Thank you to the @newsliquidX community for the reminder. Although BNC’s circulating supply has increased this time, it’s not a token issuance, and yzi is unlikely to sell. Got another taste: https://t.co/PX55oSSYAm

$ZEC ignites privacy, $ZAMA picks up FHE. If capital continues seeking “underpriced Privacy Beta,” I’ll keep monitoring these BN spot assets: ethereum:0x7cf9a80db3b29ee8efe3710aadb7b95270572d47 / ethereum:0xddb3422497e61e13543bea06989c0789117555c5 / dusk-network:native / oasis-network:native / base:0xe061aa40be525a13296cb4bf69f513242349d708 Common traits: low market cap, strong narrative, spot liquidity available. Now the more interesting question: If you could only bet on one “next rotation,” who would you pick? Comment directly with the ticker + one-line rationale. If I’ve missed any BN spot privacy assets, drop the ticker—I’ll screen them again. If this gets shared widely, my next post will break down all these projects’ tech roadmaps, FDV, unlock schedules, and recent price performance side by side. #For narrative observation only, not investment advice

This time, can you treat a friend?

AI can help you trade, but what I most want to know is: Why was this position opened? Can the strategy be backtested? And if the judgment was wrong, can we trace back the reason? After reviewing Travix_fi’s project documentation, I believe this direction is worth paying attention to. Travix positions itself as an Agentic Omnibroker—a blockchain-based trading platform that integrates multi-asset trading, event analysis, and AI-driven strategy execution. According to the team, it has completed a seed round backed by Amber Group and is currently advancing toward mainnet launch. The asset selection is particularly interesting, with a strong focus on compute and East Asian markets. Assets such as H100 chips, memory, and electricity, along with semiconductor stocks in Japan and South Korea, are all part of its product roadmap. The goal is to allow users to manage cross-asset positions under a unified margin system, using 24/7 perpetual contracts to express views or hedge risks. If you follow the AI industry, this approach makes perfect sense. Chip supply and compute costs impact different companies across the value chain; bringing these assets together enables coherent trading around a single thesis. But having assets isn’t enough—you also need to understand how events affect them. Travix’s Financial World Model attempts to track changes in the probability of events occurring, combining forward-looking data such as prediction markets to analyze how these shifts propagate to specific assets. As designed, the output includes probability changes, data sources, confidence levels in asset impact, and key risk factors—allowing users to audit the reasoning behind their judgments. The subsequent Trusted Agent layer converts this information into testable strategies, then executes trades according to clearly defined rules, preserving the rationale for entry, conditions for strategy failure, and full execution logs. This is what I value most. It’s easy for AI to generate a bullish rationale—but turning that rationale into executable rules, validating them with historical data, and reviewing them post-trade is what allows you to seriously assess whether it actually works. The order book is already live; AI trading and causal-chain trading remain in beta, with mainnet timing yet to be announced. For now, it’s best to monitor product progress closely and pay particular attention to how well strategy backtesting and execution records are implemented. If you’re interested in AI × trading or compute assets, follow @Travix_fi.

Ethereum: 0x6c5ba91642f10282b576d91922ae6448c9d52f4e This price movement hinges on one core logic: the market has suddenly realized that Phala’s AI query volume on OpenRouter has surpassed that of Venice, which is tied to $VVV—yet PHA’s market cap is far smaller than VVV’s. Simply put: OpenRouter acts like a “big model delivery platform,” where users request various AI models, and behind the scenes, different compute providers supply the necessary processing power. Recent data shows that over the past 30 days, Phala processed approximately 2 trillion tokens, exceeding Venice’s ~1.7 trillion tokens. Yet the market cap disparity is stark: PHA is worth only tens of millions of dollars, while VVV exceeds $1 billion. As a result, capital has begun chasing a straightforward arbitrage logic: “If Phala’s usage is nearly matching or even surpassing VVV’s, why is its market cap only a fraction of VVV’s?” This has triggered the current valuation correction. However, it’s important to note that VVV and Venice have a tighter, more direct link between their business revenue and token value, whereas PHA currently lacks such a clear mechanism for capturing value. Thus, while PHA has fundamental usage data supporting its case, this rally is still largely driven by a “valuation re-rating” relative to VVV. The key things to watch going forward: Will OpenRouter query volumes remain sustained? And will Phala establish a direct link between AI-generated revenue and the PHA token?

Fly

$hype has reached a new all-time high again.

Help Evie’s boss hire talent. One of the most reliable agencies to emerge during the last cycle. Looking forward to seeing them lead not just in Web3, but also in the AI space! Highly recommend candidates with hands-on AI marketing experience to apply—compensation and benefits are top-tier.

The article was written last weekend but only published today. Just now, @ForestBai1 reminded me that they’ve updated the latest version of the gameplay template example to help new users easily experience @MojoAI_HQ agent’s comprehensive AI trading, analysis, and monitoring capabilities. The official release is coming very soon—those without an invite code can save and follow now: https://t.co/HMAEMAiWqq

To master the ARC ecosystem, which key accounts should you follow? [Official Accounts] Arc, @arc: Mainnet progress, ecosystem partnerships, and product updates. Circle, @circle: Company announcements, institutional partnerships, and Arc strategy. USDC, @USDC: Stablecoin applications, cross-chain interoperability, and payment ecosystem. [Management, Product & Technology] Jeremy Allaire, @jerallaire: Co-founder, CEO, and Chairman of Circle. Nikhil Chandhok, @chandhok: Chief Product and Technology Officer at Circle. Rachel Mayer, @0xrachelita: Vice President of Product at Circle, involved in Arc product development. Sanket Jain, @blockjain: Arc product team member, listed as Lead Product Manager in official event materials. Adi Seredinschi, @AdiSeredinschi: Chief Product Manager at Circle, involved in Arc product and consensus infrastructure. Adrian Soghoian, @Soghoian: Circle engineering team member, focused on on-chain infrastructure. [Ecosystem & Community] Sam, @samconnerone: Head of Circle and Arc developer community. Bobbi Lee, @bobbilee: Lead of the Arc Architects community program. Jonny, @jonny_cruz3: Public bio lists as Head of Arc on-chain transactions. Drake Breeding, @DrakeBreeding: Arc/Circle ecosystem expansion. Peter Schroeder, @peterschroederr: Global marketing lead for Circle/USDC. [Launchpad Official Accounts] Argus, @arguspad: Arc token launch and trading platform. Tolly, @TollyLabs: Arc trading terminal, Launchpad, and on-chain data platform. LONG, @Longdotsupply: Cross-chain custody and token launch platform for stock tokens. Lift, @liftdotfun: Arc token launch platform. Peach, @peachlfg: Arc aggregate trading and asset launch platform (corresponds to https://t.co/imQD1hQhlO). https://t.co/eUj5dRg1Rd, @minarafun: Token launch platform centered on USDC-native liquidity. https://t.co/auom5cuqYI, @bozodotfun: Arc token launch platform. ArcPad, @arcpad_meme: Arc token launch platform.