Just launched SweetValueLab on @RankInPublic! Analyze free stock valuations, reverse DCFs, and 13F data to see what growth each price is assuming. Come check us out and vote!
rankinpublic.xyz/products/sw…
Allen retweeted
As someone who has personally spent $500k / mo+ on Google Ads for years, I can tell you with certainty:
This revenue growth in Search is artificial & extremely unhealthy for Google’s business long term
Search volumes are declining as legacy search is being increasingly cannibalized by non-monetized LLM queries
Google’s response?
Manufacture revenue growth via short-sighted, highly extractive, customer-hostile tactics. I.e. charge advertisers more for lower quality clicks, including clicks they do not want and explicitly did not approve Google to charge them for
A few examples to illustrate:
For all of its history until recently, Google operated on a 2nd price auction model
I.e. if you bid $5 CPC and the next highest bidder bids $1 CPC, Google charged you $1.01 for the click (one penny more than the 2nd highest bidder) rather than the $5 you bid
This was a genius move by Google early on as it incentivizes advertisers to input their true maximum willingness to pay rather than trying to play the game of bidding low and constantly adjusting to try to stay just ahead of the next highest bidder while still not paying too much
However recently, Google silently deprecated the 2nd price auction and began charging advertisers as much as their bid and budget caps allow, regardless of what anyone else is bidding
It’s a short-sighted cash grab at the expense of the long term health of the advertiser ecosystem
Making thing worse, Google also recently nerfed keyword targeting precision
Google previously had precise keyword targeting settings that allowed advertisers pick individual search phrases to bid on, defined down to the character w/ exact match or phrase match targeting
This was one of the core features that made search advertising magic, enabling advertisers to run extremely precise campaigns based on exactly what their target customer typed
But now, even if you bid on a specific term or phrase using the strictest exact
-match targeting settings, Google will show your ad across 1000’s of unrelated keywords, labeling them as as “exact match (close variant)”
The definition of “close variant” means whatever they want it to and changes constantly. The result is advertisers get billed for clicks that are totally irrelevant to their business and that their targeting settings explicitly forbid Google from targeting. Google does it anyway and there’s no ability to turn this off
So now exact match is broad match, and broad match is just meaningless spam
This is all very bad for advertisers, but for Google, it allows them to show your ad and bill you for clicks across 1000x more searches that were previously going unmonetized (mainly because they’re garbage queries no one wants)
This is how you grow revenue atop declining search volumes
Lastly, and perhaps most egregiously, Google quietly stopped respecting budget caps by a factor of 2x. For example campaigns we’ve been running for years with $1000 daily budget caps suddenly began spending $2000+ per day
And the extra spend is entirely on the garbage keywords Google arbitrarily throws in as “exact match (close variants)” which have no value to our business, but can’t be turned off
Google offers no refunds nor any recourse for overspend or spend on keywords you explicitly did not target
These are not the actions of a healthy business. These are the actions of company whose core business is in decline but desperately needs to pump quarterly earnings so Wall Street will continue to fund insane capex while hopefully looking through their rapidly deteriorating negative free cash flow
Google operated a benevolent monopoly for the better part of 25 yrs
Meaning the value Google captured from Search was but a small fraction of the value it created, and that spread produced a potential energy that justified expectations of high earnings growth far, far into the future
This is now no longer the case
At the alter of AI capex, Google is sacrificing the golden goose
Q2 was an amazing quarter, with our AI investments redefining what’s possible across every part of our business.
Alphabet revenue grew 24% YoY and Google Cloud accelerated to 82% growth. We saw exciting momentum across the board from Search to YouTube to the Gemini app (which reached 950M monthly active users). Our model APIs are processing 22B tokens/min (up from 16B+ last quarter) driven by our workhorse Flash models. We’re also seeing great adoption of Gemini Enterprise, used by 90% of the Fortune 100, as well as strong demand for our security solutions.
Outstanding results and momentum, and such an exciting moment—thanks to all of our partners and employees around the world! 🙌 About to hop on the call!
$KO Coca-Cola raised its 2026 guidance again this morning.
Q3: unit case volume +5%, comparable EPS $0.91 vs $0.88 expected, revenue $13.38B (same as Q2, to the million).
Comp EPS growth guide: 9–10% → at least 11%.
North America volume: flat.
sweetvaluelab.com/blog/coca-…
$MCD 麦当劳今年跌了 18%,但过去一年它的 EBITDA 还涨了 7%。跌下来的是估值:EV/EBITDA 从 5 年中位数 17.9 倍降到 14.4 倍,比过去 5 年任何一个季度末都低。
我们把 10 家美国快餐股做成了一个等权指数,从 2021 年起算到今天,只涨了 6%。
sweetvaluelab.com/tools/rest…
Anthropic's S-1 is public: $11.6B of revenue in Q2 2026 and its first quarterly operating profit, $974M. The $80.7B first-half net loss is mostly a fair-value charge. sweetvaluelab.com/blog/anthr…
Anthropic is in talks with Nscale for a second ~$45B data-center deal (Bloomberg).
On August's six-year terms, that's ~$90B with Nscale, or ~$15B a year.
Q3 revenue annualises to $67.2B, so that's about 22% of it.
The revenue math: sweetvaluelab.com/blog/anthr…
AI bubble pressure today: 85/100, Extreme. Is AI a bubble? A daily 0–100 score of how stretched the AI build-out is against its own history: 13 indicators on capex, debt, payback and chip suppliers, plus a circular financing chart.
sweetvaluelab.com/tools/ai-b…
EE 新政是 IRCC 用"高薪职业名单"代替了"逐个劳动力市场测试",赌的是高薪岗位天然难以造假,再加上事后撤销 PR 形成威慑。这个赌注能不能成立,取决于两件事:一是审核官员能否真正核查 offer,二是事后执法有没有力度。
这个改动同时让"本地劳动力保护"这一环消失了。
$JPM trades at 3.10× tangible book on a 23.0% return on tangible equity.
$CITI.NE : 1.45× on 12.0%.
$ZION : 1.39× on 17.9%, 35% below the board's theory line.
23 US banks, one formula, Oct 13 close: sweetvaluelab.com/tools/bank…
$10,000 in SCHD ten years ago, dividends reinvested: $33,547 today.
The same $10,000 in SPY: $42,803.
Rebuilt my free backtest this week. Daily prices, real dividends, and now you can add money every month. No sign-up.
sweetvaluelab.com/tools/port…
Allen retweeted
美国家庭几年亏掉上百万会怎样?
推荐三部电影,就知道答案了:《无依之地》《老无所依》《赴汤蹈火》。
《无依之地》讲的是 2008 年金融危机余波中,内华达一座小镇工厂倒闭,人去镇空。女主角开始了边打工、边西行的公路生活:在亚马逊仓库打包,在旅游景点的餐厅帮厨,在营地当临时管理员……
《老无所依》里,德州一个越战老兵外出打猎,撞见一场火并后的现场,几具尸体、几包海洛因,还有 200 万现金。他决定拿走现金、改变生活,却被杀手一路追杀。当地的老治安官一路追踪,最终也没能救下他。结尾,老治安官讲起父辈荣光,感慨老无所依。
《赴汤蹈火》,故事同样发生在德州。主角是两兄弟,一个勇武有前科,一个离异有孝心。为了赎回家族农场,他们联手抢了一连串银行,而被抢的,正是那家用贷款套住农场的银行。
最后,也是一位快退休的老警察,一枪击毙了有前科的哥哥,弟弟侥幸逃脱。
三部电影,三个走投无路的普通人,两个追不上时代的老警察。所以,美国家庭几年亏掉上百万会怎样?
答案是铤而走险,亡命天涯。
Allen retweeted
摩根士丹利刚发布了一年一度的选股名单Vintage Values 2027,去年淘汰得只剩3只,又新增12只
我总结了一下变化(相比2026):
保留:
$AMZN(亚马逊)电商+云算力
$MCK(McKesson)医药分销$V(Visa)支付清算
移出:
$MSFT(微软)软件+云服务
$META(Meta)社交+AI模型
$PANW(Palo Alto Networks)网络安全
$WDC(西部数据)存储硬件
$SPGI(标普全球)金融指数与数据
$KKR(KKR)私募股权
$BSX(波士顿科学)医疗设备
$THC(Tenet Healthcare)医院运营
$WMT(沃尔玛)零售超市
$RTX(雷神技术)航空防务
$ETN(伊顿Eaton)工业电气
$NEE(NextEra Energy)公用事业+新能源
$EQT(EQT)油气开采
新进:
$GOOGL(Alphabet谷歌)互联网+AI算力
$AAPL(苹果)消费电子
$DT(Dynatrace)软件可观测性
$EQIX(Equinix)数据中心+算力基建
$KEYS(是德科技Keysight)电子测试测量仪器
$LPLA(LPL Financial)独立券商平台
$TRU(TransUnion)个人征信
$LLY(礼来)生物医药
$KO(可口可乐)消费饮料
$FWONK(Liberty Formula One)F1赛车+传媒
$HONA(霍尼韦尔航空航天)航空航天防务
$WMB(Williams)天然气管道
Allen retweeted
We'll be spending a lot more time trying to understand the outputs of language models. A few thoughts, tips & tricks:
Writing. Something I've had success with: Ask your LLM to explain something in ASD-STE100, it's a controlled language specification originally developed for aerospace maintenance documentation. LLMs well-versed in this language and it comes with heavy constraints on clean writing style that I often find a lot more readable. Sometimes I've tried to soften it a bit e.g. ask for "80% of the way to ASD-STE100" because the spec is quite stringent. But even better:
Diagrams / images. Instead of writing, ask your LLM to create a diagram. These can be a lot easier to process, parse, and understand. But even better:
Web pages. Ask for output "in HTML" to get a beautiful, interactive webpage. LLMs are getting really good at frontend and can create beautiful experiences, animations, etc. But even better:
Explainer videos. The output format I am most bullish on is fully custom / bespoke explainer videos generated on any arbitrary topic. Experiment with things like "Create a 3b1b style video explainer on X. Use my ElevenLabs API key for audio narration". (you'd need an API key for the latter or you can ask your LLM to find you decent free alternatives that use your local compute). This is actually starting to work!
In summary:
- As LLMs get better, they will do more and more of the legwork autonomously, and a lot more of our work will rise up the abstractions into oversight and understanding.
- Luckily, LLMs can help here too because as intelligence and code are increasingly abundant, you can ask for large, custom, discardable software artifacts (e.g. web apps, video explainers) that would have never made sense to create before. Push the boundaries here and you'll be surprised.
做了个特斯拉分部估值工具,把公司拆成汽车、储能、服务、FSD、Robotaxi、Optimus 六块分别估。
结果是:悲观每股 $23,中性 $97,乐观 $540,现价 $364。
按现价倒推,市场在押 2030 年有 190 万辆 Robotaxi。
所有假设都能自己改,欢迎拍砖 👇
sweetvaluelab.com/stocks/tsl…
How to value a software company: Rule of 40 and SBC
sweetvaluelab.com/blog/how-t…
Allen retweeted
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