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热门科技推文 - 2026-06-07
- Authors
- Name
- geeknotes
2026年6月7日 科技每日简报
Today's top tech conversations are led by @MilkRoadAI, whose post about 'RT @MilkRoadAI: This is WILD! ...' garnered the highest engagement. Key themes trending across the top stories include models, spacex, billion, https, claude. The community is actively discussing recent developments in AI, engineering practices, and startup strategies.
1. MilkRoadAI (Group Score: 380.7 | Individual: 51.9)
Cluster: 11 tweets | Engagement: 394 (Avg: 56) | Type: Tech
RT @MilkRoadAI: This is WILD!
One week before SpaceX's historic IPO, Google signed a deal to pay SpaceX $920 million per month from October 2026 through June 2029 for access to 110,000 Nvidia GPUs, CPUs, and related infrastructure (Save this).
That is 30 billion over the life of the contract.
This comes less than a month after Anthropic committed $1.25 billion per month for full access to the Colossus 1 data center in Memphis, 200,000+ GPUs, 300+ megawatts of power capacity, through 2029.
Two of the most consequential AI labs in the world combined committed value over $70 billion.
The question that haunted SpaceX's IPO roadshow was why did Elon keep spending billions constructing Colossus, Macro Hard and Macro Harder, three facilities totaling nearly 2 gigawatts of AI compute when xAI's revenue wasn't yet on the same trajectory as OpenAI or Anthropic?
Wall Street was pricing in a risk that Elon was building capacity ahead of revenue which would mean sustained cash burn without a clear payback timeline.
That concern was legitimate on its face, because xAI had been aggressive on model development but had not yet demonstrated the enterprise revenue numbers to justify the infrastructure cost.
The answer is that the compute itself was always the product.
Amazon has AWS, Microsoft has Azure, Google has Google Cloud, Elon just confirmed that he has been quietly building the fourth major hyperscale AI cloud and his first two paying customers are Google and Anthropic, the very companies most aggressively competing in the AI race.
xAI's Colossus facility in Memphis was built at a speed that no traditional data center developer could match, it went from groundbreaking to operational in roughly 122 days.
That is what happens when you have direct Nvidia relationships, a construction operation built around SpaceX-style execution, and a founder who treats infrastructure buildout the same way he treats rocket launches: compress every timeline and eliminate every bottleneck.
The result is that SpaceX now has three operational facilities, Colossus, Macro Hard, and Macro Harder with Macro Hard and Macro Harder in Blackwell architecture running 1.2 gigawatts combined.
Colossus 1, built on H100s and optimized for inference, is the facility that went to Anthropic first.
The Blackwell-era facilities are where the next-generation training workloads happen and Google's deal suggests they are renting into that capacity as it comes online through the second half of 2026.
Elon's compute leasing business would generate approximately 20 billion range analysts had been modeling for SpaceX more than enough to fully subsidize the infrastructure investment and take the financial pressure off xAI delivering immediate AI product revenue.
That changes the entire valuation conversation of SpaceX completely!
Milk road remains bullish on Space and come join Milk Road Pro and get our full SpaceX IPO breakdown, how we're thinking about the $1.75 trillion valuation and our entire AI thesis. Link below!
See 10 related tweets
- @MilkRoadAI: RT @MilkRoadAI: Goldman Sachs just dropped the most precise map of where $7.6 trillion is going over...
- @aakashgupta: The SpaceX revenue ramp is wild.
In all of 2025, the entire company did $18.7 billion in revenue, m...
- @rohanpaul_ai: Rreuters: SpaceX’s 150B in demand (2x oversubscribed)
SpaceX has ...
- @BullTheoryio: BREAKING: SpaceX has announced a new deal with Google worth $920 million per month to provide AI com...
- @edzitron: One of the most important post bubble bits of regulation we need is the end of circular financing de...
2. chandrarsrikant (Group Score: 212.8 | Individual: 53.8)
Cluster: 8 tweets | Engagement: 9182 (Avg: 597) | Type: Tech
RT @BernieSanders: I will soon be introducing a bill to give the public a 50% ownership stake in the largest AI companies in America.
This would guarantee that the trillions created by AI are used to improve the lives of all of us — and block oligarch decisions that harm the American people. https://t.co/y3ERWOsRfs
See 7 related tweets
- @BullTheoryio: BREAKING: President Trump wants to give every American a piece of OpenAI, Anthropic, and xAI.
Speak...
- @StockSavvyShay: President Trump said the administration may consider taking equity stakes in U.S. AI companies.
He ...
- @Reuters: Trump says his team will 'look into' US taking stake in AI companies https://t.co/ZSSg1s8VGn https:/...
- @Forbes: Could Americans Build Wealth Through AI? Why Trump May Be Considering Equity-Sharing Scheme https://...
- @ohryansbelt: This is a great way to rebrand a government bailout of AI companies that realize they'll never turn ...
3. ReutersBiz (Group Score: 147.4 | Individual: 49.3)
Cluster: 5 tweets | Engagement: 918 (Avg: 17) | Type: Tech
WATCH: Donald Trump told reporters that his team might buy US stakes in artificial-intelligence companies and said he would host a meeting with AI executives as soon as next week https://t.co/leXlONTLFZ https://t.co/sU44wMYqn8
See 4 related tweets
- @KobeissiLetter: BREAKING: President Trump says the Trump Administration might buy equity stakes in US AI companies a...
- @Reuters: Donald Trump told reporters that his team might buy US stakes in artificial-intelligence companies a...
- @mikeallen: RT @danprimack: Source says he told Trump and Susie Wyles last week. Expect him to launch some sort ...
- @Mayhem4Markets: Bullish. Especially with the faberge egg dude in the background.\n\nQT @Reuters: Donald Trump told r...
4. NielsRogge (Group Score: 135.7 | Individual: 49.3)
Cluster: 4 tweets | Engagement: 552 (Avg: 71) | Type: Tech
RT @victormustar: Before the week ends, let's acknowledge one of the most INSANE week ever for open AI, with 25+ notable open-weight drops across every modality:
🧠 LLMs
→ NVIDIA Nemotron 3 Ultra: 550B hybrid Mamba-MoE, only 55B active, 1M context, MMLU 89.1. NVFP4 variant claims ~5x throughput on Blackwell. First openly-weighted 550B hybrid Mamba-Transformer, closing the gap with frontier closed models.
→ Google Gemma 4 12B: fully open dense any-to-any (text/image/audio/video), 256k context, encoder-free, 140+ languages, AIME 2026 at 77.5. Shipped with a 23-checkpoint QAT wave (mobile ONNX + MLX). Most deployable model of the week.
→ StepFun Step-3.7-Flash: 198B sparse MoE VLM, ~11B active, SWE-Bench PRO 56.3. Apache 2.0.
→ Liquid AI LFM2.5-8B-A1B: edge MoE, just 1.5B active, 128k ctx, MATH500 88.8, MLX-ready. Best on-device option this week.
→ JetBrains Mellum2-12B-A2.5B-Thinking: their first open MoE, near-Qwen3-14B coding at 2.5B active. Apache 2.0.
🎨 Image gen (the surprise of the week)
→ Ideogram 4: their FIRST-EVER open weights. 9.3B flow-matching DiT trained from scratch. #2 overall behind GPT Image 2, top open-weight model on Design Arena + LMArena. Strongest open checkpoint for text-rich images, full stop. It has taste. Still can't believe this is open weights.
🔊 Audio & Speech (a breakout week for open TTS, 4 labs shipped)
→ Boson Higgs Audio v3 4B: 102 languages, 21 emotions, singing/whispering/shouting, sub-second TTFA. → RedNote dots.tts: the only fully continuous (no codec) open TTS pipeline, Apache 2.0. → Google Magenta RealTime 2: real-time music gen, <200ms latency, text+audio+MIDI. multimodalart ported it to PyTorch within hours with live ZeroGPU demos. → NVIDIA Nemotron-3.5 ASR: 600M streaming, 17x more concurrent streams vs Parakeet RNNT 1.1B.
👁️ Vision & VLMs
→ PaddleOCR-VL-1.6: SOTA document parsing at 1B params, Apache 2.0. → Baidu NAVA: 6.3B joint audio-video gen, best-in-class A/V sync, Apache 2.0.
🎬 Video, 3D & World Models
→ NVIDIA Cosmos3-Super: 64B omnimodal world model coupling action trajectories with video+audio gen, for Physical AI. → JD JoyAI-Echo: up to 5-min multi-shot text-to-video on LTX-2.3. → ByteDance Bernini-R + VAST TripoSplat (single-image-to-3D Gaussian splats, MIT).
See 3 related tweets
- @gavinsbaker: Quite a week for open-source AI. Especially American open-source. Nemotron 3 Ultra is the most impo...
- @pmarca: Interesting.\n\nQT @victormustar: Before the week ends, let's acknowledge one of the most INSANE wee...
- @BrianRoemmele: I am up late catching up on 25! Open Source AI models released just this week!
Have our testing sys...
5. levie (Group Score: 116.1 | Individual: 33.5)
Cluster: 4 tweets | Engagement: 230 (Avg: 689) | Type: Tech
Token costs are becoming one of the hottest topics for any enterprise I talk with right now. It’s very bullish for AI in general because it means these systems are being used at a scale that wasn’t contemplated before.
It also gives way to another form of differentiation that will emerge for the applied AI layer, which is model routing.
As tokens take on a significant amount of the cost of any given workflow, then companies will inevitably want to ensure that their dollars go into the most efficient use of tokens for the particular job at hand.
Frontier intelligence will always be relevant at the high end of tasks, like coding, legal and financial analysis, healthcare, and more. And dollars spent here will only go up over time. But, equally, you can peel off individual tasks to lower cost models (whether they’re from open weights vendors or the major labs) and deliver a more efficient end outcome.
To do this effectively, the applied AI layer needs to understand the workflows in their domain better than anyone else, and be able to mix and match models to different jobs. If you’re doing document extraction, you need to know which models perform better or worse for any given document type. If you’re legal analysis, you want to know which models perform various types of tasks best. And so on.
This will become one of the bigger differentiation points over time. The companies with the best evals, the best ability to route the workloads, and those that have business models directly aligned to customers financial goals, will be in a great position.\n\nQT @chamath: Your margin is my opportunity: AI version…
The biggest surprise of 2026 is that the capability gap between the best open-weight/source models and the best closed models has narrowed much faster than the pricing gap. The pricing gap remains enormous while the capability gap is quite narrow.
What does this means in practice?
For a company consuming 1 billion input tokens and 1 billion output tokens per month:
GPT-5.5 Pro: ~30,000 DeepSeek V4 Pro: ~2,740
I asked ChatGPT what it thought about this and it answered as follows:
“If I were building a company today, the economic frontier would look roughly like:
DeepSeek V4 Pro / R1 for high-volume inference.
Claude Opus for premium agent workflows where reliability matters.
GPT-5.5 Pro only for workloads where its incremental capability demonstrably produces enough business value to justify a 20–40× token premium.”
Most CEOs have no idea that, instead of this nuanced approach, their teams are running amok internally by picking the most expensive models in most cases and burning through massive budgets with zero governance, audit ability and control.
As control planes like our Software Factory become more standard, you can expect the run rate revenue growth of the frontier labs to go down meaningfully and the revenues of the open models to skyrocket.
Why? Because we can implement the nuanced approach above and be agnostic to model - instead focusing on customer intent, model task and cost management among other things.
See 3 related tweets
- @danielnewmanUV: Brilliant take. Intelligence isn’t one thing. Model diversity will be a necessity as the infinite sc...
- @dee_bosa: RT @chamath: Your margin is my opportunity: AI version…
The biggest surprise of 2026 is that the ca...
- @edzitron: It’s actually bullish that it’s too expensive\n\nQT @levie: Token costs are becoming one of the hott...
6. sairahul1 (Group Score: 113.7 | Individual: 39.3)
Cluster: 4 tweets | Engagement: 112 (Avg: 78) | Type: Tech
Anthropic engineer:
"You're not supposed to watch Claude Code work. You're supposed to wake up and review what it shipped."
Most people use Claude Projects like a slightly better chat window.
They open it, ask something, get an answer, close it.
That is not a Project. That is a very expensive notepad.
The engineers who built Claude use it completely differently.
Persistent context. Custom instructions. Knowledge bases. Workflows that remember everything about your business — forever.
Here is the exact setup most users don't know exists ↓
Bookmark this. Read it before you open Claude today.\n\nQT @eng_khairallah1: https://t.co/WRWNtgam2L
See 3 related tweets
- @eng_khairallah1: RT @sairahul1: Anthropic engineer:
"You're not supposed to watch Claude Code work. You're supposed ...
- @Av1dlive: RT @Av1dlive: Anthropic engineer:
"You can build 5 assistants in one afternoon. Each one handles ...
- @cgtwts: RT @cgtwts: Anthropic engineers:
“You’re not supposed to watch Claude Code work. You’re supposed to...
7. mkratsios47 (Group Score: 111.6 | Individual: 28.0)
Cluster: 4 tweets | Engagement: 64 (Avg: 269) | Type: Tech
Congratulations @sriramk, and thank you for your service. Grateful for all the valuable contributions you made to the Administration’s AI agenda. We were lucky to have you on the team. Wishing you the best ahead!\n\nQT @sriramk: 🇺🇸🚀 SOME NEWS: I'll be leaving my role at the White House at the end of this month. After a break I’ll be working on helping tackle some of the large challenges facing America on AI (more on that later).
It is hard to express how big a privilege it has been to serve the American people and how grateful I am to have had the opportunity to do so.
First and foremost, it has been an honor to serve under President @realDonaldTrump . Without his leadership, we would not be leading in the AI race.
Second, I owe a lot to the person I’ve worked mostly closely with over the last 18 months - @DavidSacks . His continuing advocacy for America winning on AI has been and continues to be crucial.
Some key public accomplishments from last year I’m proud of
Architecting and publishing the American AI Action Plan - charting the course for America to win on AI and helping execute on that for the last year.
The AI acceleration partnerships to help American AI stack win globally.
The National AI Policy Framework for Artificial Intelligence executive order (forming the basis for working with the Hill this year)
Advocating for the American AI stack with our allies globally (the AI summits in France and India, state visits to the UK, the Middle East and more)
So what’s next?
The past 18 months have given me a front row seat to this critical moment on AI facing America and our allies. Whether it is energy, data centers or a clear path for Americans to experience the benefits of AI, there are many tough issues we all need to navigate together. I plan on building institutions that help tackle some of those challenges for America and its allies.
I want to thank many others who have helped along the way in the administration : Kevin Hassett, @mkratsios47 , CoS @SusieWiles47 , VP @JDVance , @StevenCheung47 , Sec Bessent, Sec Lutnick, Sec Rubio and @jacobhelberg , @USWREMichael , Josh Gruenbaum, Watson Fagan, Ryan Baasch, Jeff Kessler, Alexei Bulazel, DepSec Landau, DepSec Dabar, Will Scharf, Taylor Budowich, @JamesBlairUSA , @elonmusk and many, many others. You know who you are and I know I’ll continue to see you a lot more.
Most of all, I want to thank @aarthir on supporting everything and being part of this unexpected but amazing journey from last January. None of this would be possible without her.
This journey has been the privilege of a lifetime and shown me how special this country is and how it needs all of us to contribute in anyway we can - and I plan on continuing to do just that.
🇺🇸
See 3 related tweets
- @gokulr: Congrats @sriramk and thank you for your service and for your leadership in crafting our AI policy. ...
- @TrungTPhan: RT @sriramk: 🇺🇸🚀 SOME NEWS: I'll be leaving my role at the White House at the end of this month. Aft...
- @PatrickMoorhead: I hope we get more in-industry tech folks in and around the administration to make things happen at ...
8. aakashgupta (Group Score: 94.4 | Individual: 37.0)
Cluster: 3 tweets | Engagement: 29 (Avg: 49) | Type: Tech
Shipping a mobile app got dramatically easier in 18 months. The payoff for shipping one fell by half.
Agentic AI collapsed the cost of writing code, and app releases jumped roughly 80% off the 2024 baseline. But code was always the cheap part of building a product. The expensive part was getting a human to open the thing twice, and that number didn't move at all.
Run it. Releases up ~80%. Apps with real usage: flat. App reviews down ~20%. So reviews per release fell more than half. The average app shipped today pulls less than half the attention the average app pulled before the boom.
Attention is fixed. There are only so many hours of human screen time, and AI does not manufacture more of them. Drop the cost of supply to near zero while demand stays flat and you don't get more winners. You get a longer line for the same prize.
Distribution, retention, and knowing what to build were always the parts that decided whether a product lived. A coding assistant touches none of the three.
Scarcity moved. Anyone can produce now. The rare thing is being the one app out of 180 that someone still opens on Tuesday.\n\nQT @jenzhuscott: Massive output uptick due to agentic AI. Complete flat adoption. https://t.co/s6ubPsy0SL
See 2 related tweets
- @seraleev: 1. AI dramatically simplified app development.
- App reviews have fallen by ~25%.
- User attention...
- @DataChaz: “Attention is all you need.”
and with agentic AI, shipping an app is now basically one click away. ...
9. bcherny (Group Score: 91.2 | Individual: 28.1)
Cluster: 4 tweets | Engagement: 9000 (Avg: 4833) | Type: Tech
RT @AnthropicAI: Our internal data shows Claude is accelerating AI development—a possible path to recursive self-improvement, or AI autonomously building a more capable successor.
It’s happening faster than we thought, and the implications deserve greater attention. https://t.co/OVVPJO7VQx
See 3 related tweets
- @robertwiblin: Building the Torment Nexus to get it regulated. https://t.co/izDH63QQDp\n\nQT @AnthropicAI: Our inte...
- @DataChaz: RT @DataChaz: 🚨 Dario confirmed that Claude is currently designing the next version of itself.
To t...
- @WesRoth: RT @WesRoth: Anthropic published new internal data suggesting Claude is accelerating AI development ...
10. garrytan (Group Score: 83.2 | Individual: 31.5)
Cluster: 3 tweets | Engagement: 194 (Avg: 167) | Type: Tech
You can now finally try one of those big projects I was teasing that I started working on a few months ago.
We want this to over time get better at helping you learn the best techniques to build better software, faster.\n\nQT @ycombinator: Today we're launching Paxel: a free tool that analyzes your Claude, Codex, and Cursor coding sessions and gives you a profile of how you build with AI.
It runs locally inside Docker, and your code never leaves your machine.
Try it at https://t.co/HqSHneQSTQ https://t.co/ykmg52NLDR
See 2 related tweets
- @garrytan: RT @ycombinator: Today we're launching Paxel: a free tool that analyzes your Claude, Codex, and Curs...
- @ohryansbelt: Mogged by community note\n\nQT @ycombinator: Today we're launching Paxel: a free tool that analyzes ...
11. GergelyOrosz (Group Score: 82.4 | Individual: 49.4)
Cluster: 2 tweets | Engagement: 3690 (Avg: 663) | Type: Tech
Just learned:
Software engineers used to do manual data labeling at Scale AI while Alex Wang was CEO. After he left, new leadership joined, and were HORRIFIED to learn this. Stopped it ASAP
Now at Meta, software engineers are assigned manual data labeling... see the pattern?
See 1 related tweets
- @chris_j_paxton: I don't think the lesson here is "engineers shouldn't be labeling data"\n\nQT @GergelyOrosz: Just le...
12. TFTC21 (Group Score: 82.3 | Individual: 34.0)
Cluster: 3 tweets | Engagement: 68 (Avg: 51) | Type: Tech
Trump wants the government to take equity stakes in AI companies and send dividends to Americans.
He's meeting with AI leaders at the White House next week.
The government becoming a shareholder in private companies should make everyone uncomfortable. https://t.co/x8TaMQH69i
See 2 related tweets
- @altcap: When gov’t owns / controls the means of production it is socialism. I don’t trust shares in the hand...
- @rohanpaul_ai: FT: Trump administration, OpenAI discussing possible government stake in the AI startup.
OpenAI has...
13. gregisenberg (Group Score: 81.7 | Individual: 35.1)
Cluster: 3 tweets | Engagement: 73 (Avg: 917) | Type: Tech
The most comprehensive Hermes Desktop tutorial on the internet NOW is LIVE.
You'll learn sessions, profiles, artifacts, cost savings, and real use cases for making money and building startups with Hermes agents.
Whether you're already running Hermes or haven't started yet, this is the episode for you.
@AlexFinn says this is the moment Hermes overtakes OpenClaw. S/o to Alex for walking me through it.
"It's now the best way to use AI agents on your computer"
I do think the desktop app of Hermes looks almost like an Apple product.
Everything you need to know about Hermes Desktop App/agents in 43 minutes
This episode is 100% free. No ads. @startupideaspod
I just want to see you win on the internet. And I think Hermes can help.
Plus, It's fun thing to play with this weekend. Share this with a friend. Link below.
Watch
See 2 related tweets
- @Teknium: RT @akshay_pachaar: The Hermes Desktop App is insanely good.
It's now the best way to run AI agents...
- @Teknium: RT @iamlukethedev: Hermes Agent v0.16.0 (2026.6.5) just dropped
This is arguably the biggest Hermes...
14. eng_khairallah1 (Group Score: 79.2 | Individual: 29.7)
Cluster: 3 tweets | Engagement: 210 (Avg: 77) | Type: Tech
RT @eng_khairallah1: Anthropic engineer:
"You can build 5 assistants in one afternoon. Each one handles a task you've been doing manually every single day."
this is one of the best workflows I've seen in a long time
in this video he breaks down exactly how most people are using Claude:
- the 14% you lose to CLAUDE.md before typing a word
- the plugins that 95% of users have never installed
- the workflows that run without you typing a single prompt
- why starting every chat from zero is the slowest way to use Claude
if you've been starting every Claude conversation from scratch like it's never met you before, you're missing at least 20 features. probably 24
instead of another show tonight, watch this
make sure to bookmark it before it gets lost in your feed
the guide is in the article below
See 2 related tweets
- @eng_khairallah1: RT @eng_khairallah1: Boris Cherny, the creator of Claude Code at Anthropic, just explained why he st...
- @eng_khairallah1: RT @eng_khairallah1: Anthropic engineer:
"You're not supposed to prompt Claude. You're supposed to ...
15. abacusai (Group Score: 75.1 | Individual: 28.2)
Cluster: 3 tweets | Engagement: 5 (Avg: 375) | Type: Tech
🚨 Agent Swarm - Build A Billion Dollar Consumer Business On The Abacus AI Super Computer!
Create multi-agent swarms using top models including Opus 4.8, Gemini 3.5 and GPT 5.5
Each worker agent excels at different tasks - front-end coding, back-end coding, testing, mobile app, research and monitoring
Master agent orchestrates worker agents - use english to instruct the master
See 2 related tweets
- @bindureddy: 🚨 AGENT SWARMS V2 - RUN MULTIPLE SMALL AGENTS IN PARALLEL
Introducing the next generation of Agent...
- @abacusai: 🚨 AGENT SWARM FOR CODING - PARALLEL AGENT EXECUTION
Create multi-agent parallel swarms orchestrated...
16. business (Group Score: 72.1 | Individual: 49.0)
Cluster: 2 tweets | Engagement: 802 (Avg: 78) | Type: Tech
Elon Musk will virtually attend a closed door technology conference run by ASML to discuss his Terafab project, which the chip-equipment maker considers a “serious endeavor.” https://t.co/uuYSQeFXbz
See 1 related tweets
- @StockMKTNewz: ELON MUSK WILL VIRTUALLY ATTEND A CLOSED-DOOR ASML $ASML EMPLOYEE CONFERENCE TO DISCUSS TERAFAB
Her...
17. BanghuaZ (Group Score: 70.0 | Individual: 35.6)
Cluster: 2 tweets | Engagement: 37 (Avg: 17) | Type: Tech
Agents providing improvements in production environments with SGLang. Very cool work!\n\nQT @InfiniAILab: 🌀 Introducing Vortex — sparse attention designed by AI agents, efficient at scale.
📈 Same accuracy, way more throughput — across every model we tried 👇 🔹 GLM-4.7-Flash (MLA) → 4.7× faster 🔹 MiniMax-M2.7 (229B) → 1.37× faster 🔹 Qwen3-1.7B (agent-discovered!) → 3.46× faster
🤖 How? An agent writes a flow in a few lines of Python; Vortex compiles it into fused kernels in a real serving stack (SGLang) and benchmarks it end-to-end.
🏗️ The design: a Python frontend (vFlow) over a page-centric tensor abstraction (vTensor) + a serving-integrated backend.
📄 https://t.co/gZSPl7PXVp 💻 https://t.co/awlislOZWw 🌐 https://t.co/EBWbTObQbb 📚 https://t.co/apTWhIGD1M
See 1 related tweets
- @lmsysorg: We're excited to see Vortex built on SGLang! By integrating directly into the serving stack, Vortex ...
18. sairahul1 (Group Score: 69.6 | Individual: 38.3)
Cluster: 2 tweets | Engagement: 74 (Avg: 78) | Type: Tech
A guy built a system of 7 Claude agents on his MacBook.
No assistant. No sales team. No office.
Every day it scans Google Maps across 3 cities, finds small businesses with no website or one from 2014, builds a landing page mockup, renders a 10-second video of it, and sends a personalized cold message — before he wakes up.
47 clients a month. $400 each.
480 in API costs.
Traditional web agencies run 8-person teams for the same order flow.
He runs it alone from a MacBook and an iPhone.
When a positive reply comes in while he's in a taxi, his Mobile agent books the Zoom call. He taps "approve" and joins 10 minutes later.
The only time the system wakes him is when a deal breaks $3,000 or the reply rate drops below 12%.
Everything else runs without him.
Here's the complete playbook for building such $10K/month passive income machine with AI ↓\n\nQT @sairahul1: https://t.co/fgPRB2Dmr0
See 1 related tweets
- @sairahul1: RT @sairahul1: A guy built a system of 7 Claude agents on his MacBook.
No assistant. No sales team....
19. OfirPress (Group Score: 68.7 | Individual: 34.2)
Cluster: 3 tweets | Engagement: 1566 (Avg: 182) | Type: Startup
RT @jenzhuscott: Massive output uptick due to agentic AI. Complete flat adoption. https://t.co/s6ubPsy0SL
See 2 related tweets
- @zoink: When execution is cheap, design and creativity are the edge.\n\nQT @jenzhuscott: Massive output upti...
- @GEVS94: “Taste”\n\nQT @jenzhuscott: Massive output uptick due to agentic AI. Complete flat adoption. https:/...
20. paulg (Group Score: 68.1 | Individual: 31.6)
Cluster: 3 tweets | Engagement: 1275 (Avg: 2350) | Type: Tech
Curiously enough I did office hours today with a startup that cuts companies' LLM token costs by optimizing requests. They can cut costs by about half, which they split with the customer. So the TAM is a quarter of the model companies' corporate revenue. That's a big TAM!\n\nQT @paulg: If big companies can't make a net return on their LLM token costs, that doesn't mean it's impossible to. In fact this is exactly what you'd expect to happen with a new technology. Incumbents can't use it well, and are replaced by upstarts who can.
See 2 related tweets
- @matteocollina: RT @paulg: If big companies can't make a net return on their LLM token costs, that doesn't mean it's...
- @ycombinator: RT @paulg: Curiously enough I did office hours today with a startup that cuts companies' LLM token c...