kind of work for us. I am worried there will be no place for us in advancing knowledge and understanding the world. I think that the defining question of our time is how to avoid this fate. It’s not a matter of my own job, or yours; it’s a matter of the purpose and dignity of humanity as a whole. Big words, I know, but I think they are warranted, and I don’t care if the cynics call it cringe. So next time you see someone complaining that AI is steamrolling their field of expertise, don’t join in the heckling choir. Don’t be cruel. And don’t assume that someone who has devoted their life, or at least their career, to furthering knowledge wants to stand in the way of progress. Instead, try thinking constructively about how we can work together to ensure that human experts and intellectuals can float on top of the AI wave rather than be drowned by it. Do we have a deal? Alright, thank you! Now I will go back to thinking and working on AI, meaning artificial intelligence, not anti-intellectualism.
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I've been so AI pilled, that I've done a complete 180. AI is a money incinerator. It's a collective hallucination. Everyone sees everyone else shoveling money into the incinerator and starts doing the same. Everyone just keeps shoveling money hoping that one day the engine starts running. And maybe it will. But it isn’t. AI is expensive. Especially when you have to actually pay for tokens. And the real systemic work, the stuff that replaces people because it is autonomous, runs on tokens. The question isn’t whether your AI systems are cheaper than Americans. It’s whether they’re cheaper than people in Latam, Southeast Asia, or Africa. They aren’t. AI also suffers from broken clock syndrome. When we task AI with doing a specific task, it can often give a quality or correct output. But the problems arise when we ask an AI to produce that type of output with different inputs. If you don't know the process it used to give you the initial correct output, there's no way to know if it can take your input type and generate a quality output repeatedly or if it is just a broken clock that happened to be right. So in order to build durable results with AI, you need to build the process the AI is going to use to generate the output. You need to build in oversight. And the more varied the inputs, the more complex the output, the more granularly you need to control the functions within the black box. Otherwise, your fail rate is going to be high. And this failure rate increases whenever there is nested processing and thinking. Then there is the cost of building these systems in the first place. If you actually want something that works, you need to invest considerable resources into the build. Senior talent to develop it, token costs during calibration, ongoing maintenance when it breaks, etc. The common argument against this is to “let AI do the building on its own.” The problem with this is AI doesn’t think. It doesn’t reason. It guesses the next most likely thing in a series. So it will build something for you that will look like a house, but you go in the basement and the foundation is upside down. It’s got wires running through water pipes. The hot and cold water taps are reversed. It looks right from a distance, but any deeper level of scrutiny the illusion falls apart. Nobody is making money from the “work” that AI is doing. If they were, we would have such a rapid consolidation of wealth nobody would know what is happening. Every industry would be consolidated overnight into unassailable monopolies. I hear from lots of people who say they are making money from using AI. And my question to them is how much did it cost to build and what’s the payback period. Large companies are pulling back on AI investment. These are the companies that should be most able to realize a positive ROI on AI. So the question is whether they are uniquely incompetent at development and deployment or are smaller businesses bad at calculating cost and ROI? This results in our current environment: The only people making money in AI are the people who are selling it. It remains to be seen when using AI is profitable and how much work it can profitably replace.
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We won a @TheWebbyAwards ! Thanks to all y'all who have supported us and a huge congrats to the other nominees. 🏆
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We built the web presence for a fintech startup rewiring how $150T in cross-border payments actually moves. Tolken is building a network that matches banks, fintechs, and PSPs in real time across every corridor. No pre-funding. No new licenses. One integration. Check it out: tolken.co The challenge: make infrastructure that connects global financial systems feel approachable on a screen. Solution: Dark palette. Engaging motion. Dense product information that still reads clean. Two-sided storytelling for senders and providers without making either feel like an afterthought.
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Righteous retweeted
Replying to @HeyRighteous
@HeyRighteous made the The Webby Awards. Currently sitting at #4. Trying to move that up. Vote → wbby.co/57650N đŸ™đŸ»
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Great work doesn’t need a committee. It needs a crew that knows what they’re doing. That’s Righteous. righteouscreative.com
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No fluff. No layers. Just execution. AI in the right hands. Strategy that moves. We’re live: righteouscreative.com #righteouscreative #ux #webdesign #creativecollective #ai
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