🐢 **接纳自身节奏，摆脱速度焦虑**：作者在高度强调效率的理性主义社群中，曾因无法达到“更快”的标准而感到焦虑和自我怀疑。通过与女友的相处以及反思，作者认识到自己更适合“慢”的节奏，如同“乌龟而非兔子”。这种自我认知转变是摆脱无效内耗、以更健康心态面对学习和挑战的关键第一步。

📚 **深度理解重于技巧，耐心是关键**：文章指出，在大学阶段，作者因追求考试速度而屡屡失利，即使努力也仅能勉强及格。而更深层次的理解和对课程外的知识探索，才是真正有益且能“保护灵魂”的策略。作者强调，在实际应用和选择真正有用的技能方面，耐心和深度思考远比速度更重要，尤其是在学术和研究领域。

💡 **从他人经验中学习耐心与包容**：作者通过观察朋友在遇到学习瓶颈时，能够给自己积极的心理暗示，并认识到“不必一次性解决所有问题”，从中获得了启发。这种对他人的耐心和对自己学习过程的包容，帮助作者敢于 tackling 挑战性的问题，不再害怕失败，而是将其视为探索的一部分，这与Gwern和研究量子力学的视频中的耐心学习者所展现的精神一致。

⏳ **长远视角与持续耕耘**：借鉴Gwern关于“长内容”的理念，作者认识到许多博客文章是“快”的产物，而真正有价值的内容往往是“慢”的、持续耕耘的成果。这种“长远”的视角，鼓励人们去 tackling 那些庞大或繁琐的项目，通过长期的信息收集和知识积累，即使是普通人也能展现出非凡的洞察力。这是一种对抗拖延、拥抱过程的有效方式。

Published on October 10, 2025 12:10 PM GMT

Epistamic status: Journal

One thing I love about the rationality community is the munchkinism and aiming for really high standards. Don't just arrive at the truth, but arrive at the truth as fast as possible. Cheating is technique. How could I have thought that faster?. Do hard things and do them quickly. I think I found all of this advice valuable, but sometimes, especially in written content, an implicit assumption got implanted in myself that I was failing when I wasn't perceiving myself on a minute-to-minute or hour-to-hour basis as being able to do more well than say my fellow students when it comes to, implementing some algorithmic problem. I would then often feel anxious, and then learning new things would be even harder and also it wouldn't be any fun.

This hurt my self-esteem in university in a counterproductive way when I kept barely passing exams even though I was trying my best. In high school, I got by well, because the math material was just too trivial and I would often have self-studied a lot of the material anyway through Khan Academy. In exams I would be done half an hour early and would be able to go through all of my work again to fix all the embarrassing mistakes I made. And even when it came to writing, I would just practice and get more marks than my peers even if my essay would be half the expected length.

In university I would just barely pass exams because I wasn't fast enough. Whenever I would study with other people before the exam I would notice how people who had a worse understanding before the exam and whom I would explain concepts to would score more well than I did in the exam. I had gone into uni already having read How to Become a Straight-A Student, but all the advice there or elsewhere was no help^[1]. I assumed it must have mostly to do with me getting too stressed in exams and then not being able to read fast enough. Or with other students goodharting old exams more than me. The critical voices in my head would tell me though that this was a cope and I was just not as smart as I thought I was.

After meeting my girlfriend I noticed the critical voice in my head was right, just not quite in the way I expected. My girlfriend is very fast. She reads at 1.5x my speed and waits impatiently while I am taking 3 seconds to parse her questions (she just commented on that while I was writing this post and she was asking me to hand her something) and has mostly given up on delegating tasks to me in the kitchen, since I am just too slow at cutting onions.

I had gotten that onion critique before, but I think living with my girlfriend finally made me realize that I just run at a different clock speed at most tasks. I am a tortoise not a hare. Who knows maybe I am just the equivalent of choline deficient (though I checked that particular hypothesis) and this is ultimately fixable? I haven't found the fix so far and I think there might not be one.

So my new explanation is that I am just slow compared to the median computer science student. On the take-home math assignments I do better than the median students, because they go for more shallow understanding than me, perhaps there is even a tradeoff, where more of my thinking is just naturally invested in reflecting on what I am currently doing which is just slow. I sometimes appear fast because I have thought about a question deeply before and have an answer cached. In exams, I get cooked. I was trying to force myself to go at a speed that I would be able to solve all the questions and would innevitably make too many errors. I don't have any useful advice here for my past self here. Other than to be more patient. Slow is smooth, smooth is fast Going through more textbooks outside of my curriculum instead of goodharting even more on exams was in fact the correct soul-preserving strategy. It also explains why I write slowly, although I am also generally terse^[2] since I like the aesthetic.

The great thing is outside university nobody cares about how fast I can apply the gauss algorithm. It's just important that I know when to use it. Learning and being fast is way less important than prioritizing general skills actually applying what you learn and learning which skills are actually useful under what circumstance. In life generally, but also in learning and research, patience is important.

The way I finally noticed this error was by seeing enough people who I respect being patient with themselves. For example when I was mentally assisting my friend who was trying to understand language, I noticed that after he had been going into a few dead ends for around 30 minutes without really getting traction anywhere, he just mentally gave himself a pat on the back for diving into some confusions and also was noting some traces that seemed worth perhaps following up on some time. You don't have to crack the nut in one go. Now I do dare to tackle challenging problems like this for 5 minutes, but I noticed implicitly I had developed some fear of tackling problems as hard as my friends problem, because I would anticipate seeing myself failing.

Gwern is one of my favorite patient writers (This entire section on his long content writing is inspiring):

I have read blogs for many years and most blog posts are the triumph of the hare over the tortoise. They are meant to be read by a few people on a weekday in 2004 and never again, and are quickly abandoned—and perhaps as Assange says, not a moment too soon. (But isn’t that sad? Isn’t it a terrible ROI for one’s time?) On the other hand, the best blogs always seem to be building something: they are rough drafts—works in progress. So I did not wish to write a blog. Then what? More than just “evergreen content”, what would constitute Long Content as opposed to the existing culture of Short Content? How does one live in a Long Now sort of way?My answer is that one uses such a framework to work on projects that are too big to work on normally or too tedious. (Conscientiousness is often lacking online or in volunteer communities and many useful things go undone.) Knowing your site will survive for decades to come gives you the mental wherewithal to tackle long-term tasks like gathering information for years, and such persistence can be useful—if one holds onto every glimmer of genius for years, then even the dullest person may look a bit like a genius himself⁠. (Even experienced professionals can only write at their peak for a few hours a day—usually first thing in the morning⁠, it seems.) Half the challenge of fighting procrastination is the ⁠pain of starting⁠—I find when I actually get ⁠into the swing⁠ of working on even dull tasks, it’s not so bad. So this suggests a solution: never start. Merely have perpetual drafts, which one tweaks from time to time. And the rest takes care of itself.

When I looked at this video of this guy studying quantum mechanics, notice how he is extremely patient with himself.

prototype I've made that'll let us look at this book while I use this unusual practice the general idea and what I'm1:15going for here is that like we're going to be reading some Quantum Computing sorry quantum mechanics stuff this will1:21be cold for me and I anticipate this will be difficult for me I last studied1:27quantum mechanics 16 years ago I looked at it briefly during my collaboration1:33with Michael Nielsen a couple years back when we were working on Quantum Computing but like to be clear he was the expert there so this is cold for me1:39I read the preface where uh Griffiths talks about linear algebra requirements1:46and those are also about 17 years out of date so we'll see how this goes I think it's gonna be hard and because I think1:52it's going to be hard I think I'm going to need help um so I'm going to lean on various tools for help I'll lean on uh gpt4 if that2:00seems useful but but mostly I think what's going to be hard is like there's just going to be a lot of new stuff2:06uh very rapidly getting thrown at me and I need to internalize this stuff and one2:11way to do that is by doing a bunch of practice problems and we're going to do a little bit of that assuming that we we get there2:17um but uh in order to have uh a decent experience during those practice problems in order to make good use of2:22time I also need to just have internalized the core terms The Core Concepts the ways that they relate to2:28each other the properties of things notations there's a lot of notation in this book I can see already just by2:34glancing at it um and I don't want to be in a position where like I'm looking at these these problems uh and trying to just like2:39figure out what does this what does this variable mean so anyway we're going to be using this memory system stuff as I2:45go uh and and the idea is that I'm going to be writing little tasks for myself as we2:51read that try to transform the knowledge in the book into tasks that make me2:57retrieve or use or do something with that knowledge so that I internalize it more effectively and I'll I will3:04practice those tasks as I read to make sure before I go too far a few pages3:09Beyond a new idea that I have indeed internalized it but I'll also be curing3:15these tasks with me in subsequent weeks so that ideally you know if we talk about the content of this chapter in a month um I will still be able to talk3:23about it confidently and that is like not my experience well when I started quantum mechanics 17 years ago I think