{
  "video_id": "reddit_1wgii3h",
  "channel_slug": "LocalLLaMA",
  "channel_handle": "r/LocalLLaMA",
  "title": "DeepSeek engineer relections on RSI - burying my talent to yesterday",
  "url": "https://www.reddit.com/r/LocalLLaMA/comments/1wgii3h/deepseek_engineer_relections_on_rsi_burying_my/",
  "external_url": null,
  "upload_date": "20260914",
  "published_at": "2026-09-14T22:38:42+00:00",
  "transcript": "Note - This is translated from the actual blog link right at the bottom.\n\nA few days ago, DeepSeek v4.1 was released. It raised the ability of small models to a new level.  \nAI is improving much faster than anyone expected. From the first ChatGPT that could only chat simply with a few thousand tokens of context, to models with real reasoning like OpenAI o1, DeepSeek R1, and Kimi K1.5 Thinking — that only took about two years. From reasoning models to agents that can smoothly use tools, run commands, and finish complex tasks — that took only about a year and a half. It’s hard to imagine what AI will be like in one, two, or three more years. How powerful will it be? Will it already be able to improve itself and deeply enter areas like embodied intelligence?  \nAI is getting better and better at writing operators  \nIn the field I work in — designing and writing operators — AI has also improved very quickly. In just one year, it went from a small helper that could look up documents, read code, and find bugs, to an expert that can independently read CUDA, PTX, and SASS code, use professional tools to analyze the stall time of every instruction, and then optimize operators by itself. I believe that soon it will also be able to design operator schedules on its own, evaluate different schedules, implement them, and optimize them.  \nOf course I am proud of DeepSeek v4.1’s success — after all, its main Attention operator was written by me \\[1\\]. Its good performance is partly a recognition of my work. But the times keep moving forward, and technology cannot be stopped. I know clearly that in half a year or one year, the operators written by AI will most likely be as good as mine, or even better. AI can think 300 tokens in one second, type a command in half a second, and finish a piece of code in twenty seconds. I cannot. AI can keep improving in model depth, thinking strength, tool use (how often it interacts with the environment), and even parallelism. I cannot.  \nHumans have never hesitated when it comes to destroying themselves. Why do I still work hard to optimize operators, even though I know that the better my operators are, the faster our new models will train and run, the faster model ability will improve, and the sooner I will be replaced? One reason is that writing operators feels like playing a game to me. It gives me a lot of joy. When I invent a new technique or see the performance of my operator go up, I feel as excited as a speedrunner who breaks their own record. And when I see that my operator is much better than the official ones from the vendors, I feel very proud. But a more important reason is this: even if I give up or deliberately slow things down, other companies’ models will still keep improving and will replace me anyway. “Of course I hope I won’t be revolutionized. But if it has to happen, I hope the person who revolutionizes me is myself.” When everyone is so determined to destroy themselves, I have no choice but to join this cruel arms race.  \nWhat about me?  \nWhen the day comes that AI writes operators better than I do, what will happen to me?  \nMy judgment is: I probably won’t lose my job completely, but I will have to change careers. I can still keep a job, but I may never again be able to do the work I once loved.  \nI once made a judgment about the changing times and my own future: because things are changing so fast (the AI progress above is a good example), I cannot predict what will happen in five or ten years. But no matter what, I believe that with my vision, judgment, initiative, and intelligence, I can stay in the game and stand at the front of the times again. However, this judgment only guarantees that I won’t become unemployed. It does not guarantee that I won’t need to change careers. In fact, it encourages me to change careers in order to avoid unemployment.  \nWhat does changing careers mean? It means I have to give up the field of operator design, writing, and optimization that I have worked in for a long time and loved deeply, and instead become a “mecha pilot” for Agents. Before, my interests, what I was good at, and what industry needed were basically aligned. Now, AI has made what I am good at into something it is even better at, and industry demand has shifted from “people who can write high-performance operators” to “people who can use AI to produce high-performance operators faster.” To meet industry needs, I will have to leave the direction I loved and move to an unknown new direction. I believe that with my understanding of engineering, upper-level model needs, and lower-level hardware, I can still produce operators with high quality and high efficiency. I also know I might come to love this new direction (or I might not). But the feeling of having my passion taken away is really not nice. That quiet joy of sitting at my desk and calmly writing operators for a whole afternoon may become a final song this summer. I have to bury my talent in yesterday and become a mecha pilot. My hands hold more gears, but my heart has fewer rhythms.  \nHere is a simple comparison: You are an expert at knitting sweaters. You are especially good at creating patterns and matching colors. The sweaters you make are high quality and beautiful, so rich people from near and far ask you to knit for them, and you make good money. At the same time, you really enjoy sitting by the window with a cup of tea, looking at the green mountains, water, cows, sheep, and cooking smoke, and quietly knitting for a whole afternoon. But one day someone invents a magical machine. You only need to give it yarn and a pattern, and it automatically knits a sweater. The quality and texture are as good as yours, and it is much faster. You know that your colleagues can easily reach your old level with this machine, so you have to use it too. You also know that with the knitting skills you built over twenty years, even when everyone has the machine, your speed and quality can still be better than others. But that feeling of listening to the rain by the window, slowly pulling the needle and thread, and enjoying the quiet time is crushed by the noise of the machine.  \nI know this is helpless, but there is no other way. I can keep my job, but my old passion will most likely have to be given up. I am a person whose rational side and emotional side are quite separate. When I need to be rational, I can be very rational, but sometimes I also show my emotional side. I remember when I moved out of the rental apartment I had lived in for a year, I cried a lot because I didn’t want to say goodbye to the memories. Saying goodbye today to the era of hand-writing operators and optimizing them with the human brain is even more cruel.  \nI don’t know if any readers feel the same way, but I think this is just how things are.  \nWhat about people?  \nWhile AI keeps improving, I also worry about some questions:  \nWill students now be much more likely to use AI to finish homework, especially practical labs? Imagine there are two choices: one is to spend eight hard hours finishing a lab and maybe not even get full marks; the other is to start an AI model, spend a few cents and a few minutes, and let AI write full-mark code. Which one will most students choose?  \nThe point above will cause many students to have seriously weak engineering skills — things like organizing code, building systems, thinking about future needs and designing for them in advance, and abstraction ability. As AI keeps getting stronger, are these engineering skills still necessary? Will they be abandoned by the times like the old skill of “writing x86 assembly fluently,” or will they always be valuable like the ability to “understand the whole computer system from software to system to hardware”? If it is the latter, then it is dangerous — a person with poor engineering skills, when paired with AI, can produce messy code several times faster than before, planting all kinds of problems in systems and making the world more of a “clown stage.”  \nIn future society, will power become more important than technology or intelligence?  \nThese questions may need to be answered by the times themselves.  \nConclusion  \nWith the development of AI, future society may move toward two extremes: communism or Cyberpunk 2077. In the first, productivity is greatly liberated and people’s living standards improve a lot (I’ll stop here so I can pass review). In the second, a few tech companies control most resources. Only a very small number of people can use the most advanced AI and technologies and get close to “mechanical ascension.” Most people can only use very weak AI. Crossing social classes will become harder and harder: you need the strongest AI first in order to cross classes, which creates a dead loop.  \nGuess what: if Anthropic forever holds the most advanced AI in the world, will future society become communism or 2077? You guess?  \nSo I still believe that the most advanced intelligence should be provided to everyone in an open and cheap way. I do not trust that Anthropic or OpenAI will do this. Especially, I do not want Anthropic to hold the most advanced artificial intelligence or AGI. To put it strongly, that would be as serious as letting Hitler get atomic bomb technology before the Allies. That is why I chose and continue to stay at DeepSeek: we research powerful, fast, and widely beneficial artificial intelligence and open-source it. Maybe this can pull the world a little bit back from the 2077 side.  \nMay the future world be well. May all the beauty be blessed.  \n\\[1\\] “Main Attention” only includes the MQA attention with head dim = 512. It does not include the indexer used to select the top-k important tokens. That part was written by other (also very strong) colleagues (and their AI Agents).​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​\n\nhttps://mp.weixin.qq.com/s/zk0KxuLzhmMJ4LPYW\\_OHMA\n\n\n\n--- Top Comments ---\n\n\n[39 upvotes] I feel the same as him. I've been a professional software engineer for 20 years next year, and have been programming my entire life even prior to that. The only constant is change, but this change does feel bigger and scarier. \n\nOnly thing that's been surprising is how easy its been to still stay on top of said change and be better at using it than most of my coworkers. I figure that will let me survive for a while longer in this industry. I'm trying to pay off my house before it all blows up\n\n[40 upvotes] In case anyone wants an easier read. I thinks he has many interesting points.\n\nKinda funny that AI engineers (talking about kernel and maths stuffs, not prompt engineering) training AI for their work, and they get replaced first. I remember one of minimax M3 show off was having the model optimising come CUDA stuffs on its own. \n\n\nThe post covers:\n\n1. **The acceleration** — AI went from basic chat to reasoning models in ~2 years, agents in another ~1.5 years. The engineer notes that in their field (writing CUDA/PTX/SASS operators), AI has gone from helper to writing better code than humans in under a year.\n\n2. **The personal conflict** — They wrote the main Attention operator for DeepSeek v4.1. They know AI will surpass them in 6–12 months. They stay in the race anyway because the work feels like a game to them, and because stopping wouldn't save them — everyone is racing ahead anyway.\n\n3. **The career pivot** — They accept they'll need to move from \"writing operators\" to \"piloting AI agents\" that do it. Same industry, different role. But they grieve the loss: the quiet afternoon joy of hands-on craftsmanship is gone.\n\n4. **The sweater metaphor** — Knitting by hand was fulfilling; t\n\n[19 upvotes] Its so interesting to hear this from Chinas side\n\nAnthropic and OpenAI are all like if we don’t build it, an authoritarian government like China can build and control it\n\nAnd this guy is like if China doesn’t build it, OpenAI or Anthropic will and it will be controlled by corporations and they won’t share the benefits properly across society. Fascinating and honestly I hear where he’s coming from",
  "transcript_chars": 12082,
  "ingested_at": "2026-09-15T01:30:03.094959+00:00",
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    "author": "WebAssemblyMan",
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