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Team Grasp retweeted
Edit your future self #personalcurriculum
You create a learning plan when you know least about the subject. Two lessons in, you find you already know half of it. Or the module assumes something you never properly learned. ✨You can now edit your paths✨ Open the path, go to the chat, say what you want to change: "drop the SQL joins lesson, I use them daily" "I don't understand closures, add something before this" "go deeper on indexing" Review and approve. Keep learning. Editing is free. Credits are only spent when you create a lesson.
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Team Grasp retweeted
The post by @venkyganesan inspired me to build a 10 hour course with @graspdotstudy on Contrarian VC Investing. A bit theoretical, it links into reflexivity, mimetic desire, keynes and other theories of market movements and price/capital formation.
A few thoughts on the current state of venture capital. When the Music Is Playing In July 2007, a few weeks before the credit markets seized up, Chuck Prince, then the CEO of Citigroup, gave an interview to the Financial Times. The line everyone remembers is this one: "As long as the music is playing, you've got to get up and dance." He was mocked for it for years afterward, and he lost his job a few months later. But I have come to think he was saying something honest. He wasn't claiming the music would play forever. He was admitting that he couldn't sit down while it was still going, and neither could anyone else in his seat. I've been thinking about that quote a lot lately, because right now is the most disorienting period in venture capital I can remember, and I have been doing this for a while. Here is what makes it disorienting. It's not that things are bad. Some things are spectacular. We have companies in our portfolio growing faster than anything I have seen in my career, and I don't say that lightly. At the same time, we have companies with no revenue, no product, and a founding team you could fit in a conference room raising billions of dollars at valuations of $10 to $50 billion. Both of these things are true at once, and if you try to reason about them with the same framework you will drive yourself crazy. Two ideas have helped me make sense of it. Neither is mine. The first is reflexivity, which George Soros has been writing about since the 1980s. In most of life, perception follows reality: the weather is what it is, and your opinion of it changes nothing. In markets, it runs the other way too. Prices change what participants believe, and what participants believe changes the prices. The feedback loop can run for a long time, and while it's running it looks exactly like progress. Here is how reflexivity is playing out in AI. Full disclosure: Menlo is an investor in Anthropic, so read the following with that in mind. People watched a frontier lab go from a $4 billion valuation to $18 billion, then $60 billion, then $180 billion, then $380 billion, and now something close to a trillion. They drew the obvious conclusion: that is what a neo lab looks like. So the next neo lab gets priced off that path, not off anything it has built. Then it gets marked up in a subsequent round, and the markup itself becomes the proof. Look at Thinking Machines. Look at Reflection. At that point valuation has stopped being an output of the metrics and has become the metric. Nobody is discounting cash flows. They are discounting the last round. Soros is very clear about one thing, and it's the part people skip: you cannot know when or how a reflexive process ends. You only know that it does. Every one of them has. The second idea is Chuck Prince's, and it explains why smart people keep dancing even when they can see the loop for what it is. As far as I can tell, there are two groups on the dance floor. The first group got in early. Firms like ours were in some of these AI companies before the numbers got silly, and the paper gains are enormous. When you are sitting on gains like that, you start to feel like you're playing with house money. I have been around long enough to know that house money is the most dangerous kind, because you don't respect it the way you respect money you had to earn. The second group missed the early rounds and knows it. Their LPs know it too. So they are trying to make up for lost time by writing very large checks very late, which is the one strategy almost guaranteed to turn a missed opportunity into a real loss. House money on one side, FOMO on the other, and reflexivity feeding both. That's the whole story. Everyone has a reason to keep dancing, and the reasons are different, which is why nobody can talk anyone else off the floor. So what do you do? The instinct in our business is to answer with company identification: just pick the right neo lab and you'll be fine. I think that's the trap. When price has become the signal, being right about the company is not enough, because you can be right about the company and still be wrong about the price by a factor of ten. The public-market investors I admire figured this out a long time ago. They spend as much time on how much to own as on what to own. The winners in venture over the next decade will be the firms that treat portfolio composition and position sizing as seriously as they treat sourcing. How much of the fund is in companies whose valuation rests on the last round rather than on revenue? What happens to the portfolio if the reflexive loop breaks next year instead of in five? Those are not exciting questions. They are the ones that will matter. The music will stop. It always does. Dance if you must, but know where the chairs are.
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Team Grasp retweeted
grasp.study for people who care about understanding
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You create a learning plan when you know least about the subject. Two lessons in, you find you already know half of it. Or the module assumes something you never properly learned. ✨You can now edit your paths✨ Open the path, go to the chat, say what you want to change: "drop the SQL joins lesson, I use them daily" "I don't understand closures, add something before this" "go deeper on indexing" Review and approve. Keep learning. Editing is free. Credits are only spent when you create a lesson.
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Mentor chats in Grasp now let you stop, edit, try again, and copy any message (including the mentor's answers, for your notes). Easier to steer, easier to keep what's useful. grasp.study/
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The best chats with a mentor are the long ones. Where you talk through what you're after and figure it out as you go. So we added voice to the Grasp mentor. Tap the mic, say what's on your mind, and it comes back as text you can tidy up before sending 🎙️✨
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You've probably got something in the back of your mind. A thing you've meant to learn. A job you're working toward. A field you keep circling. That's where Grasp begins. Tell it your goal, and it builds the path around it.
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This week we had the pleasure of @romovpa presenting "Claudini: Autoresearch Discovers State-of-the-Art Adversarial Attack Algorithms for LLMs" arxiv.org/pdf/2603.24511 He showed us how auto-research (i.e. Claude Code in a loop, equipped with a simple benchmark) can discover attack algorithms on LLMs better than hand-crafted SOTAs. "Attack" here is a prefix added to a prompt that would lead to a fixed string in the output of an LLM with high probability; LLM is a white box with known weights. Some takeaways: 1. Without seeding this autoresearch with multiple hand-written attacks, it does not work — it combines ideas, but does not come up with novel ideas. 2. Autoresearch does much better than hparam search only. 3. Plenty of options for reward hacking — need to design benchmark with autoresearch in mind. 4. Kimi performed no worse than Claude or Gemini in this task. 5. Always useful to run autoresearch if you have a benchmark to optimise as it is so low effort and powerful.
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Lesson titles describe a topic. Outcomes describe what you'll actually do. We added outcomes to the draft view so you can make more informed decisions about which lessons to focus on before you build. grasp.study
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Grasp Paper Club reviewed Prolonged Reasoning Is Not All You Need: Certainty-Based Adaptive Routing for Efficient LLM/MLLM Reasoning (arxiv.org/pdf/2505.15154) last week. - Our concise summary - Sometimes it’s enough to have a short answer. We can train a model to provide short or long answers. Based on the perplexity of the short answer, we can decide if we should switch to long answer. Their solution and literature review of SoTA could be improved.
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Grasp builds your learning path. Now you can choose which lessons to create, and when. 30 minutes to an hour of focused learning, ready when you are.
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"If you're not making progress, it's just that the quality of what you're learning isn't up to the mark. It's not that you as a person are not capable." Raj, a web developer in Bengaluru, at our first meet up. More from him and four others in our new film. Come watch the full video on grasp.study.
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The most useful learning goals describe what you'll be able to do, not just what you'll know. Three choices that can help you shape good ones with Grasp:
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3. Build on what you've already learned. New courses work better when they pick up from existing ones rather than starting from scratch. With Grasp you can reference previous courses to create new ones.
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If you're not sure how to frame your goal, talk it through with Grasp's mentor before you generate the course. It can help you narrow things down, factor in a target date if you have one, and figure out what's realistic given the time you have. paths.grasp.study
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