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!
Replying to @MaxAnderson
1000% this. Even with competitor names in a negative list I was being charged crazy cost per click for terms that were clearly seeking contact details for that competitor. They were all triggered by exact match and labelled “close variant”.
I’ve gave up on google now.
1. Homeowners track their estimated home values on Zillow and Redfin religiously
2. Those value estimates are based on recent historical comps of closed transactions
3. The market is frozen so those value estimates aren’t moving down to the true price at which the market would actually clear for a net-new listing put on the market today
4. High overlap between homeowners and stock owners, wealth effect means most homeowners dont *need* to sell. It would just be nice to sell if they could get the high price they think their home is worth
5. Due to frozen market and lack of recent comps to adjust value estimates down, homeowners believe their home is worth more than it actually is, and are enticed to list for “nice-to-have” sales at artificially high list prices
6. Due to overpriced listings the market stays frozen and the cycle reinforces itself
7. A small portion of buyers who *have to* buy do transact at those artificially high prices because they have no other choice
8. This provides just enough signal to keep the value estimates pinned artificially high
Cycle probably won’t break until homeowner move from “it would be nice to sell if I can get this price” to “I have to sell at any price”.
Which likely needs a stock market crash or recession
In the meantime prices will stay high but liquidity very low
Sell your house and move into an office building
JUST IN: A 95k sq ft office building in the heart of DT Denver is set to sell for $2.7M - an INSANE $28 per sq ft
It last sold for $24.5M in 2018 - a staggering ~90% discount in 8 yrs
Here's the crazy part:
The building underwent major upgrades recently, w/ 5 of its 7 office floors already built out and move in ready
And the property sits directly on Denver's iconic 16th Street corridor, which just underwent a $175M renovation
Denver's office market is truly experiencing an apocalypse
Stay tuned and follow for more updates on the office market meltdown
Housing prices are primarily driven by:
1. supply vs demand (demographics)
2. interest rates
Re: supply vs. demand
- US population is growing at 0.5% YoY and decelerating
- US housing supply is growing at 1.0% YoY and accelerating
Re: interest rates
- The US government has $40 trillion of debt growing 7% YoY, against $5.4 trillion of income growing 3% YoY
- Debt-to-income ratio of 772%, going to 800%+ next year
- Any corporation with 800% DTI would be considered distressed "junk bond" debt, C or CC credit rating
- The free market prices such assets around 17% interest rates today
"but acktually the US gov can print $ to pay its debt and can force certain price-incentive entities to buy so deserves a better credit rating than a corporation in the same position"
Yes. But to the extent it actually does print $ to pay down the debt, the market responds by selling off bonds, thereby driving up rates, thereby forcing even more printing, in a negative feedback loop that ends in hyperinflation
Meanwhile the share of price-insensitive buyers in the Treasury market is continuing to drop precipitously
As those dynamics play out the price the US gov has to pay on its debt will increasingly approach the price the free market would demand from any borrower with the same creditworthiness
Iotw if you think interest rates are going down over the coming years (let alone decades) you are smoking crack
Buying a home today is financially retarded
This is life changing
introducing FindMyWifePhone™️ my latest shortcut squarely placed on the pareto frontier. there is no easier & cheaper way to find your wife's phone.
"honey, do you know where my phone is?"
the fuck I dont!
"can you call me?!"
she keeps her phone on silent.
so i made this shortcut to help.
trigger = i send her a text with !ping in it
action = hey phone sets a timer for 1s
timer always works, we like to keep our phones on silent + dnd and we dont use apple watches. so finding each other's phones used to be a challenge. we both have this set up in reverse, and its worked well.
bonus shortcut = button in home screen widget to send !ping to my wife
(we also have one called !awaken which disables silent, sets volume to max & disables do not disturb in case of emergency)
Hamilton Helmer's 7 Powers is still the bible on moat-building
Almost none of these are negatively impacted by AI:
1. Scale economies
2. Network effects
3. Switching costs
4. Brand
5. Counter-positioning
6. Cornered resource
7. Process power
AI does slightly erode:
- switching costs via making it easier to batch copy your data and settings out of one system and into another. But you can still create and expand very real switching costs.
- cornered resource, to the extent the cornered resource was code or expertise. What remains in cornered resource are things like patents, legal/regulatory moats and mostly importantly, proprietary distribution + distribution deals/relationships. These are still enormously powerful.
- process power, to the extent portions of your process have leaked into the public domain or LLM training datasets, or can be done more efficiently now with agents. This can be largely defended by running self-hosted & open source models.
While on the other hand:
- AI makes it easier than ever to create new business models that are counter-positioned against large incumbents
- Scale economies, network effects, and distribution advantages are more important than ever
- Brand is likely to matter more, not less, in a world where consumers and businesses are inundated by AI slop
🤖 Made with AI
Here's how to turn an iPhone into the most secure crypto wallet. 10 steps:
1. Buy the cheapest new iPhone (17e, $699 in the US). Never used.
2. New Apple ID, fresh email, unique password
3. Face ID off. Custom alphanumeric passcode, 12+ characters
4. Lockdown Mode on
5. Erase data after 10 failed passcode attempts: on
6. iCloud backup off, before you install anything
7. Install the wallet from its official site and check the publisher
8. Generate a new address. Write the seed phrase on paper or steel. Never photograph it
9. Send a small test amount first, then move everything
10. Airplane mode, no SIM, no Wi-Fi ever again. Phone in a safe, seed in a different place
Skip step 6 or step 8 and the whole setup falls apart.
🤖 Made with AI
oh my god this is worse than we thought
here's @Ledger $86M exploits explained
> cryptobilis was a reputable and authorized Ledger/Trezor/OneKey dealer for over 4 years
> they decided to sell the company to a Chinese guy (most likely patsy for DPRK) from northern China in MARCH 2026
> the "Chinese guy" modded the devices within the supply chain itself (physical), namely Nano X devices, to contain an implant module
> ledger validity/genuineness check CANNOT detect this because hw wasn't actually tampered with, just spied on
> quoting @MagicalTux:
" implant just monitors what's shown on the screen, will take note of the seed as it's shown to you, then transmits it to 3rd party"
> former owner chimes in on X (pic below) to say that "they were under a NDA" to not mention anything to anyone for 6 months
> they obviously didn't alert any of their partners that they were authorized to sell devices of... because NDA, duh!! its in the name!
> conveniently, funds start getting siphoned a few weeks before this magical NDA due date, and being laundered across all blockchains

























