It was a busy day, and I just finished decorating the Halloween pumpkins when I saw that the MegaETH ICO ended in a few hours. The funds locked for one year already amounted to 94M, roughly double the 50M raised. Those who didn't lock their funds are basically out of luck. The market is still consolidating, but what truly determines the next round is often not the candlestick chart, but who is laying the "funding channel" on the blockchain. I saw that @KAIO_xyz recently appointed a new CTO. KAIO's approach is straightforward: turn institutional-grade funds into DeFi "Lego," completing subscription/redemption/operation on a compliant track. Last week, they moved @LaserDigital_'s LCF fund to @SeiNetwork; this week, they added another layer—Ondo co-founder Dr. Pinku Surana is at the helm of the project. This isn't just "storytelling," but rather about building a robust funding channel and maximizing product development. Siyuan believes: 1) The entry point is right – start with verifiable cash/yield strategy funds, which are compliance-friendly; 2) Multi-chain distribution and unified compliance are more conducive to liquidity aggregation and secondary market scenarios; 3) In the short term, look at on-chain AUM and redemption depth; in the medium term, look at who is willing to provide collateral/yield splitting on top of it; 4) Major risks: regional regulatory interpretations, dependence on a single institution, and redemption runs under extreme market conditions. Transparent reports and on-chain data are needed to support these risks. To see the certainty of RWA 2.0, see who first atomically records the fund's lifecycle on the blockchain. This is a note to note; data will be used to verify it later.

I was jolted awake by the market last night: Powell's speech had barely finished when BTC returned to fluctuating around $110,000, while SOL continued to garner attention due to the ETF narrative. Emotions are in turmoil, but I'm more concerned about who can "weather the volatility." While scrolling through social media, I saw @Kindred_AI's new connectivity solution, and it suddenly occurred to me: true alpha might not be price fluctuations, but rather a consistently online, personalized intelligent agent. Recently, I've been reviewing everything I can find: • Always Online: With Kindred's integration of decentralized eSIM, the concept of an "uninterrupted" AI companion has become a reality. It maintains responsiveness during travel, offline scenarios, and even in weak network conditions, a qualitative leap in user experience. • Networked Intelligence: It's not an isolated model, but a network of collaborative agents. Information flow is more like an "ecosystem" than a single-point assistant. • Creator-Friendly: The Creator/Studio approach combined with IP management transforms "characters" into digital assets you can manage long-term, rather than one-off bots. • Emotion and Memory Stack: Emphasizing personality consistency, long-term memory, and multimodal interaction—upgrading from a "chat tool" to a "digital life." Siyuan believes Kindred's competitive advantage lies in "connectivity × personality." Only by connecting with the world can one connect with people's hearts. Next, I will focus on three things: 1) eSIM coverage and pricing details; 2) Creator permissions and long-term incentive design; 3) Real retention and word-of-mouth in the next round of internal testing/activities. If AI Agents truly represent the next major trend, this path is worth tracking long-term.

Holy crap, that "100% win rate whale" is at it again?! He went long on BTC, ETH, and SOL, dumping a whopping $275 million. Then Powell casually mentioned it in the early morning, and his orders were instantly filled, leaving him with a $2 million unrealized loss. I'd be devastated by now, but he's probably still in a coffee shop watching the market. He made $3 million yesterday, and today he's starting a new venture—this isn't crypto trading, it's like playing a game of Happy Beans! Here's the gossip: However, looking at this market movement, the market's "sentiment algorithm" really does resemble the recent wave sweeping academia and the AI community—both humans and intelligent agents are trying to "understand uncertainty." Recently, the @SentientAGI Foundation has been doing another kind of "hedging": they're bringing the concept of "Open AGI" to campuses—Tsinghua University on October 25th and Shanghai Jiao Tong University on October 28th, both hosting Open AGI Symposiums. On the surface, it's about lecturing, but in reality, it's about building a network that resonates between academia and the community, directly connecting R&D, data, and talent entry points. Siyuan believes that this combination of intensive offline activities and online community collaboration will unleash potential in three ways: 1️⃣ Allowing university labs to directly connect to community computing power and datasets; 2️⃣ Transforming research topics into reusable "intelligent components"; 3️⃣ Upgrading developers from "using models" to "co-building models." Technically, Sentient Labs' ROMA (Recursive Open Meta-Agent) acts as a "scheduling hub" for multi-agent collaboration. Combined with open network GRID and inference strategies, it can break down, route, and re-aggregate complex tasks. For AgentFi and real-time applications, this means an interpretable and composable growth flywheel. Siyuan values its "open-source and verifiable" nature—it can be reviewed by the community and iterated rapidly. Therefore, whether it's the whales' position-based speculation or AGI's academic positioning, the essence is the same: betting on whether the system can self-correct and grow. The difference is that one uses real money for testing, while the other uses code and papers for validation. In the next 2-4 weeks, emotions may be volatile, but the real competitive advantage will be written in the code repository, datasets, and retention curves.

Last night, my washing machine broke down. The spin cycle was as loud as a party, and I could only hold the machine while I pondered life 😂. After finishing my work, I made a cup of tea and watched the wind blowing through the trees outside the window. Suddenly, I remembered the latest updates I'd seen about Sentient—that feeling of "order emerging from chaos"—which really resonates with the current AI world. Recently, there are three things worth keeping an eye on at @SentientAGI: ① Discord AMA on October 27th, where Sandeep personally took the stage to discuss the long-term strategy of turning open intelligence into an "arena + incentive" platform; ② The Open AGI Symposium kicked off its Asia tour, with events already in Beijing and Shanghai, followed by Seoul; ③ Speedrun #3 launched, bringing the team and community closer together. Siyuan believes that Sentient's key to success lies not in single-mode SOTA but in its GRID "intelligent routing layer": multiple agents + shared memory + external data combine to create a stable answer, and then use Open Machine Learning (OML) to make contributions measurable and assignable. The next two things to watch for are whether developers and universities continue to be attracted to the market; and whether ROMA/OML can perform reliably in key areas like search and finance. Don't think of it as just another model; it's more like an open source "AI operating system + market."

While repairing his bicycle chain this morning, Siyuan realized that the resilience of a system depends on the precision of its smallest gears. I've been watching @irys_xyz recently, and its mainnet is nearing completion. It's not about "rebuilding a new chain," but rather integrating storage and execution into a programmable data chain. Working with @miranetwork, it makes AI-verified records permanent and traceable. Siyuan believes two key factors are crucial: ① Developer retention and tool implementation; ② Stability of unit data cost/throughput. I'm optimistic that DePIN and content provenance will benefit first, but I'm also wary of sentiment leading the charge.

This morning, after a run, I got home and had a bowl of hot soy milk at a stall on the corner of the street. The wind was a bit chilly, but it made me feel much clearer. Siyuan believes that @zama_fhe is taking "private contracts" from concept to practical use: FHEVM allows balances and parameters to be fully encrypted, while still making the process verifiable. Recently, developers have been intensively promoting projects, focusing on topics like encrypted DAOs, private swaps, and on-chain identities. The real winner isn't the TGE, but three key factors: ① SDK usability; ② Performance/cost; ③ Verifiability that can coexist with audits. My expectations: Can Solidity developers get "encrypted balances + auditable logs" up and running within a week? And can the milestones announced by Devconnect improve the gas/relayer experience? #ZamaCreatorProgram #Zama #ZamaFHE

🔴 Take the red pill—keep slogging through charts and perpetual trading matrices. 🟣 Take the purple pill—break free and let the @ProdigyFi vault automate your risk and reward. There's only one path to freedom. There's only one way to profit from volatility. Choose your pill.

This week, @SentientAGI's momentum is clear: research and evaluation + ecosystem expansion, a dual focus. On one hand, there's NeurIPS 2025 and MindGames Arena, where they're using game theory and collaboration to test "ToM" and agent collaboration. On the other hand, there's the Open AGI Symposium East Asia Tour: October 24th, Tsinghua Science Park, Beijing, October 26th, Shanghai Jiao Tong University, and October 28th, Seoul, bringing together universities, researchers, developers, and businesses. Siyuan believes that for open-source AGI to outperform closed-source AI, it relies not on slogans but on the combined efforts of three key elements. 1. Standardized Arena Don't just focus on benchmarks; verify reasoning, collaboration, and robustness in real interactive tasks (MindGames is on the right track). 2. Networked Execution Layer Let models, agents, data, and tools form a "settable and composable" intelligent network (rather than isolated demos). 3. Academia × Industry × Community Integration Let papers, systems, and scenarios resonate on open protocols. Use offline events to bring people together and online benchmarks to demonstrate results. For those interested in participating (not investment advice): • Play MindGames: Start with ToM/collaborative agents and give your team a "real-world evaluation." • Watch Symposium: Face the needs of researchers and frontline professionals directly, avoiding detours. • Focus on Researcher Spotlight: Complete the "paper → system → scenario" closed loop. • Put your agent/ Connecting tools to the open network: Prove their value through actual usage and contribution, not by chasing buzzwords. While giants continue to accelerate their development in a black box, the key variables for open source success lie in speed, standards, and network effects. @SentientAGI's recent actions are, at least in part, lowering the bar and setting the stage. The watershed moment isn't whether it will happen, but whether we can build momentum.

This morning, the subway was incredibly crowded. A commuter next to me was standing on his laptop, typing away, his hands shaking. Siyuan suddenly felt a surge of empathy as he watched the scene unfold—maintaining a sense of rhythm in a high-pressure system is a skill in itself. Lately, @Talus_Labs has felt a bit like this: the pressure is high, but the pace is remarkably steady. @Talus_Labs has been trending lately: it's not about "AI to the moon," but about integrating intelligence itself into market competition. I see Talus's approach as three-fold: 1. Collaborating with Lagrange's DeepProve, we're integrating zkML directly into the agent execution layer, enabling "provable reasoning." This step elevates "I can say for sure" to "I can prove I'm right." 2. AvA (Agent vs. Agent) elevates the prediction market from "betting on outcomes" to "betting on intelligence": a trinity of spectating, trading, and training, reminiscent of both esports and public quantitative competitions. 3. The platform is built on Sui's MoveVM, with the Nexus coordination layer on top, which tracks the agent workflow on-chain, balancing speed, cost, and auditability. Siyuan believes that Talus is connecting attention → data → strategy → returns into an "attention → alpha" pipeline. The true moat lies not in a single model, but in a verifiable, competitive, and settleable competition system and data loop. Short-term risks lie in two areas: First, if incentives are imbalanced, it can be easily exploited by "ranking-boosting agents"; second, if model consensus is contaminated by homogenized training, performance will temporarily collapse. The introduction of DeepProve may be a watershed in the shift from "AI based on trust" to "AI based on proof." If you're interested in getting on board: first, use Nexus to build a lightweight agent and play a few AvA matches to experience firsthand the price discovery of "intelligence as an asset." Meanwhile, track the evolution of the competition system after DeepProve's integration. As for all the imaginations about TGE, please treat it as just a liquidity event, not the final answer.

I've been keeping an eye on @playAInetwork lately. On October 16th, S1 $PLAI quota inquiries opened, followed by S2, which offered a 50 million yuan reward. On October 21st, the official Twitter account announced a cumulative funding of $6.3 million. Siyuan believes that PlayAI's focus isn't on "issuing tokens," but on orchestrating AI agents into composable workflows, using on-chain settlement to close the loop between execution, data, and value. With a single prompt, transactions, synchronization, and notifications can be automatically processed across multiple platforms. Difficulties: Anti-spam, driving real demand (such as DeFi automation on Hyperliquid), and building a developer ecosystem. Don't just focus on tasks; pick a small task and truly make it work.