This main cycle is being compressed into two layers.
On one side, there’s revenue, buybacks, and RWA. Hyperliquid takes most of its income to buy back and burn. Then a batch of projects follows suit. Look at it separately: is the money earned by the protocol itself, or “printed” via one hand to the other? The difference this time is that the data rises first, then revenue comes back through buybacks—the token starts to catch and hold the protocol’s value. $HYPE, $UNI, $RAY, $LIT are on this track. $PONS, $STONK, $AI —these new launchpads—are also put into the same category.
On the other side, there’s privacy and AI, which rely more on storytelling. $ZEC is the most typical example. $NEAR hangs privacy trading and full-chain trading. $VVV is a privacy AI, and it tokenizes compute.
On-chain, this wave is mainly about tokenized stocks.
Robinhood’s first wave had the most “golden dogs,” led by $PONS and $Ai, and there’s also pure Meme like $CASHCAT. After playing the token–stock pairing game for a round, this chain enters a cooldown.
Solana also survived without top-tier exchanges. $ZCAT pairs with $ZEC , spawning a batch of Memes built around token–pairing. $Cate does Social Trading—Poorgoat-style leaders help push Holders up. $STONK is the biggest beneficiary here: pairing went from being cold to having consecutive days of revenue that surpassed $PONS.
On BSC, Flap first ran out $Marscoin and $牛. Four’s $4STOCK originally looked the most like a crypto–stock flywheel, but a high-control market wiped out the sentiment. Genius’s tax revenue goes straight into buying stocks, with the goal of getting onto the board. $GSTOCK overtakes $4STOCK, becoming the leader of crypto–stock here.
The buyback flywheel is in the shanzhai. The crypto–stock pairing is on-chain. Next wave—let’s see whether new catalysts can still come through.
On one side, there’s revenue, buybacks, and RWA. Hyperliquid takes most of its income to buy back and burn. Then a batch of projects follows suit. Look at it separately: is the money earned by the protocol itself, or “printed” via one hand to the other? The difference this time is that the data rises first, then revenue comes back through buybacks—the token starts to catch and hold the protocol’s value. $HYPE, $UNI, $RAY, $LIT are on this track. $PONS, $STONK, $AI —these new launchpads—are also put into the same category.
On the other side, there’s privacy and AI, which rely more on storytelling. $ZEC is the most typical example. $NEAR hangs privacy trading and full-chain trading. $VVV is a privacy AI, and it tokenizes compute.
On-chain, this wave is mainly about tokenized stocks.
Robinhood’s first wave had the most “golden dogs,” led by $PONS and $Ai, and there’s also pure Meme like $CASHCAT. After playing the token–stock pairing game for a round, this chain enters a cooldown.
Solana also survived without top-tier exchanges. $ZCAT pairs with $ZEC , spawning a batch of Memes built around token–pairing. $Cate does Social Trading—Poorgoat-style leaders help push Holders up. $STONK is the biggest beneficiary here: pairing went from being cold to having consecutive days of revenue that surpassed $PONS.
On BSC, Flap first ran out $Marscoin and $牛. Four’s $4STOCK originally looked the most like a crypto–stock flywheel, but a high-control market wiped out the sentiment. Genius’s tax revenue goes straight into buying stocks, with the goal of getting onto the board. $GSTOCK overtakes $4STOCK, becoming the leader of crypto–stock here.
The buyback flywheel is in the shanzhai. The crypto–stock pairing is on-chain. Next wave—let’s see whether new catalysts can still come through.