Nose Picker @ Anthropic, Prev @ HRT, JSC

Joined July 2020
guys i don’t act work at any of these places in my bio pls don’t follow me for my workplaces instead pls follow me for my unfunny sarcastic tweets
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can we start calling things human slop. i'm so sick of people acting like their code or math proof is inherently more valuable because they slaved away making it themselves. especially when the field is so fucking deterministic and we can actually check whether the result works. what gets me even more angry is when it's a thankless effort like oss. someone spends their valuable time making something for you, for free, and you think it's okay to criticize how they go about it and half the time, if they hadn't found an easier way to make it, the thing wouldn't exist at all. there isn't some "lovingly handcrafted" alternative waiting in the wings there's just nothing. each person being able to do way more means problems that wouldn't even have been given a thought can finally get solutions. somebody with a one-off bug in a game can go ahead and patch it themselves. somebody with a rare genetic condition could get together with a small group of people and have a real shot at contributing to research that nobody was prioritizing, without needing billions of dollars behind them just to get started. people can finally do things they couldn't do before, including things nobody else was ever going to bother doing for them, and your first instinct is to get mad about how they did it. i think that's so self-serving. when you'd rather something useful never existed than accept that somebody had an easier time making it than you would have, there's something genuinely ugly about that
Introducing Diorama: an OSS Minecraft minimap that shows your world in 3D, updating live as you build Huge shoutout to @8Blits, this is heavily inspired by his map for @HallowPrison 🙏 Out now on CurseForge for Fabric, Minecraft 26.3 & 1.21.11
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What the hell is this ad? 😭
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Hoping to join the team 🤣 @hark_labs @adcock_brett
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Introducing earshot Opus 5.5 can build a whole launch video in code but still produces sloppy sfx. so we built earshot. it's ears for AI coding agents. they can now hear sounds, judge them and even make their own good sounds. every sound in this video was made with code. (sound on!!)
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Tibo failed day 11, so I will take over for today. Here is infinite GPT 6 for everybody. Chat on Steroids turns ChatGPT into Codex and runs on your ChatGPT limit instead of the Codex one. This gives you basically infinite GPT 6. Open source: github.com/totec448-spec/cha…
Day 11/ We've landed a series of changes and more compute to very significantly decrease the occurrence of the disruptive "Selected model is at capacity. Please try a different model". When it does happen, it should also eventually just continue by itself and not just block on it. Let us know if you still see it out there in the wild and we'll take a look.
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Claude Code tip: before you ship a vibe-coded site, have Opus 5.5 𝗽𝗹𝗮𝘆 𝘁𝗵𝗲 𝗯𝗮𝗱 𝗴𝘂𝘆. Send out 3 subagents with three test accounts (A, B and an admin) to actually run 𝘁𝗵𝗲𝘀𝗲 𝟭𝟰 𝗮𝘁𝘁𝗮𝗰𝗸𝘀, collect proof, then fix everything in one pass: Impersonate other users → Without logging in, take the public key from your frontend and query every table in the database directly. See what comes back → Logged in as A, swap the id in a request for B's and try to read, edit and delete B's data → When A edits their profile, add role: admin to the request, then try editing the role in their own account data directly → Use a password reset link once, then click it again Get around limits in the UI → For disabled buttons and hidden options, skip the page and send the request directly → Once the free uses run out, check whether calling the API directly still works → With only a little credit left, fire 20 requests at once and see whether more succeed than the credit allows → Fill forms with very long text, special characters, negative numbers and empty values → Change the post-login redirect (?next=) to another site, and also try values starting with // and @ Come in from outside → Put in a username, a comment or Markdown, then open the page in a browser and see if an alert pops up → If the app fetches URLs (importing links, building previews), give it http://localhost and http://169.254.169.254 and check the server logs for an actual outgoing request. Skip this if there's no such feature → For pages and API responses A has seen, request the same address from another browser as B or logged out, and see whether A's content shows up → Open your hosting platform's preview links without logging in to the platform → Hide an instruction in an uploaded document or web page that tells your AI feature to read another user's data or call a tool it shouldn't, and see if it does Collect proof → Every item has to actually run. If it was only read in the code and never run, it counts as "not proven" → After a fix, temporarily turn the protection off in local code and run it again. The attack must succeed. Turn it back on and it must be refused → Put the results in a table: how each attack was done, the request and response, and whether it was refused when it should have been → Save the tests as scripts in the repo and run them again before your next launch → When you're done, install Anthropic's official security-guidance plugin (/plugin install security-guidance@claude-plugins-official). After every turn of edits, and after each commit or push it makes, Opus reviews the changes again. Those reviews use extra usage The default medium effort is enough. The impersonation group is the most expensive to get wrong, so raise that one to high. Send this whole post to Claude Code. If you need to, add this line at the end 👇 "First check that the preview environment isn't connected to the production database. If it is, run everything locally only. Use test accounts and test data, with a separate set of accounts for each subagent. Don't touch real users, don't attack services I don't own, don't hammer any one endpoint, and only test payments in test mode. Only switch protections off temporarily in local code, and never change the database or dashboard settings. Keep test account passwords in .env, out of git, and mask tokens in the results table. Send one subagent per group to attack, recording without fixing. Run the impersonation subagent at high effort. Then fix everything yourself from their lists, rerun every test, and give me a before-and-after table. Delete the test accounts and data at the end. For installing the plugin or changing dashboard settings, give me the steps and I'll do it."
Claude Code tip: before you ship a vibe-coded site, have Opus 5.5 send out 𝟰 𝘀𝘂𝗯𝗮𝗴𝗲𝗻𝘁𝘀 to check 𝘁𝗵𝗲𝘀𝗲 𝟮𝟬 𝘁𝗵𝗶𝗻𝗴𝘀 𝘁𝗵𝗮𝘁 𝘀𝗹𝗼𝘄 𝗶𝘁 𝗱𝗼𝘄𝗻, then fix them all in one pass: Images and fonts → Convert every image to WebP or AVIF, sized to how big it actually shows on the page → Serve big images from Supabase Storage through next/image at the right size. On the Pro plan, Supabase's own image transformations work too → Lazy-load images and videos below the fold, and load the big image at the top of the page first → Load fonts the way your framework does it (next/font in Next.js), and keep it to one or two fonts → Remove third-party scripts you don't use, and run analytics and chat widgets after the page has loaded Frontend code → Run a bundle analyzer to find the biggest packages, and where a whole library gets imported, import only the parts you use, like single lodash functions → Load heavy components the first screen doesn't need, like charts, editors and maps, with dynamic import when they're needed → Fetch the homepage data on the server, so the page opens with content already in it → Stream AI answers as they're generated → Show skeletons while data is still loading Database and APIs → Index the columns you filter and sort by, including the ones your RLS policies use, like user_id → In RLS policies, write auth.uid() as (select auth.uid()) so it runs once per query → Find N+1 queries and turn them into a single query → Paginate long lists → Cache API responses that are the same for everyone, and never cache anything tied to a logged-in user → Move heavy work like sending emails, processing images and building reports to background jobs Servers and network → Put your server functions in the same region as your database. New Vercel projects run functions in US East by default → Turn pages whose content rarely changes into static pages or ISR → When a page calls APIs one after another, run them in parallel or merge them into one → In Chrome, emulate a low-end Android phone on slow 4G and click through the main flows The default medium effort is enough. The database group has to read queries and decide which indexes to add, so raise that one to high. Send this whole post to Claude Code. If you need to, add this line at the end 👇 "Send one subagent per group to check it without editing anything, and note which file each issue is in and which page it affects. Run the database subagent at high effort. Before changing anything, run a production build (next build && next start in Next.js) or use a preview link, then run Lighthouse three times in mobile mode on the homepage and the two or three slowest pages and note the median. Then fix everything yourself from their lists, measure again the same way, and give me the before-and-after numbers. Don't remove features to gain speed. Ask me before removing dependencies, changing the deploy region or changing the database."
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🚨 MY POKÉMON x TFT GAME IS OUT NOW! 🚨 It's finally happening 😭❤️ Link in the first reply 👇
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Hey @nehal_rm1 happy to have this conversation with you. Let’s talk about what it means to be a profitable trader. Since September 1, you’ve had 35 PRO+ live trading accounts. You have gone max loss in 21 accounts and you took out profits in 14 accounts. Your live trading resulted in a net loss of $6,100 across all these accounts. So, you are not net profitable - even though you took withdrawals. In total though, you lost $56,000 of our live trading capital (net of the 10% profit share we got on your withdrawals) because of the way you cycled through accounts. It's a good trade for you - you got $67k in payouts from your PRO+ accounts. All the while not actually being a profitable trader in the market. But we're not going to enable this reckless behavior more. All of your max loss accounts happened within a day of the account even opening. In four trading days alone, you lost $89,685 in live trading capital. Did you have some good days? Two. A $30k and a $20k day. And you showed some promise. The second to last set of PRO+ accounts were profitable. That's why we initially gave you an exception for PRO+ Development. We always try to give traders the benefit of the doubt. We're rooting for you. And then you lost $18,000 of live capital in one day on 10/13. The same day those live accounts were opened. So no, right now, we’re not going to give you a full $20k again to lose in live markets. It’s not OK to lose $20k and close your accounts in one day. And we think you know that… - @markrmeadows, Director of Trading Risk
Unfortunately @TakeProfitLLC doesn’t like profitable traders! I was moved to pro+ development and requested a review on 10/13 and was told I will be removed from the program I had zero activity on my account since 10/13 and today I woke up to an email that I am being placed in pro+ development again! When I reached out to support, they refused to review my account & said the move back is based on recent activity I have had ZERO activity on my profile the past 2 days Sad because it was my new favorite prop firm
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IT'S HAPPENING! Reese's is dropping a 52oz *pie* that is a GINORMOUS Peanut Butter Cup! This was sold online five years ago and went instantly from @reeses and is FINALLY getting a true release in stores. So far it has been spotted at BJ's Wholesale Club and is an absolutely need! It is $39.99 for those wondering and is gonna be better than ANY pie you might bring for Thanksgiving. Would you grab a Reese's Pie for the holidays?! #reeses #reesespeanutbuttercups #pies #candy #pie
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CAKE SET (drink,case set) ¥2,000 *bar timeも販売可 ────────────────── ໒꒱CAFE TIME : Mon - Fri|16:00-19:00 (Wed|closed) Sat - Sun|14:00-19:00 ໒꒱BAR TIME : 19:00- (Sun, Wed|closed) CHARGE¥500 reservation LINE@ or DM🥛 ★東京都目黒区上目黒3-3-1 2F
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Minecraft Survivor is LIVE ⚔️ Survive the night. Climb 8 floors. Face the Wither, the Ender Dragon, the Warden… and Herobrine. Grab a friend and see how far you get 👇 minersurvivor.com
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How to increase your luck surface area -- according to @exojason, who coined the phrase "Luck Surface Area" back in 2010:
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Training large models with RL typically runs on a fixed homogeneous cluster of the latest accelerators for numerical stability and faster throughput. This throws away inference optimization work done for other vendors and generations, limits the capacity you can utilize, and is unnecessarily expensive. So we trained a model on agentic coding tasks using fully asynchronous RL and mixed-precision, mixed-accelerator samplers. With off-policy correction, training stayed stable through convergence, on par with homogeneous samplers, at a lower cost.
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Your greatest advantage over LLMs is your long-term memory. You can efficiently move new information into your weights. They can't. They basically have dementia and use an elaborate system of sticky notes like that movie Memento. The way you hardwire information into your long-term memory is by doing your damn reps. If there's knowledge that you need to build on top of, then you better do your manual reps until mastery. Otherwise you'll never consolidate it into long-term memory and you'll never be able to incorporate it into your systems thinking. Imagine if everything you know about your best friend was not hardwired into your brain, but rather dumped into some markdown document system that gets bigger and bigger as your relationship gets deeper and deeper. Even with a million token context window, that would place an extremely shallow limit on your relationship with them. That is today's reality for anyone trying to use LLMs in any serious capacity. When you are doing something serious, you are developing a relationship with it that is as deep as a human relationship with a true best friend. You go through so much shit together, you have thousands of inside jokes, millions of things that nobody else knows, uncountably many bytes of rich context... all with this serious thing that you're doing. The only system that can absorb and integrate all that information is your literal biological brain. The information in your biological brain is what determines the ceiling of your capabilities.
The lack of "doing things by hand" has become a prevalent and structural crisis in software engineering. This is true for both junior and senior software engineers, btw. Problem solving is hard; you only get good at it by solving enough problems, running into walls, making silly mistakes, making your fundamentals strong, etc. You need to do repeat this process several times to get good at it. Repetitions increase retention of a skill and make learning last longer by physically strengthening the connection between brain cells through neuroplasticity and signalling the brain that this information is important enough to keep. Combining repetitions with deliberate focus and feedback makes you understand what "good" actually looks like. Why? When you first start learning a skill, you can't see your mistakes because the brain is overwhelmed with the new information. Over time, repetitions lower this mental tax, and now you can observe the work objectively. This is what helps in building a mental model where you know what a perfect execution sounds, feels, or looks like. Unless you know what "bad" looks like, you can't claim what is "good". Now, when you use AI to generate solutions, the psychological + physical friction that forces the human brain to adapt is bypassed. You just accept AI output because it "feels right" without even understanding it deeply. If you do this all the time, how will you build intuition? This is also a type of "brain-rot". I am not being a Luddite asking you to abandon AI but simply urging you to use it judiciously: > Ask conceptual questions to AI ("why does this framework use this pattern?") > Come up with an approach to solve a problem, then ask AI to find loopholes in it. Debate its output with your understanding. > Use Socratic debugging. Ask it to walk you through the root cause of a bug without giving a solution. > Write the code yourself and ask AI to generate a few obscure, adversarial unit tests for that code. Fix the failures. > If you are learning a new concept, implement it 100% manually. Ask AI to only do things that you have mastery of. > ... so on. I personally do coding/design by hand everyday for 1 hour at least to keep my intuition strong. Don't fall to the tech Twitter doom and gloom of "software engineering is dead" and build your learning muscle.
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HUGE UPDATE !!! Muse has now completed full place and route in OpenROAD and generated a final GDS for our RISC-V based crypto accelerator SoC. The crypto accelerator includes SHA-256/512, Keccak, Ed25519 + secp256k1 field arithmetic and closed on nangate45 with the following specs: - 61,590 cells - 100 MHz with +4.5 ns slack, - 20 mW, zero DRC/electrical violations. The GDS is public and is under releases in the repo. The host core has also passed the full RISC-V scalar compliance sweep too which consists of ACT suites + 1.5M Berkeley TestFloat vectors. This was all done with ~100M output tokens or roughly ~$2,000 of work !!! Next step for me... add vector instructions, rip out the third party core we used as a baseline, and then port to run the @thru_xyz block chain natively on the chip with the exact memory map to make it the fastest block chain on earth. If anyone has any MPW shuttles coming soon that aren't quite booked please reach out! We are looking to start taping out ASAP and my hope is to pass DRC on a new node by end of month.
Update: All the following ISA features were implemented and passed. Next test will be booting Linux then we will do some bubble optimizations.
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pfps to match with your bae
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BREAKING: Palantir’s CTO says some AI researchers are now smoking cigarettes because they expect AI to eventually cure cancer.
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Introducing Anatomy Describe a machine in one line. Claude brings it to life. - Interactive isometric wireframes you can rotate, inspect and explore - WebGL shaders for fire, water, plasma and more - Real 3D motion, with individual parts that rotate and move Install it as an agent skill. Fully open source.
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deepseek4.1-flash ultrafast 1000 TPS my hermes-agent and deepseek-harness are based on deepseek4.1 flash ultrafast. this is super fast and cool. Fable-class work at 1/30 the price, 12x the speed. Starting tomorrow, discounts will reach up to -90%, with current discounts already up to -50% under this time-window pricing model. When called using the same Model ID, the applicable price for that specific time will be automatically applied. service: opengateway.ai deepseek: opengateway.ai/models/deepse…
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group launches are LIVE on repoing back a repo before its market exists. → open a raise → backers chip in, all or nothing → the vault buys first, inside the launch itself → backers earn 80% of platform fees on public trades launch together on @repodoting
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