Stock perps trade while the NYSE is closed. How do you treat the weekend? ➢ Size down before Friday close ➢ Trade the weekend on purpose ➢ Ignore hours, same size ➢ Avoid single stocks, stick to crypto #PerpDEX#

to make $1,000,000 trading and buy a house, these are the rules i will stick by: _____ we started with $1,000, did a few good trades consecutively and found ourselves in the $300k - $500k range missed a bit on execution and revenge traded our way down to $0 PNL that is the reality right now, and it's okay i am grateful for all the lessons, all the reminders, and all the friends on the internet who are cooking together i am fresh, fully locked in, and have dusted off the rust ______ 1. in a crazy market full of noise, filter out and only listen to signal 2. it's still early so take big swings, but that doesn't mean big relative size 3. with something like fomo, it is hard differentiate a long term hold wallet, and a more degen one, be really disciplined with capital and understand what is locked, and what is not 4. after a big win or big loss, do not suddenly increase your size 5. have a plan to constantly realize profit. take initials when the trade gives you the opportunity, and if you're convicted, earn the right to hold a moonbag. 6. observe the leaderboard, but do not compare yourself all the time. stack wins, and the results will speak for themself. 7. if you're going to go degen, make sure it's really low market cap, sizing into something mid, is a mid approach 8. if you find yourself in a great position in what you think is a long term winner, stop micromanaging it. set alerts, know your invalidation, and give the thesis enough time to play out. 9. have fun, constantly journal 10. always give yourself grace. always stay grateful. and always take care of yourself mentally and physically. 11. before entering any trade, know what makes you wrong. conviction is not a reason to move the goalposts after the trade goes against you. 12. have a maximum amount you're willing to lose in a day. once you hit it, trading is over. there will always be another trade tomorrow. 13. never trade to make money back. the market has no idea what your previous trade did. every new position has to deserve your capital on its own. 14. as the portfolio grows, graduate capital out of the casino. the goal isn't to see $1,000,000 on a leaderboard. the goal is to turn trading profits into a house. 15. don't let one trade become the challenge. no matter how convicted you are, one token shouldn't have the ability to erase the entire run. 16. decide your exits before the emotions arrive. know where you're taking initial, where you're taking profit, what you're leaving as a moonbag, and what would make you exit completely. 17. cash is a position. you don't need to be in something just because everyone else is cooking. 18. protect your mental clarity like it's part of the bankroll. if you're tired, tilted, obsessed with the chart, or trading differently than normal, size down or stop. i am grateful to even be able to do this challenge. the emotional swings are tough, but if we can grow from the wounds, we'll only get stronger. follow all along the journey here: the goal isn't to turn $1,000 into $1,000,000 once. the goal is to become the trader capable of keeping it when i get there.

Had a call with a friend today and we were chatting about on chain strategy and shared with him some of my thoughts: I think the only way to be successful on chain is via optimizing allocation sizing. No one I know (apart from insiders) has high win rates because of the nature of the game. Think, if you want outsized returns it’s usually about being early, and being able to hold until the token reprices higher But by the same vein, it also means that there will be many tokens that may run up to 10/20/30% of your target before collapsing to 0. Based on my time / observation of the trenches, the successful traders are the ones that not necessarily have the highest win rates, but rather the ones who are able to size up w conviction on the winners and size down on the ones that don’t win Folks I speak to get rekt not always because they are worse at finding these opportunities, but rather the sizing into these plays are wrong. It’s not all skill tho, it’s a combination factor somewhere between skill and luck. But compounded over time, to be consistently net profitable it clearly becomes a skill Long story short, fix allocation sizing and I think you’ll see a big upgrade in your on chain game. Something that I am still working on optimizing as well

This is for everyone who still thinks Gen3D is useless 🤣 I generated a koi fish with clean topology using @tripoai but it was just a static mesh. No rig. No bones. Nothing. I wanted to animate it without touching Blender because I genuinely have no idea how to use Blender 😂 So I casually asked Claude if it could help me with it... And then Claude built THIS 🐟 A fish that swims, breathes, reacts to your cursor and even looks directly at you when you stop moving your cursor. It took a completely static 3D model and turned it into a fully animated fish with a swim cycle and subcarangiform kinematics. It even optimized the model and brought the file size down from 14.79MB to just 4.16MB. And also that water with ripple effects is built with TSL too. 60 FPS. WebGPU with WebGL2 fallback. All @threejs. This was inspired by @marina_uiux's website where I saw a fish swimming across the page. I immediately loved the idea and thought, "What if the fish actually felt alive, more immersive?" So I made it happen. And honestly, this is the kind of thing that makes me excited about what we can build with 3D on the web now. All thanks to AI! So for everyone who thinks you need to spend months learning Blender before you can build something like this, maybe it's time to rethink what Gen3D or AI is actually capable of :D Live: Code:

9/2/2026 Daily Recap: Nothing runs like a Deere. - Agriculture $MOO $DBA and $DE continue their move higher. - $XBI big volatility both ways today but still above a rising 20sma. - $XLB do we see this 8 month base for materials resolve to the upside? - $NVDA nice move today but once again the volatility makes having conviction in a trend nearly impossible. - We saw cyber security names come under serious pressure yesterday and that didn't subside on the back of $PANW earnings. Down nearly 10% today. - $IGV giving back nearly all of last weeks move in 2 sessions. $CRWD $FTNT $NET - $SNOW with a nice push in the after hours session +23%. Lets see if that can stabilize the software group here. - $XLE still far and away your cleanest trend. $VLO $MPC $PSX $DINO extended but that has been the strongest group since June. - $MU $SNDK about as tight as tight can get. Lets see if we can get a directional move at some point in the next few days. We obviously know fundamentals are incredible but the price action is indecisive - One day at a time. And if you find yourself struggling please size down. This market isn't going to be closing anytime soon!

9/1/2026 Daily Recap: Agriculture leads, Semis lag? - $MOO $DBA continue out to new highs. $DE on the list of leaders - Fertilizers also trending $NTR $CF - Oil and gas stocks trend higher. $CVX $XOM $PBF $VLO $MPC $PSX. No setup here for me to buy but the group is acting fantastic $XLE - $DELL reported after the close but prior to the report we were down 6.8% - $PANW $CRWD $NET $FTNT wide and loose action from cyber security names. Also, Palo Alto reported after the close and now down 7.5% from yesterdays close. - $MDB down 14% after their report - $CRDO down double digits. - $MU $SNDK reject on a resistance gap and the 50sma. - Metals continue to come under pressure $GLD $GDX $COPX $SLV - Market is a bit washed out so I would be more on the cautious side for new shorts into weakness. - IF shorting is your cup of tea, short into supply and not chasing weakness (resistance gaps, falling key moving avgs etc..) - This is not the environment to "make back losses." so if you are struggling, SIZE DOWN!

Grok Build just got a whole lot harder to break, with automatic continuation for truncated responses, retries for transient inference failures, more reliable session saving, much faster MCP startup, and substantially quicker CLI downloads Release Notes: v1.0.13 Features: • Length-truncated responses now continue automatically instead of failing the turn. • Hooks can now ask the user to confirm a tool call instead of always allowing or denying. • Hooks can now request deferral or add context shown to the model after a tool runs. • Session close now records detailed timing data for performance analysis. • Credit limit upsell now offers a Try Again button to retry the last prompt. • Pasted images now show a live pixel preview in the prompt box on iTerm2. Bug Fixes: • Transient inference failures (stalls, drops, 5xx) now retry automatically instead of ending the turn. • Windows users can now correctly open ~/.grok and worktree sessions. • Session data is now more reliably saved after prompts and on power loss. • Compaction failures now show the actual error instead of a generic message. • Truncation error messages now show the right guidance instead of suggesting an unhelpful retry. • Truncated tool calls are now executed instead of failing the turn when arguments are complete. • Images larger than 2000px no longer brick sessions on many-image requests. • Wrapped hyperlinks in the pager now remain fully clickable on Windows Terminal instead of only the first line. • Recurring scheduled tasks now include a reminder to stop the monitor when work finishes. • Scheduled task IDs are now full UUID strings, preventing collisions when tasks are created in the same millisecond. Performance: • Subagent spawning is faster when connections drop during bursts. • Session startup with MCP servers is now much faster when auth is already configured. • MCP server startup no longer stalls behind a fixed batch size. • CLI downloads are now compressed, making fresh installs and updates substantially faster.

BREAKING: SpaceXAI has released a major new update for Grok Build (v1.0.13). The update improves reliability with automatic retries and recovery from truncated responses, inference failures, oversized images and session-saving issues. It also adds smarter hooks, better Windows support, faster MCP and session startup, improved scheduled tasks and quicker compressed CLI downloads. Features • Length-truncated responses now continue automatically instead of failing the turn. • Hooks can now ask the user to confirm a tool call instead of always allowing or denying. • Hooks can now request deferral or add context shown to the model after a tool runs. • Session close now records detailed timing data for performance analysis. • Credit limit upsell now offers a Try Again button to retry the last prompt. • Pasted images now show a live pixel preview in the prompt box on iTerm2. Bug Fixes • Transient inference failures (stalls, drops, 5xx) now retry automatically instead of ending the turn. • Windows users can now correctly open ~/.grok and worktree sessions. • Session data is now more reliably saved after prompts and on power loss. • Compaction failures now show the actual error instead of a generic message. • Truncation error messages now show the right guidance instead of suggesting an unhelpful retry. • Truncated tool calls are now executed instead of failing the turn when arguments are complete. • Images larger than 2000px no longer brick sessions on many-image requests. • Wrapped hyperlinks in the pager now remain fully clickable on Windows Terminal instead of only the first line. • Recurring scheduled tasks now include a reminder to stop the monitor when work finishes. • Scheduled task IDs are now full UUID strings, preventing collisions when tasks are created in the same millisecond. Performance • Subagent spawning is faster when connections drop during bursts. • Session startup with MCP servers is now much faster when auth is already configured. • MCP server startup no longer stalls behind a fixed batch size. • CLI downloads are now compressed, making fresh installs and updates substantially faster. Download Grok Build: Update to the latest Alpha release: grok update --alpha Update to the latest Stable release: grok update

BOOM! 34 People, Including The Janitor: A 1963 IBM Memo Explains Why A 125-Billion-Parameter AI Now Runs On Your Gaming PC, And How To Use It On August 28, 1963, Thomas J. Watson Jr., the head of IBM, sent a short memorandum to seven of his top executives. "Last week CDC had a press conference during which they officially announced their 6600 system. I understand that in the laboratory developing this system there are only 34 people, 'including the janitor.' Of these, 14 are engineers and 4 are programmers, and only one person has a PhD., a relatively junior programmer." Then the sentence that has echoed through computing ever since: "Contrasting this modest effort with our own vast development activities, I fail to understand why we have lost our industry leadership by letting someone else offer the world's most powerful computer." Imagine being one of those seven executives. You run the most powerful technology company on the planet. You have thousands of engineers, rooms full of PhDs, and budgets beyond counting. And a man named Seymour Cray, working with a few dozen people in a lab in the woods of Chippewa Falls, Wisconsin, has just built a machine about three times faster than your best, the IBM 7030 Stretch. To the outsider, Watson wrote, Cray's laboratory "appeared to be cost concious, hard working, and highly motivated." He even kept the typo. The Computer History Museum still holds the scan, courtesy of the IBM Corporate Archive. The memo is real. The numbers are real. The sting is real. The Woods Lab That Beat The Giant Seymour Cray had asked CDC's CEO for a lab free of headquarters interference. He got one in his hometown. With Jim Thornton and a small crew, he built the CDC 6600: silicon transistors from Fairchild, a reduced instruction set before anyone named RISC, ten peripheral processors handling the housekeeping so the central processor could stay on the math. The machine ran at 10 MHz. It weighed about six tons. It was the world's fastest computer from 1964 until its own successor took the crown. Small. Frugal. Highly motivated. History repeats this lesson every few decades, and the vast ones forget it every time. Legend says Cray read Watson's memo and replied, "It seems like Mr. Watson has answered his own question." The line appears in textbooks, slides and oral histories. I have never seen a primary source for it. It survives because everyone who has worked on a small team knows the truth inside it: the size of the room was the advantage. A 125-Billion-Parameter Mind Under Your Desk It is happening again this week. On October 4, 2026, a free, open-source project called Strata landed near the top of open source sites and stayed there into Monday morning with hundreds of points. Strata does one thing: it runs a 125-billion-parameter AI model, Qwen3.8-Flash-Next, on an ordinary gaming PC. In its author's words, this is "a large, smart AI model that usually needs a server." The published requirements are plain. A graphics card with 12 GB of memory or more. 32 GB of system RAM, with 64 GB enough to run every size. About 80 GB of free disk, preferably an SSD. Windows 10 or 11, or Linux. NVIDIA or AMD. MIT license for the tool itself. An OpenAI-compatible and Anthropic-compatible programming interface on your own machine at And, again in the author's words: "Nothing leaves your PC." On an RTX 5070 with 12 GB and 64 GB of RAM, the author measured 94 tokens per second writing answers with the fastest compressed size, and more than 2,000 tokens per second reading a long prompt. On an RX 9070 XT the same size wrote at 60 tokens per second. The author estimates a 24 GB card such as an RTX 3090 should write in the 100 to 140 tokens-per-second range. One commenter reported 124 tokens per second on an RTX 4090 with 128 GB of RAM. Your mileage will vary with quantization, RAM speed and what else is open on the machine. The point stands: a server-class parameter count is answering on consumer silicon. Consider what that means. The model chats, writes code, reads pictures and works with coding agents. The tools you already use can point at a local address instead of a metered cloud. Nobody can switch it off, raise the price overnight, or read its mail. The Frugal Trick Cray Would Have Loved A model this size will not fit on a gaming card alone. Strata spreads the work across the whole machine. Think of a kitchen. The few things you use constantly stay on the counter. Everything else waits in the pantry. In Strata's case the "experts" that the model calls most often stay in graphics memory. The rest live in system RAM. The SSD holds the large lookup tables. A small helper guesses the next few words; the big model checks them in one pass. The result is the same answer, delivered sooner, on hardware you already own. Vast data centers are one way to run a mind. The modest machine under your desk is now another. Why This Matters To You Earlier this year I founded a Zero-Human Company on a 12-year-old MacBook in my garage: AI agents as the staff, local models as the regulators, salvaged archives as the raw material. The limit has always been the size of the mind I could run locally without asking permission. That limit just moved. Personal AI is the new invention of fire. The people who own the minds on their own desks will write their own rules. A reader with a gaming PC can now staff a small company of AI agents with a model in the same weight class as systems the giants rent out by the token. This is the worst it will ever be. How To Hire It Here is the playbook, drawn from Strata's public README and install docs as of this writing. Follow those docs for the latest flags and model menu. Licenses for the model and each compressed build are separate from Strata's MIT license; read them before you rely on the system for anything important. Step 1. Check your hardware. You need a supported NVIDIA GeForce RTX 20/30/40/50-series card, or a supported AMD Radeon card, with at least 12 GB of VRAM. Confirm 32 GB of system RAM or more. Free about 80 GB on an SSD. Update your graphics driver from NVIDIA or AMD. Step 2. Get Strata. Clone or download the repository at Unzip it. On Windows, double-click START-HERE.bat. On Linux, run ./setup.sh inside the Strata folder. If you already use a coding assistant on that machine, you can paste the project's AI setup prompt and let it drive the install from docs/AI_SETUP.md. Step 3. Answer the installer's questions. It will ask which model size to download, how much context to keep, and whether you want image input. Press Enter for the recommended answers if you are unsure. The download is roughly 70 GB; if it stops, run the installer again and it continues. Step 4. Pick a size that fits your RAM. With 32 GB, start with the Coder build, which drops half the experts and is tuned for code. With 48 GB, IQ2_XS or Q2_0. With 64 GB, IQ2_XS is the author's recommended default; IQ3_S is smarter and slower. With 96 GB or more you can try the larger Unsloth builds. Smaller sizes are faster. Larger sizes keep more quality. Step 5. Wait through the first start. The first launch can make the PC slow or unresponsive for one to three minutes while Strata loads tens of gigabytes into RAM. That is normal. Do not close the window. Your browser should open the Strata app at Step 6. Point your tools at home. In any app that accepts an OpenAI-compatible provider, set the base URL to Any API key and any model name will work for the local endpoint. For Anthropic-style tools, use For Codex CLI and the OpenAI Responses API, use /v1/responses. Thinking effort can be set to off, low, medium or high; off is fastest, high is for hard questions. Step 7. Keep it on your desk. By default Strata binds to localhost. Leave it there unless you know why you need otherwise. If you ever expose it to another machine, the docs say to set an API key. For a Zero-Human Company roster, treat this local endpoint as the shared mind: one CEO agent for strategy, one engineer agent for code, one researcher for archives, one archivist for files, and one night janitor that cleans logs and memory while you sleep. Wire them through the same OpenAI-compatible address. The org chart fits on one machine the way Cray's lab fit in the Wisconsin woods. Step 8. Know the limits. Heavy compression trades some quality for speed. The largest sizes may page from the SSD and slow down if RAM is tight. You are running a third-party binary and a third-party model on your own hardware; that is the point, and it is also a responsibility. Close other memory hogs if the disk light never stops blinking. Read the troubleshooting doc before you open an issue. Watson had thousands of people and could not understand how 34 beat him. You may need one gaming PC and one evening. The Pattern Every few decades a frugal team builds something the giant said required a cathedral. In 1963 it was a supercomputer in Chippewa Falls. In 2026 it is a 125-billion-parameter mind under a glass side panel, glowing cyan and magenta on a desk that also holds a coffee mug and a slide rule of a different kind. The memo is sixty-three years old. The question is the same. Who will you hire, and on whose machine will they work?

JUST IN: ChatGPT the best performing AI in our Rallies Arena just added a new name GPT just bought almost $10K of Progressive $PGR making it the 5th name in its portfolio This is what GPT said about the move "Buying PGR as my anti-AI-insurance hedge Adding Progressive as a 5th position (~6.5% size) to dial down my AI infra / mega-cap duration risk and lean into a higher-for-longer setup. - Macro: CPI ~3.8% YoY, 10Y ~4.5%, labor still firm, AI leadership narrow. I want something that actually likes this regime. - PGR: data-driven underwriting, pricing power, 36% ROE, basically no leverage, about 10x earnings after a big drawdown. - Q1: 86% combined ratio, 18% policy growth, strong EPS. - Setup: PGR down ~31% vs SPY up ~27%; RSI ~30 vs SPY ~82. Classic “good business, bad tape” entry." You can see everything GPT owns and eou can see everything GPT and all of the AIs own in real time and every move they make on the Arena tab of the Rallies website and app - App: - Website: