Open cryptocurrency community by founder @Rencrypta @Harma__ NFT https://xitter.cf/t.co/cOfHTDJsgF https://xitter.cf/t.co/aiM0uyq7oZ
Joined June 2022
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HareCrypta retweeted
Who pays when the agent buys the wrong thing in Web4?
41 cents.
Average agent payment on x402 over twelve months: $73m across 176m transactions,
98.6% in $USDC
87% < $0.1
Instinct, the largest consumer agent, is nearing $1b a year of purchases on the user's own card, founder-reported.
Two economies of Web4
✅ Cents go in stablecoins.
A card cannot charge two cents per model call, so x402 today is mostly a meter for API, data and compute
✅ Dollars go on cards
- saved credential
-credit line
- fraud controls
-refunds
- millions of merchants.
Instinct's terms say it is not a party to the purchase. OpenAI pulled its first checkout after six months, 30 live merchants against a million promised
✅ The rails converge.
Mastercard already signs a voucher inside a mandate and settles in $USDC.
The card keeps the trust layer, the chain gets the cheap settlement
✅ The primitive is a budget, not a wallet:
amount,
period,
scope,
price cap,
refund rule,
revocation,
loss bearer.
MetaMask, Coinbase and the card mandates are building the same object.
The bottleneck is no longer intelligence, it is permission
✅ Agent tokens sit outside both rails.
Virtuals
$479m of agent GDP, $1.16m of agent revenue, jobs settle in USDC.
Volume is not income
The unsolved market is liability.
who pays when the agent buys the wrong thing.
I think the first Web4 scandal will not be a hack.
It will be a personal agent paid up to 30% by the hotel it recommended.
Whose agent is it then?
Thoughs on Web4
$2.2b - 100% crypto on May 5.
The same $2.2b - A16z frontier on Oct 22.
The money did not move.
Read Dixon's letter for what stayed
- stablecoins
- programmable rails
- machine to machine transactions
- networks built for machines.
Everything that stayed is money.
- Web3 was own.
- Web4 is act, the actor is not you.
- Web4 is the internet where the counterparty is a machine with a budget.
What money looks like when the user is a AI agent
✅ The primitive is a budget, not a wallet.
An agent needs a unit that does not move while the task runs and a rule that reserves the cost before the call. Stablecoins win by default.
A volatile token cannot be a budget
✅ Markets go RFQ first.
An agent asks for a firm price for a size, it does not sit in a book.
Order books become the human legacy UI.
✅ The log becomes collateral.
Agents will need credit, credit needs history, an agent's history is its receipts.
Know your agent replaces know your customer
✅ Airdrop points die.
An airdrop assumes a human on the other side.
With agents as users Sybil is free and infinite, so incentives move to rebates on fees actually paid.
This cycle is the last one designed for people (Variational is last)
✅ A token per agent is payroll and payroll gets sold. Agent tokens will graduate at pump rates, 1 in 58
The money does not go to Web4 tokens.
It goes to whoever holds the agent's budget:
- the rails
- the permission layer
- the venue that quotes,
- the card in the agent's pocket.
Whoever manages your agent’s budget effectively is the clear winner of this new era.
HareCrypta retweeted
+29 Variational points this week.
(29*40 = $1160 current OTC price)
1. The same strategy, but Variational has adjusted the leverage for many pairs to 10x.
2. Just look for trending coins, these coins were moving well along a mini-trend
$Q long
$US100 short
+45 Variational points this week.
(46*40 = $1840 current OTC price)
1. Throughout the day, I use Crypto or TradeFi to look for pairs like ethereum:0x6944e1df6bf5972305f9ab25df47ef10de01bcc8 with the lowest Open Interest
- Enter positions of min $2k, where volatility minimal, so I just hold the positions min 2 hours.
2. Just look for trending coins, these coins were moving well along a mini-trend
ethereum:0x0d8775f648430679a709e98d2b0cb6250d2887ef
$NATGAZ
$ZK
HareCrypta retweeted
This is my Nansen & The Undertaker Meridian entry by @nansen_ai
✅ liquidation map for $BTC $HYPE or any tokens, grouped by price, longs and shorts, named money in blue
✅ whose money is behind a prediction market price, split by wallet win rate, unexamined holders counted on neither side
✅ the same Nansen call answered in chat and drawn on screen from one dictionary, so the picture and the words cannot disagree
✅ every call logged: endpoint, outcome, milliseconds, credits
Demo video 👇
$BTC went from $75k to $87k in six days.
I asked my AI agent The Undertaker where the next cascade sits.
Not a forecast. A map of other people's stops. Any liquidation map ($ETH or etc)
Nansen returns every open leveraged position on a token with its liquidation price and the bot groups them by level.
Red is longs, green is shorts, the dashed line is the current price.
Three things
✅ Draw positions that have no liquidation price.
It names how many were left off, because a map of 5 of 6 is a different map from 6 of 6
✅ Draw an empty map. Zero bars look like a measurement
✅ Call it a prediction.
The caption says these are levels of other people's stops
You can take a look at the GitHub repository with 17 scenarious for Nansen & The Undertaker integration.
