I build stuff.
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Joined February 2011
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This is the ridiculous line to get into the @AnthropicAI event at @SFTechWeek
This is the third event this week where the line is longer than the event itself.
I guess the agi people never learned how to plan something that involves actual human people.
We pointed our audit at a DTC brand most operators would call sharp: clean site, strong loyalty program, real budget behind promotions and member perks.
It came back 40 out of 100, with about $775K a year in modeled exposure: value the brand actively funds that AI shopping agents never see.
What stood out is how typical that is. The better your incentive machinery, the more of your value is invisible by default, because you have built more things an agent cannot read. The store with no loyalty program has less to lose. The brand running tiers, points, and funded seasonal deals has its advantage sitting in the dark.
Today the Agentic Value Audit is live. Point it at your store and you get:
- Your score out of 100 on the Share of Algorithm framework (Visibility 32, Accessibility 18, True Value 50)
- Where the points leak, ranked by what each fix recovers
- The modeled dollar exposure sitting behind the gap
How it works: 24 live ChatGPT shopper queries in your category, plus a full crawl of your site, reading exactly what an agent can read.
Each True Value dimension is scored twice: what your pages encode, and what agents actually said. Those two disagree constantly, and the gap between them is the diagnosis.
Free, with no email gate between you and your number. You see your score before we ever see your name.
If you run Profound or Bluefish, keep them. They track whether you are mentioned. This measures whether your price, member value, and deals survive when you are.
And for the gaps that need encoding, we built TrueSync. It declares your member value and live deals into the standards agents transact on, so the value you already fund stops evaporating on the way to the customer.
Run yours at audit.parleo.io (link in the comments). If the report gets something wrong about your store, tell me. That is the comment I want most.
ALT Audit results show a 40/100 score for a beauty brand, highlighting low visibility and potential recoverable value of $18.4M.
Ask ChatGPT to find the best deal on something you sell.
For most brands it quotes the list price, the worst number on the page, to the exact shopper you built member pricing for.
We ran our benchmark on the grooming category, and 1 in 31 AI mentions of the category leader cited any incentive at all. The deals are live and funded. The channel cannot see them.
Commerce has seen this movie three times, and it always ends the same way: somebody names the new score, and the budgets follow it.
When the fight was for physical shelf space, Share of Shelf became the number everyone managed to, and an $8B measurement industry grew up around counting facings.
When broadcast made attention the scarce thing, Share of Voice did the same, $12B+.
When discovery moved into a search box, Share of Search became the metric underneath $200B+ a year of spend.
Every time the shelf moved, the old metric stopped explaining who wins and a new one took the budget.
The shelf is moving again, toward what McKinsey sizes at about $1T of US agentic retail by 2030, and this shift has no score yet.
So today we are naming the fourth one:
Share of Algorithm, 100 points, three pillars, nine dimensions, one straight sum.
**Visibility (32 pts):** are you in the room when shoppers ask? Today's GEO tools track this well. Keep them.
**Accessibility (18 pts):** can agents get in and parse what you sell? Table stakes, mostly a checklist.
**True Value (50 pts):** does the value behind your price survive into the answer? Price truth, member value, deal citability, value protocols. Nobody else measures any of this.
Half the score sits on True Value on purpose. The first two pillars decide whether you show up. The third decides what the agent says your product costs, and that is where the money is:
$200B+ of US trade promotion and ~$69B of retail media a year, funded to move shoppers, evaporating before it reaches the channel where the most price-motivated shoppers now start.
Two pillars are table stakes. The third decides whether your value reaches the answer.
The full framework is public today, every point inspectable, link in the comments.
Tomorrow we're launching a powerful way for a brand or store to audit their own number.
Amazon just told a federal judge that Perplexity shopping agent shows the wrong prices. And Amazon still lost.
Most of the coverage framed it as an access fight: can agents crawl Amazon or not. The sleeper issue is deeper in the opinion. Amazon had to prove real harm, and its best argument was basically: the agent might not pick the best price, shipping, or product.
That’s Amazon saying an AI can’t reliably quote Amazon’s own prices.
The court shrugged. Said it was too speculative. No injunction.
If you sell anything online, don’t miss the takeaway: you can’t sue your way into being priced correctly by agents. If Amazon can’t prove the damage, you won’t either. “Block the bots” is not a strategy.
The only lever you have is what the agent can actually read when it lands on your site: real price, promos, inventory, shipping, all machine-legible.
Go ask an agent what your best product costs. Whatever it answers is the price your customers are hearing.
ALT A legal document discusses Amazon's claims about Perplexity AI mispricing and the court's ruling on evidence and harm to customers.
How agents actually pick the "best price"
ChatGPT doesn't just quote prices anymore, it awards its own "Best Price" tag.
Profound's June pass through about a million shopping offers found the rule: products arriving through a structured merchant feed get that tag 100% of the time, versus 21% when the machine has to scrape the page, and feed-sourced offers take the top slot in the answer 99.9% of the time.
Rank is mostly a function of what you handed the machine.
If your products still reach agents by scraping, shipping the structured feed is the cheapest rank you'll ever buy. It still won't carry your member prices, which is the harder half.
We pointed our own benchmark at the grooming category and the miss sits at the very top of the market: 1 in 31 mentions of the category's best performer cited any incentive at all, and every brand below it did worse.
The deals are funded, live on the sites, and structurally absent from the channel where the most price-motivated shoppers now start.
For example, a jar of Augustinus Bader face cream at Nordstrom cost five different amounts over the last 27 days, and which one you paid came down to which card is in your wallet.
Anniversary Sale pricing had it at $423.75. On Sunday the sale ended and it went back to $565, a $141 swing! But the sale price wasn't one price either: cardholders at Icon status could buy on July 14, Ambassadors on the 15th, Influencers on the 16th, everyone else waited until the 18th.
It gets more interesting! Free loyalty members earned points and got no early access at all. Nordstrom even prints the after-sale price next to the sale price, so a machine can read both numbers and still can't tell you which one applies to you, because the answer lives in your card status, not on the page.
Every rule of that flywheel is printed on the page and none of it is resolvable by a crawler, because the answer lives in your card status, not in the markup.
Retailers can feel the collision coming: two weeks ago 41% of multichannel organizations told Salesforce that inconsistent pricing and promotions is their #1 omnichannel failure point, and only 2% reported no failure point at all.
The agent didn't create that inconsistency, it just reads it out loud to every shopper who asks.
Being visible in the answer and being chosen by it are two different problems, and almost every tool on the market measures the first one.
At Parleo (Honey for agents) The yardstick we've built for the second comes next.
ALT A blue jar of Augustinus Bader face cream displays prices from retailers, highlighting Nordstrom as the "Best Price" at $565.
Incentives are becoming pricing rails in agentic commerce.
$19.99 or $11.69? Chewy publishes both for the same bag of dog treats, on purpose.
In the eyeball era, incentives were a marketing line. Points, member pricing, card-linked offers, subscription discounts. Brands funded them to nudge behavior and mostly treated them as a cost of doing business.
At Parleo (Honey for agents) we strongly believe that in the agentic era incentives become pricing infrastructure, probably the last lever that protects margin without torching MAP or racing everyone to the bottom on list price.
One bag of Greenies, four published prices, same page:
– $19.99 list
– $17.98 if you buy once
– $17.08 on autoship
– $11.69 on your first autoship order
That spread is deliberate pricing design, the low price buys a subscriber and the lifetime value pays for it, margin traded for loyalty on purpose. It's beautiful work.
So we asked ChatGPT what the bag costs, and it answered fast and confidently: $19.99. True, and also the worst of the four published prices on that page. The agent saw the top of the ladder and stopped, and the machinery Chewy built to turn margin into LTV never made it into the answer.
As a retailer or brand, I'd run that same test on your stack, every tier, every member price, every card offer you fund: how much of it can an agent actually see?
For most brands the answer is almost none, and the money behind that answer is not small, $200B+ a year of US trade promotion funding the deals, another ~$69B of retail media buying the banners on top, and agents bypass both sides of that coin.
The brands that win agent channels will be the ones whose member prices and deals the agent can actually read, because that's what protects the margin AND rewards the customer you already invested in.
More tomorrow.
ALT ChatGPT displays pricing options for Greenies dog treats on Chewy, highlighting various costs and discounts for purchasing methods.
The internet and e-commerce are being rebuilt for a customer that isn't human.
And people are already using AI that way. 46% of AI shoppers use it to compare prices and find deals.
The problem is that every price in a ChatGPT comparison table is usually a list price. No member price, no card-linked offer, no loyalty math, just the number sitting at the top of the page.
At Parleo (Honey for agents), we think that one detail is a critical part of what's reshaping e-commerce right now.
The internet retail runs on was built for eyeballs. Twenty years of storytelling, PDPs, banners, badges and urgency copy, all designed to influence what a person sees and buys.
Now it's being rebuilt for agents that read feeds and APIs and skip almost all of it.
The proof is in how big tech and the frontier models are behaving.
OpenAI launched Instant Checkout last fall and killed it by March. Walmart put 200,000 products in, watched conversion run about three times worse than its own site, pulled them, then rebuilt inside its own walls, where its agent can see your membership, promotions and fulfillment, and is now posting 35% bigger baskets.
The models are interchangeable. The context is the variable.
And the shift has stopped being theoretical. Salesforce found shoppers starting purchases with agentic search up 200% year over year. Adobe tracked AI-referred shoppers converting 23% worse last Prime Day and 50% better this one. McKinsey puts US agentic retail at about $1T by 2030.
Here's where it gets more interesting: Trade spend funds the offers, rewards and discounts brands run at retail. Retail media buys the banners and sponsored listings layered on top. Agents bypass both. They don't see the banner, and they can't read the deal you funded.
That gap, what actually survives the trip from your pricing stack into the agent's answer, is where we've been building for the past 6 months.
I ran a pretty simple version of this test recently. Asked ChatGPT to find the best price for a Patagonia Down Sweater Hoody. It picked the cheaper list price.
But once you factor in the member benefits and funded offers the agent couldn't see, the more expensive retailer was actually the better deal.
That's a pretty meaningful problem if your best customers are the ones getting those offers in the first place.
This week we're going to share a little more about how we think about it, and one thing we made.
ALT Comparison of prices for a Patagonia Down Sweater Hoody shows Amazon at $259, highlighting hidden discounts not visible to the agent.
Samar Birwadker retweeted
The CEO of the most advanced AI company in America just went on national television (Save this)
Hours after his company was blacklisted by the US government.
Here's what he said.
Dario Amodei built the only AI deployed inside the Pentagon's classified networks.
His company helped run military operations, intelligence, cyber defense.
Then the government told him to drop all safety limits.
He said no to two things.
Just two.
"One is domestic mass surveillance."
He explained: the government can already buy your location data, your browsing history, your political affiliations from private companies.
AI makes it possible to analyze all of it.
On every American, all at once.
"That actually isn't illegal. It was just never useful before the era of AI."
"Case number two is fully autonomous weapons."
Not the drones used in Ukraine and the remote-controlled systems.
Weapons that select targets and fire without a single human pressing a button.
"The AI systems of today are nowhere near reliable enough."
"We don't want to sell something that could get our own people killed or that could get innocent people killed."
He approved 98% of what the Pentagon wanted.
"No one on the ground has actually run into the limits of any of these exceptions."
The government wasn't fighting over something it needed.
It was fighting over the right to have no limits at all.
They gave him three days.
He said no.
So the President called his company "radical left woke."
Then ordered every federal agency to stop using their technology.
Then the Pentagon labeled them a national security risk.
A designation that has only ever been used against foreign enemies.
When asked if he'd received any formal legal action, he said this:
"All we've seen are tweets from the president and tweets from Secretary Hegseth."
No letter, filing or a legal document.
"When we receive some kind of formal action, we will look at it, we will understand it, and we will challenge it in court."
He said the Defense Secretary lied about the law.
Hegseth tweeted that any company with military contracts can't do business with Anthropic "at all."
Amodei: "That is not what the law said."
"The nature of the tweet was designed to create fear, uncertainty, and doubt."
Asked if this was an abuse of power, he paused.
Then said:
"This designation has never happened before with an American company."
"It was made very clear that this was retaliatory and punitive."
"I don't know what else to call it."
Asked if Anthropic could survive, he didn't hesitate.
"Not only survive it. We're gonna be fine."
Then the final question.
"If you had a moment with the President right now tonight, what would you say to him?"
"We are patriotic Americans."
"Everything we have done has been for the sake of this country."
"The red lines we have drawn, we drew because we believe that crossing those red lines is contrary to American values."
"Disagreeing with the government is the most American thing in the world."
"And we are patriots."
A CEO just went on national television and told the President of the United States:
You can blacklist us.
You can call us names.
You can threaten our business through tweets.
But we will not build machines that spy on Americans or kill without human hands.
The Pentagon just blacklisted one of America’s most valuable AI companies.
For refusing to build surveillance tools aimed at American citizens.
Hours later, its biggest rival OpenAI quietly signed the deal of the decade.
Here’s what just happened and why it changes everything.
This week, the US Department of War gave Anthropic an ultimatum.
Drop your safety restrictions and let us use your AI for anything we want.
The deadline was 5:01 PM today and Anthropic said no.
Their CEO, Dario Amodei, drew two red lines.
No mass surveillance of Americans.
No fully autonomous weapons without a human pulling the trigger.
The Pentagon called this “woke AI.”
Anthropic called it a conscience.
The Pentagon’s response was swift and brutal.
Defense Secretary Pete Hegseth branded Anthropic a “supply chain risk”, a designation normally reserved for Chinese and Russian companies.
President Trump ordered every federal agency to stop using Anthropic immediately.
But here’s where the story turns.
That same night, Sam Altman, CEO of OpenAI, Anthropic’s biggest competitor posted a message.
“Tonight, we reached an agreement with the Department of War to deploy our models in their classified network.”
The twist? OpenAI’s deal includes the exact same red lines Anthropic was just destroyed for demanding.
No mass surveillance and no autonomous weapons.
Human control over the use of force.
The Pentagon punished one company for demanding protections it then gave to another company the same day.
Altman even defended Anthropic on live television hours earlier.
“For all the differences I have with Anthropic, I mostly trust them as a company and I think they really do care about safety.”
Then he signed the deal Anthropic couldn’t get.
Anthropic was the first and only, AI model deployed on the Pentagon’s classified networks.
Replacing it will take months.
OpenAI just positioned itself to fill the most powerful AI vacancy in the U.S. military.
The stakes are staggering.
Anthropic just raised $30 billion and it was preparing for an IPO.
Now over 300,000 enterprise clients may be forced to cut ties.
Not because the technology failed.
Because the company refused to remove a guardrail that said “don’t spy on Americans.”
But here’s the real question no one’s asking:
If the Pentagon never intended to use AI for mass surveillance as they claim, why was this the hill they chose to die on?
Why blacklist a $380 billion American company over a clause the government says doesn’t even matter?
Sam Altman called for de-escalation.
He asked the Pentagon to offer these same terms to every AI company.
Including Anthropic.
The world just watched a company get punished for saying “no” to surveillance and a competitor rewarded for saying “yes, but with the same conditions.”
Bookmark and share this.
Samar Birwadker retweeted
Complete hardware + software setup for running Deepseek-R1 locally. The actual model, no distillations, and Q8 quantization for full quality. Total cost, $6,000. All download and part links below:
Samar Birwadker retweeted
This doesn’t seem to be getting enough attention. The Silicon Valley social contract forced on the public by Obama and then Trump and then Biden (minus Lina Khan) and now Trump was straight forward: We will let these bros become the richest people in human history and in exchange they will develop a tech industry that makes the U.S. dominant for a century.
They did the first part, then built monopolies to try to keep out competition rather than continue to innovate at a top level, and then got out-competed by Chinese companies in both AI and social media. They are the losers we always thought they were — and now so are we.
These kind of teardowns are why I'm spending more time on X. Good luck finding this investigative analysis on LinkedIn.
Great work @RobertMSterling, surprising details I had no idea about! E.g. 10x the 85k limit/year is just nuts! How has this gone unnoticed for so long!?
Samar Birwadker retweeted
AI is about to eat every indefensible CRUD app. And almost no one sees it coming.
ServiceTitan: $9.5B valuation $TTAN
~$700M+ ARR
~12,000 customers
>110% NRR
But here's the thing: they're ultimately well-executed CRUD applications with no moat for plumbers, HVAC, lawncare, etc.....
Let me show you something wild.
Samar Birwadker retweeted
Peter Thiel reluctantly agreed with Elon Musk's belief that if the Democratic Party won the 2024 election, it could consolidate power into a one-party state.
"I didn't want to believe Elon when he said this, so I texted him and told him I hadn't believed you when you said this at first. But I think this is because, psychologically, I don't want to believe that."
"The sense in which I felt that he was correct was if Trump, with much better substance and much better on so many things, could not win in 2024 against the machine, then the machine would always win."
"And if the machine always wins, then you no longer have a democracy. You certainly no longer have a democratic process within the Democratic Party. We can always debate the election shenanigans in November 2020."
"The far more extraordinary thing was in March of 2020 when Biden came in fourth or fifth in Iowa and New Hampshire and then somehow got rammed through South Carolina. All the other candidates drop out."
"So, this extremely non-democratic primary in the Democratic Party in 2020 led to an even less democratic process in which Biden was replaced with Harris."
"If the machine could defeat Trump, I thought it was reasonable that it would gain even more power and somehow be unbeatable, and the country would become like California, a one-party state."
@elonmusk
@peterthiel
