There’s no world where just giving out your bank account number means your entire balance and transaction history are publicly exposed. Yet in crypto, this is accepted as completely normal. 😄 Watching the American Fortress video, this point really resonated with me. I found it particularly interesting that you can send assets using a @username, and that stealth addresses make it harder to link transactions. Honestly, from an ordinary user’s perspective, what matters far more than which cryptographic techniques are used is how easy and secure the experience actually is. If you can send funds without having to memorize or copy complex addresses—while still protecting your privacy—that’s a compelling direction. Of course, what’s shown in the video may differ from the actual product’s polish; it’s worth testing firsthand to see if it’s truly that simple. But one thing is certain: The blockchain needing to be transparent is entirely different from needing to expose your assets to the entire world. Privacy isn’t just a feature for criminals—it’s a basic right that ordinary users deserve too.

Let’s take a look at N1Chain. #16 – Nord v22 While reviewing today’s N1 update log, I stopped at this one line: Positive unrealized PnL now counts towards available margin. This is surprisingly significant. For example, suppose you’ve taken a BTC long position but haven’t closed it yet, and your unrealized profit has accumulated substantially. You’re making money, but since you haven’t realized it yet, previously you couldn’t use that profit as collateral for new orders. Starting with Nord v22, that positive unrealized PnL is now included in the margin available for placing new orders. In other words: You no longer need to rigidly separate your capital by first closing your BTC position to lock in profits, → then rebuilding your collateral, → and only then opening a new position. Of course, this doesn’t mean you’ve gained free money. If the market moves against you, your unrealized profit will vanish immediately—so continuing to add positions based on it will increase your risk accordingly. And here’s one crucial point: You still cannot withdraw unrealized profits. Withdrawals and transfers continue to follow more conservative criteria. Actually, I appreciate this approach. It grants more flexibility for trading while maintaining stricter standards for actual withdrawals. Sometimes, changes like this resonate more with active traders than flashy new markets. Instead of treating your unrealized profits as just a number on the screen, Nord v22 now actively incorporates them into your account’s overall capital efficiency. This, to me, was the most impactful change in Nord v22.

Let’s learn about N1Chain. #15 - Multichain Deposit Friend: I’m thinking about trying N1—how do I deposit money? Me: First, create a wallet, get some USDC, check which chains are supported, and if needed, bridge over… Friend: Never mind, I’m not doing it. Haha, honestly, for someone new to on-chain services, this is more common than you’d think. We’ve bridged a few times, so it doesn’t phase us—but for newcomers, depositing funds feels like a quest before they’ve even made a trade. That’s why I’ve noticed the recent update to N1’s deposit screen—it actually looks pretty good. Now you can deposit directly from a wider range of chains, and even bank or card pathways are starting to be integrated. It’s not a flashy update. But maybe the most important question on a perp exchange isn’t “How much leverage can I use?” but rather “How do I even deposit money here?” If users get exhausted before they even click the trade button, no matter how good the order book is, it won’t matter. Looking at N1’s recent updates, they’re not just adding trading features—they’re also quietly eliminating these annoying friction points one by one. I really like these kinds of updates. The shorter the instruction manual, the more new users will come in.

Let’s learn about N1Chain. #10 – High-Performance Chain In blockchain projects, when we see metrics like TPS or latency, it used to feel like nothing more than a benchmark competition. But in the context of a Perp DEX, things are different. Speed can directly impact the quality of liquidity. For example, imagine a market maker places bids to buy BTC at $100,000 and offers to sell at $100,010. If the market moves but the order takes too long to cancel or update, there’s a risk that someone will be filled at the outdated price during those few seconds. From the market maker’s perspective, this risk naturally gets priced in. As a result: Latency ↑ → Quote Risk ↑ → Spread ↑ → Trader’s Execution Cost ↑ This is the dynamic at play. That’s why it feels reductive to view N1’s constant emphasis on sub-ms latency as merely a speed boast. N1 integrates the order book directly at the network level. Instead of apps implementing their own order books and uploading results to the chain, the network itself is deeply involved in order matching and execution. This matters because what traders ultimately want isn’t just “an extremely fast blockchain.” They want: Narrow spreads Deep liquidity Rapid order updates Predictable execution The ultimate goal of N1’s high-performance chain must lead precisely to these outcomes. Speed itself is not the product. But when that speed translates into better quotes and better executions, it ceases to be just a specification—it becomes real trading infrastructure. That’s why, when evaluating N1 today, I’m looking at order book design and latency alongside TPS.

Let’s learn about N1Chain. #9 - Oracle Previously, I wrote about N1’s TCGX, but what I was even more curious about was this: “How do you assign a single price to something like trading cards?” BTC and ETH have real-time prices and high trading volumes across exchanges. But trading cards are completely different. Some cards rarely trade at all. The same card can have different prices depending on its condition or version. And if someone sells one expensive card at an odd price, it doesn’t mean the entire market has gone up. Thus, creating a perpetual contract for such a market ultimately hinges on oracle design. Looking at how N1 built TCGX, I was surprised by how much thought they put into it. First, they didn’t just include any random cards. Instead, they carefully selected 160 cards with frequently updated price data and observable real-world price movements. The composition is: Pokémon: 48 cards Magic: 80 cards One Piece: 16 cards Lorcana: 16 cards But they didn’t allocate weights based purely on card count. Doing so would have given Magic half the index weight simply because it has more cards. Instead, the actual index weights are set separately: Pokémon: 45% Magic: 42% One Piece: 11% Lorcana: 2% Personally, what I found most interesting is how they handle outlier prices. If one card suddenly spikes tenfold, and TCGX follows suit, that would obviously be problematic. So N1 uses a Huber estimator to limit the influence of prices that deviate excessively from the mean. In a test where all 160 cards were given equal weight, when one card’s price spiked tenfold: - A standard log average would cause the index to move by ~1.45%. - But with N1’s method, the index moved by only ~0.50%. Conversely, if the entire card market rises uniformly by 5%, the index follows exactly that 5% move. In other words: It reflects overall market trends, while preventing a single outlier from dominating the entire index. Seeing this helps me understand why Discovery Markets isn’t just about “listing quirky assets.” The first and most critical requirement for turning previously illiquid assets into perpetuals isn’t UI, or leverage, but creating a trustworthy price. Regardless of whether TCGX succeeds, if N1 plans to keep creating markets for previously untradeable assets, this custom oracle technology will likely become a foundational pillar.

One of the biggest friction points in onchain prediction markets often happens before the actual prediction even begins. A user may already have USDC in their wallet, but still need to source ETH for gas, approve the token, and submit multiple transactions just to open a small $5 position. That is a lot of unnecessary friction for a very simple action. This is where ULTRAMINT takes a different approach. ULTRAMINT is a buy-only prediction market designed to simplify the entry flow as much as possible. Instead of requiring users to hold ETH for gas, the user simply signs a USDC transfer authorization. The platform’s relay then submits the transaction onchain on the user’s behalf. The flow is essentially: USDC in wallet → Sign transfer → Relay submits onchain → Position purchased No separate gas token. No user-paid gas at entry. No purchase fee. That may sound like a small UX improvement, but it matters. In crypto, friction is not only about how much something costs. It is also about how many steps a user needs to understand before completing an action. Gas acquisition, approvals, wallet prompts, transaction confirmations — every additional step creates another point where a user can drop off. ULTRAMINT pushes most of that complexity into the background. Another interesting part of the design is the pricing mechanism. ULTRAMINT uses an LS-LMSR AMM, which automatically adjusts market prices based on trading activity and market conditions. Rather than relying on a traditional order book where users need counterparties on the other side, the AMM continuously provides a pricing function for each possible outcome. This makes the market structure more predictable from a UX perspective and allows users to enter a position without waiting for a matching order. There is, however, an important tradeoff: positions cannot be sold before resolution. Once a user buys a position, they hold it until the market outcome is finalized. That means ULTRAMINT is less about actively trading prediction shares and more about taking direct exposure to an outcome and holding that conviction through resolution. In that sense, it feels closer to: “Choose an outcome, take a position, wait for resolution.” rather than: “Trade the probability curve.” The fee structure reflects that philosophy as well. There is no purchase fee and no user-paid gas when entering a position. Instead, fees are applied at settlement after the market resolves. The standard settlement fee is 2.00%, and it can decrease to as low as 0.50% depending on market size. So the economic design is fairly clear: reduce friction at entry, move costs to settlement, and keep the user flow as simple as possible. What I find most interesting about ULTRAMINT is not just the prediction market itself, but the way it approaches onchain UX. For most users, “being onchain” should not necessarily mean thinking about gas tokens, approvals, or transaction sequencing every single time. If someone already has USDC, the ideal experience is probably much closer to: sign once, buy the position, and wait for the result. That is a much more intuitive mental model. And if prediction markets want to reach users beyond the crypto-native crowd, reducing this kind of operational friction may be just as important as creating new markets in the first place.

Attended the SurfAIHQ meetup on October 2, 2026. The atmosphere is amazing! I had no idea there were so many great venues in Seoul for rent... lol Having a great time—catch you later! 😁 https://t.co/dCcwkiDzHu

Let’s learn about @N1Chain. #3 – MCP The N1 update that caught my eye the most was MCP. Now, on N1, you can trade using AI Agents. Actually, the idea of AI + Crypto has been discussed so much that I initially didn’t think much of it—but this feels different. It’s not just asking AI, “Analyze the BTC chart,” and calling it a day. Instead, N1 has built the infrastructure directly on the exchange to connect analysis → judgment → actual trading. In traditional trading, where you need to constantly watch the screen, I believe the future will increasingly involve giving agents specific conditions, having them monitor the market, and letting them execute actions automatically when those conditions are met. And in such a system, the performance of both the chain and the exchange becomes critical— because agents don’t sleep, they continuously monitor the market, and can generate far more actions than any human. This also makes it much clearer why N1 built an L1 from the ground up for trading and layered on features like Perps, RFQ, and Atomics— they’re thinking ahead in exactly this direction. It’s still early days, but N1’s MCP feels like a compelling starting point in the transition from “an exchange designed for humans” to “a financial infrastructure used jointly by humans and agents.” — — — — — — — — — — — — — — — — — — — — — — — — — — — Also, I found it a bit inconvenient that TP/SL functionality wasn’t available when using RFQ markets on N1 right now. When I asked the team, they kindly let me know: Current version is 21, and TP/SL will be enabled starting with version 22. N1 is really working hard. Seriously!

Wow... I have no idea how many weeks it's been since I've seen only C... I feel like I've been mugged by a thug... 😭😭😭 @renaissxyz https://t.co/fitCKV5vTi