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I have to say - for me it started 2 years ago. I remember the moment so well. I was on vacation in Montenegro. Early night. Everyone is asleep and I am on the balcony watching the cruise ships in Kotor bay as the horizon faded to dark. And I think it was Sonet 3.5 (don't quote me). I had just setup a plugin in NeoVim called Avante by @yetone . And it was magic. Coding with AI at the time wasn't the same - I was going function by function. I was accepting diffs one hunk at a time. But I remember that night - from 10 to like 2 in the morning - I built what I thought would have taken me a week (I was rusty and learning the stack). It was an internal tool - a partial JSON parser / repair tool - so you can take half finished JSON and safely turn it into something that would parse. It is more complicated than it sounds. Anyway. I was hooked that day. At the time I was an executive at a Fortune 50, so coding was not in my job description as such. I had hundreds of engineers... but I have to say - it relit my passions, and now as I am (hopefully) building another startup - I still love it. And I still yell at it. And constantly hunt where it is messing up the architecture and adding bloat and.... well you know how it is.

I asked people: "which robotics labs and startups have the highest talent density?" 28 votes: Physical Intelligence (@hausman_k, @svlevine, @chelseabfinn, @adnan_esm, @brian_ichter, @QuanVng, @lachygroom) 18 votes: Generalist (@peteflorence, @andyzengineer, Andrew Barry) 9 votes: Sunday (@tonyzzhao, @chichengcc) 6 votes: Skild AI (@deepakpathak, @gupta_abhinav_) 4 votes: Dyna (@Lindon_Gao, @YorkYang5050, @JasonMa2020) 3 votes: Bracket Bot (@sincethestudy) 3 votes: OpenAI Robotics (@model_mechanic, @PengchuanZ, @ChengshuEricLi) 2 votes: 1X (@BerntBornich) 2 votes: The Bot Company (@kvogt, @pariljain, @lukeholoubek) 2 votes: Figure (@adcock_brett) 2 votes: Genesis (@zhou_xian_, @theo_gervet, @johnsonwang0810) 2 votes: Prometheus (@JeffBezos, @vik_bajaj, @sherjilozair, @wgussml, Alex Graves) 2 votes: Robocurve (@chooi_jeq) 2 votes: Tesla (@elonmusk) 2 votes: Weave Robotics (@kaandogrusoz, @evan_wineland) People couldn't pick a company they work at or founded. Disclosure: I'm a small investor in Physical Intelligence. I didn't vote.

Opus 5.5 is incredible at instructional video generation. I made this launch video for a inference startup in 1min for ~$2. Videos like these used to take weeks if not months and a lot of coordination with agencies and 1000x the costs. Humans broadly prefer video to text. This changes the substrate of communication. These videos actually help communicate technical ideas in seconds (photorealistic video gen like Seedance is not very useful here). - changes how often marketing should be talking about products and launches - change how sales people can talk about technical products to their customers - allow technical people to easily explain concepts internally without long docs And thats just scratching the surface within startups. Prompt: “make a modern slick and punchy video for a modern startup that works on inference”

💰 Passed $10M/y in revenue + investment gains this year I've always been aggressively increasing my profit margins to as high as possible, especially the last few years, and especially this year where I've reduced my SaaS dependencies to just a handful of companies by vibecoding my own replacements It's now about 94.5% profit! Spend less -> lower costs -> more profit -> more money saved -> more money to invest -> more % returns on investments And at some point that investment return starts to pass by your business revenue which it has for me for about a year now Most of my investments have been simple ETFs like Vanguard S&P500, but also a few lucky stock and startup bets that worked out: Back in 2022, I couldn't get any available GPUs, so I thought it might be smart to buy Nvidia if there's such a shortage and that was a good bet too Then back in 2023 @dannypostma recommended me to invest in the companies we used for our AI inference for our photo AI apps, so I did that too. First I invested in @replicate and then also @FAL From then I just asked every app/service I used if I could invest, like @cursor_ai in 2025 which then got acquired by @spacex recently! My business revenue has remained very stable at about $200K-$250K/mo, but even with that investment returns have now surpassed that Investments fluctuate a lot so some years it's up some years it might be down a lot (who isn't expecting a big crash at some point?), and most investment gains are unrealized (I never sell!), so keep that with a big grain of salt! I keep my revenue/gains together with my profit margin and my sleep score in my situation monitor dashboard, as those are equally important :D Many people in the last decade told me to spend all my money, either personally or with my business to grow it, we don't know how that would have ended up, maybe my companies would be bigger, but I'm happy I did it in my own lean profitable healthy way and it ended up great I think! 🙏😊

Been heads down on my own AI startup this year so I haven’t taken a single paid promo. Scroll my TL if you don’t believe it. I don’t live off this. Started aping memes recently just to test my team’s unreleased on chain signal. Now people keep calling it insider. I get it maybe y’all think I’m too pretty to actually have any skill. Grateful as hell to my team for the fire strategies though. Don’t want to move bags. Don’t even like posting alpha. Definitely not dropping analysis. AI can already distill that mid slop for you. From now on I’m just posting selfies. Be grateful a pretty girl is even on your TL.

patterns in the ai startups that blow up if you advise enough companies, take enough founder calls, watch enough launches, you start to see repeating structures here’s the blueprint all of them share: 1. a relentless launch cadence they never shut up one of my clients launched every wednesday higgsfield launches 2-3x/wk always manufacturing something to talk about 2. one channel = unfair advantage they’re active everywhere but one channel carries them 3. a founder who’s the face the founder is the loudest account in the company weekly podcasts. vlogs. clip & ugc farms people know the product bc they know the founder 4. volume over perfection they never post and chill out they tell the same story 100 times for every post that does 10k views, another does 10m 5. no fear of price the loudest ai companies don’t negotiate they spray higgsfield is a perfect example of crazy budgets 6. a second motion once plg breaks elevenlabs is around $500m arr i believe the first $300m came from plg the rest came from enterprise, now 50/50 ish 7. omnipresence over roi on most channels they stop asking about direct roi they ask how the whole entire planet hears abt them scroll anywhere & they’re there they think blended CAC growth at the highest level isn’t random it’s a pattern repeated by everyone with skin in the game once you see it. you can’t unsee it.

Marc最近收入过300万，大家都在吹他，我想分享一下我的看法: 我其实一直不太看好 Marc的创业打法，它有它的独特性，以及成功的巧合性，因为不少朋友是独立开发创业去做出海、做产品。 在推上看到它，很可能会心动，跟着它的方向去做。 但是我想跟大家泼一个冷水，就是不建议大家去模仿他。 比如说，我置顶的这个项目，就是为了证明outbid和Marc 又开始做的拍卖这种网红项目，而特意做的一个社会实验。 我就是想自己亲自实验一下: 即使在同样的时间跟他推出同样的项目，也不会成功。 他的打法是粉丝经济。说的不好听一点，就是向独立开发的创业者抛售一个独立开发能轻易成功，发一个产品就能迅速赚钱的梦: TrustMRR 公开数据里，Marc 累计约 $300 万。真正贡献大头的是： • ShipFast（$130 万）：卖给独立开发者的 Next.js boilerplate • CodeFast（$83 万）：教人「几天学会写代码、把 idea 做成生意」 • TrustMRR（$33 万）：独立开发者的收入公示 + 收购市场 • DataFast（$27 万）：给 startup founder 的收入分析 • Ship or Die（$11 万）：30 天必须上线的独立开发挑战 • IndiePage（$5 万）：独立开发者主页 这几项加起来大约 $290 万 / $305 万，接近 95%。他 2025 年 11 月自己也说过：CodeFast + ShipFast 曾经占月收入 90%。 不知道大家发现规律没有？他这个独立开发者的所有产品都是帮 独立开发者去进行独立开发的. Marc他确实做过姿势矫正、习惯打卡、语言练习册这类非产品, 这些产品才是大多数独立开发者想突然创业去做的心血来潮的项目。 他最开始也是这样的独立开发者. 但是你猜怎么着？ 即使像他那样, 做的这些产品几乎不赚钱。赚钱的，基本都围着同一群人转：想靠独立开发发财的人。 他也自己承认过：AI 已经打掉了 coding course 和 boilerplate。 现在能撑住的，是 TrustMRR / DataFast 这类「卖给 maker 的基础设施」，以及持续发收入截图带来的流量。 我对 Marc本人没有什么恶意，发这个帖子不是为了批判Marc。恰恰相反，我也其实很欣赏和钦佩Marc这样能够在独立开发这个赛道里面杀出来的人。 但是作为一个中推年纪稍微大点的人，我觉得有义务说下：最近看到太多的营销号吹捧，可能会误导刚刚后来一拍脑袋选择创业独立开发的年轻人。 所以还是想写点东西: 同时，我也想鼓励一下：如果你是在独立开发这条道路上挣扎着、迷茫着、徘徊着的人，不要被这些网红程序员天天截图的 MRR 误导了。他们本来就是靠这个截图获取流量、涨粉和飞轮增长的。 独立开发就是他的客户。没错，你就是他的客户，他就是发给你看的，让你崇拜的。 让你羡慕的，让你更加义无反顾地要加大投资去做独立开发的 。 而你的产品受众，如果不是独立开发，你就没有必要跟着他一起 building public。你吸引的都是同行。 你截图 MRR，只会让同行嫉妒，同时会有别人抄你站，你App的风险。 但是独立开发这条路还是可以走的，特别是在AI的时代，机会还是很多的。但需要埋下头来深耕你的niche，到你真正客户的地方去做宣传，而不要跟风网红程序员。他们不可复制。

I'm selling my body. On September 19th, I'm competing in my first HYROX race in Turkey. You can advertise your startup on 10 of my muscles: - Your website is listed on - Your logo will be tattooed on my body on race day - I'll share it on my YouTube and X accounts Bidding starts at $1,000. Each takeover doubles the price: $1,000 → $2,000 → $4,000. If outbid, you’re refunded minus the Stripe fee. Bidding closes on Thursday the 10th at midnight UTC (in 2 days), so I have enough time to print the winning tattoos. → Sponsor my body:

BREAKING: SpaceXAI has released a major new update for Grok Build (v1.0.14) Grok v1.0.14 is a reliability and workflow update for the Grok CLI. It makes OIDC token refresh proactive, lets PostToolUse hooks send feedback back to the model after tools run, adds per-turn token and cost tracking via grok usage, and cuts Windows downloads by about 70%, with a large set of fixes that tighten sandboxing, subagent handling, hooks, and startup. Features: • OIDC token refresh is now proactive by default for better reliability. • PostToolUse hooks can now provide feedback and context to the model after tool execution. • SDK-registered PostToolUse hooks now provide model-facing feedback. • grok usage now shows persisted per-turn token and cost data. • Retry status in composer and title now shows a short reason for the retry. • Models can now declare a different identifier for each reasoning-effort level instead of always sending the same id. • Prompt suggestions now respect remote configuration and default to the current session model. • Windows CLI downloads are now ~70% smaller using the same compressed sidecars as macOS and Linux. Bug Fixes: • grok inspect now correctly shows Claude bypass locks as advisory rather than enforced. • Subagent sessions no longer leak threads or file descriptors when the parent is busy. • Cold startup no longer performs duplicate remote settings fetches. • Compaction failures due to context size now degrade input instead of retrying identically. • --sandbox strict now restricts writes to ~/.grok/sessions only. • Subagent spawning now waits longer on a busy coordinator and shows clearer retry guidance instead of "unreachable". • Failed task and todo tool calls now appear in the transcript instead of disappearing without a trace. • Composer status row no longer collapses or flashes when using double-Enter to send now. • Session close is no longer delayed by a single slow hook; each SessionEnd hook now has its own timeout. • Hook removal in the extensions modal no longer offers actions that the handler will refuse. • Interjections during a turn are now delivered atomically or not at all. • Subagent tasks no longer get incorrectly cancelled when the parent session is waiting for completion. • Workflow detail view now closes the overlay on X or outside click instead of returning to the run list. • Resuming subagents now succeeds for larger transcripts that still fit the model context with headroom. Performance: • Startup now fetches remote settings only once per boot instead of potentially twice. • First message on large repositories no longer waits on repository status scan. • Large session memory no longer blocks the agent during turn completion or subagent spawning. • Signed-in CLI starts faster by serving remote settings from a local cache on warm boots. Download Grok Build: Update to the latest Alpha release: grok update --alpha Update to the latest Stable release: grok update