I’ve been testing an sBTC loop on Zest Protocol on @Stacks. They're currently running an incentive campaign for 0.5 BTC every month. Here's a quick farming guide↓ 1. $sBTC + $USDCx This is the loop I tested first, since USDCx borrowing is also part of the incentive campaign. → Supply sBTC on @ZestProtocol → Borrow 40-50% USDCx against it → Swap the USDCx into more sBTC → Supply that sBTC back into Zest → Repeat several times I’m personally aiming for roughly 50-55% LTV. With USDCx debt, partial liquidation starts at 70%, so that leaves me roughly a 15-20% BTC drop before reaching the liquidation threshold. Just keep monitoring the price, and it'll be okay. 2. Other loops USDCx isn’t the only asset you can borrow against sBTC. The debt you choose basically changes what you’re trying to achieve with the loop: → sBTC Borrow sBTC and resupply it. Since the collateral and debt move together, there’s much less price mismatch, which is why Zest allows up to 80% LTV. → USDh Works similarly to my USDCx strategy. Borrow the stablecoin, swap it into more sBTC, then resupply. The difference right now is that USDCx borrowing qualifies for the new incentives. → STX / stSTX Borrow either asset, swap it into sBTC, and resupply. This becomes more of a relative-value trade because you benefit if sBTC performs better than the asset you borrowed. The last one carries much more cross-asset risk, which is reflected in the much lower 30% max LTV. So all three are pretty similar. The main difference is the level of cross-asset risk. Again, I'd go for borrowing USDCx because of the incentive campaign. 3. TL;DR For this, I'd say choose a strategy based on your short-term outlook for Bitcoin: → Bullish on BTC - USDCx/USDh debt gives the most direct leveraged BTC exposure. → Neutral on BTC - sBTC debt makes the most sense if the supply/borrow spread and incentives justify it, since I’m not really taking a BTC directional bet. → Bearish on BTC - sBTC debt is the more defensive loop because the collateral and debt fall together. Realistically tho, reducing leverage is safer than trying to optimize a loop for a BTC drawdown. Overall, there’s no single best loop here. Personally, my focus is on the incentives. Disclosure: I’m a long-time $STX holder and Stacks supporter.

August saw roughly $200B in DEX volume against around $90B in TVL, meaning the capital already on-chain turned over more than twice during the month. To me, that suggests traders are becoming more active again. But compared to the 2025 memecoin-frenzy levels, we’re still far from full-blown DeFi euphoria. It feels more like we’re at the early stages of on-chain activity building back up, which I’m fully ready for lol. We deserve it.

Restaking is basically a dead meta. Both $EIGEN and $ETHFI were built around it, but ETHFI has held up much better in price. Their yearly inflation since TGE: → EIGEN: 67.98% → 116.91% → 44.92% → ETHFI: 183.18% → 31.60% → 3.03% ETHFI took most of the dilution early. EIGEN still has a much heavier supply schedule ahead. And imo, ETHFI’s stronger price performance has little to do with restaking anymore. @ether_fi has spent the past year moving toward the neobank model, while ETHFI now also benefits from protocol revenue and buybacks. On the other hand, EIGEN still has more supply to absorb and much less proven fee demand behind it. Since @eigenfoundation's token started trading, ETHFI is down ~67% versus ~95% for EIGEN. The biggest difference between the two now is that EtherFi expanded to neobanks. Smartest move they ever made if you ask me.

Compiled a list of cold wallets that have never had a data breach & hack ↓ @gridplus @coolwallet @SeedSigner @SecuXwallet @thisisarculus @ngrave_official @FoundationHQ @KeystoneWallet @DCENTWALLETS @CypherockWallet Bookmark to not lose it.

So many @fomo screenshots of people printing 5, 6, even 7 figures all over my timeline. This makes it seem like everyone is printing in this market. But that's far from the reality. Only ~5.6% of traders on FOMO are profitable, and only 74 traders out of ~460K total made more than $5K. Also, most of those PnLs aren’t realized. If a large holder decides to dump their entire position, slippage would eat heavily into those profits. Large sell + low liquidity = slippage eats into profits. So if any of these users tried to 1-clip their entire position, it could wreck the chart, drain liquidity, and leave every other holder underwater. Don’t let these screenshots bring you down. They're just there for show.

Crypto created a generation of anonymous millionaires. Some bought BTC when nobody cared. Others got into ICOs early or caught the right token before everyone else. A few turned thousands into hundreds of millions. Here are 10 of the craziest crypto PnL's in history ↓

The story of my fuck up in the area of my strongest expertise: how Stacy tried to create fully automated communities When I landed on the vision of building the distribution system first (before any products) I started vibecoding content automation systems. My initial idea was to find areas of strongest human interest (ideally fast-growing topics where demand for content is still unfilled) and build a content engine that would pull relevant data and feed it into these communities. It seemed easy: collect news and data, have AI summarize the key points, and voila. A self-serving content engine, and I’d only need to handle promo. I was VERY much mistaken. Building the system itself was pretty easy. I gave it my ToV, writing rules, and a format grid – it looked solid and felt not too AI. But I didn’t factor in one thing: people are overloaded with content, and they don’t want to follow humanless content. I didn't know it then. So I launched one of the first automated communities. I spent ~$1K on Telegram Ads tests to estimate acquisition costs and user behavior. I optimized for good cost per subscriber (~$0.8) – but those users didn’t stay. They joined, then muted the channel within a few days. Mute = death. I literally paid for bots. I know that 90% of bloggers are now using AI to write content, and I was doing the same, but now I see how people react to AI content in practice. No matter if it's quite good and is based on my own content algorithms, it's just not human. Now I’m rebuilding the design from zero, putting AI where it actually does its job well: data sourcing, engagement analytics, and projecting content fit into drafts. Let's see how v2 evolves :) I share my story here →

Restaking is basically a dead meta. Both $EIGEN and $ETHFI were built around it, but ETHFI has held up much better in price. Their yearly inflation since TGE: → EIGEN: 67.98% → 116.91% → 44.92% → ETHFI: 183.18% → 31.60% → 3.03% ETHFI took most of the dilution early. EIGEN still has a much heavier supply schedule ahead. And imo, ETHFI’s stronger price performance has little to do with restaking anymore. @ether_fi has spent the past year moving toward the neobank model, while ETHFI now also benefits from protocol revenue and buybacks. On the other hand, EIGEN still has more supply to absorb and much less proven fee demand behind it. Since @eigenfoundation's token started trading, ETHFI is down ~67% versus ~95% for EIGEN. The biggest difference between the two now is that EtherFi expanded to neobanks. Smartest move they ever made if you ask me.

Compiled a list of cold wallets that have never had a data breach & hack ↓ @gridplus @coolwallet @SeedSigner @SecuXwallet @thisisarculus @ngrave_official @FoundationHQ @KeystoneWallet @DCENTWALLETS @CypherockWallet Bookmark to not lose it.

Crypto created a generation of anonymous millionaires. Some bought BTC when nobody cared. Others got into ICOs early or caught the right token before everyone else. A few turned thousands into hundreds of millions. Here are 10 of the craziest crypto PnL's in history ↓

The story of my fuck up in the area of my strongest expertise: how Stacy tried to create fully automated communities When I landed on the vision of building the distribution system first (before any products) I started vibecoding content automation systems. My initial idea was to find areas of strongest human interest (ideally fast-growing topics where demand for content is still unfilled) and build a content engine that would pull relevant data and feed it into these communities. It seemed easy: collect news and data, have AI summarize the key points, and voila. A self-serving content engine, and I’d only need to handle promo. I was VERY much mistaken. Building the system itself was pretty easy. I gave it my ToV, writing rules, and a format grid – it looked solid and felt not too AI. But I didn’t factor in one thing: people are overloaded with content, and they don’t want to follow humanless content. I didn't know it then. So I launched one of the first automated communities. I spent ~$1K on Telegram Ads tests to estimate acquisition costs and user behavior. I optimized for good cost per subscriber (~$0.8) – but those users didn’t stay. They joined, then muted the channel within a few days. Mute = death. I literally paid for bots. I know that 90% of bloggers are now using AI to write content, and I was doing the same, but now I see how people react to AI content in practice. No matter if it's quite good and is based on my own content algorithms, it's just not human. Now I’m rebuilding the design from zero, putting AI where it actually does its job well: data sourcing, engagement analytics, and projecting content fit into drafts. Let's see how v2 evolves :) I share my story here →

Full list of @Strategy buying and selling in 2026 ↓ January • Jan 5: Bought 1,283 BTC for $116M • Jan 12: Bought 13,627 BTC for $1.25B • Jan 20: Bought 22,305 BTC for $2.13B • Jan 26: Bought 2,932 BTC for $264M February • Feb 2: Bought 855 BTC for $75M • Feb 9: Bought 1,142 BTC for $90M • Feb 17: Bought 2,486 BTC for $168M • Feb 23: Bought 592 BTC for $40M March • Mar 2: Bought 3,015 BTC for $204M • Mar 9: Bought 17,994 BTC for $1.28B • Mar 16: Bought 22,337 BTC for $1.57B • Mar 23: Bought 1,031 BTC for $77M April • Apr 6: Bought 4,871 BTC for $330M • Apr 13: Bought 13,927 BTC for $1.0B • Apr 20: Bought 34,164 BTC for $2.54B • Apr 27: Bought 3,273 BTC for $255M May • May 11: Bought 535 BTC for $43M • May 18: Bought 24,869 BTC for $2.01B June • Jun 1: Sold 32 BTC for $2M • Jun 8: Bought 1,550 BTC for $101M • Jun 15: Bought 1,587 BTC for $100M • Jun 22: Bought 520 BTC for $35M • Jun 30: Sold 1,363 BTC for $80.8M July • Jul 6: Sold 2,225 BTC for $135.2M August • Aug 3: Sold 1,638 BTC for $104.7M • Aug 10: Sold 1,690 BTC for $108.6M • Aug 31: Bought 4,603 BTC for $369.7M

Robinhood is now 129x more expensive than Solana. Avg. Solana fee: $0.00259 Avg. Robinhood fee: $0.3344 Robinhood TX fee has increased by almost 5,000% since August. So, what happens when the chain actually gets mass adoption?

There is around $132M in holder revenue across DeFi over the past 30 days. Here are the protocols giving value back to holders ↓ Trading, DEXs & perps • @HyperliquidX — 99% of relevant fees buy back $HYPE. • @Pumpfun — Platform revenue buys back $PUMP. • @Uniswap — Protocol fees buy back and burn $UNI. • @JupiterExchange — 50% of revenue funds $JUP buybacks. • @Lighter_xyz — Protocol fees buy back $LIT. • @Aster_DEX — 99% of fees buy back $ASTER. • @PancakeSwap — Product fees buy back and burn $CAKE. • @Raydium — AMM fees buy back and burn $RAY. • @AerodromeFi — Fees and incentives go to veAERO voters. • @VelodromeFi — Fees and incentives go to veVELO voters. • @PharaohExchange — Fees go to xPHAR voters. • @THORSwap — Revenue funds $THOR rewards and burns. • @OfficialApeXdex — 50% of trading fees buy back $APEX. • @BreederDodo — Revenue flows back to $DODO holders.

Pons generated more fees in the last 24 hours than Lido, Axiom, Aave, and Fomo COMBINED. Robinhood Chain is now the #2# chain by app revenue, behind only Solana. Base could never...

Kalshi became the official prediction-market partner of the US Open. It’s a multi-year partnership in which @Kalshi will be promoted both online and at US Open venues. Prediction markets made their way into mainstream sports, much like sportsbooks did before them. And Kalshi is already enormous, with roughly 3x @Polymarket’s 24h volume. I’d pay attention to the exclusivity here. Rival prediction markets are reportedly blocked from advertising at the tournament and across its ESPN broadcasts. Kalshi and Polymarket may end up racing to secure the biggest events.

Full list of @Strategy buying and selling in 2026 ↓ January • Jan 5: Bought 1,283 BTC for $116M • Jan 12: Bought 13,627 BTC for $1.25B • Jan 20: Bought 22,305 BTC for $2.13B • Jan 26: Bought 2,932 BTC for $264M February • Feb 2: Bought 855 BTC for $75M • Feb 9: Bought 1,142 BTC for $90M • Feb 17: Bought 2,486 BTC for $168M • Feb 23: Bought 592 BTC for $40M March • Mar 2: Bought 3,015 BTC for $204M • Mar 9: Bought 17,994 BTC for $1.28B • Mar 16: Bought 22,337 BTC for $1.57B • Mar 23: Bought 1,031 BTC for $77M April • Apr 6: Bought 4,871 BTC for $330M • Apr 13: Bought 13,927 BTC for $1.0B • Apr 20: Bought 34,164 BTC for $2.54B • Apr 27: Bought 3,273 BTC for $255M May • May 11: Bought 535 BTC for $43M • May 18: Bought 24,869 BTC for $2.01B June • Jun 1: Sold 32 BTC for $2M • Jun 8: Bought 1,550 BTC for $101M • Jun 15: Bought 1,587 BTC for $100M • Jun 22: Bought 520 BTC for $35M • Jun 30: Sold 1,363 BTC for $80.8M July • Jul 6: Sold 2,225 BTC for $135.2M August • Aug 3: Sold 1,638 BTC for $104.7M • Aug 10: Sold 1,690 BTC for $108.6M • Aug 31: Bought 4,603 BTC for $369.7M