0XC

AI Agents are unlikely to appear at scale in Web2 games but are poised to thrive in fully onchain games for two key reasons: 1. AI Agents struggle with understanding game graphical interfaces. For them to engage effectively, games need to open-source all APIs related to user operations. Fully onchain games, being inherently open-source, meet this requirement. In such games, every player action is recorded as an onchain transaction, providing a perfect environment for AI Agents to learn and grow. @lordOfAFew , through Daydreams and @ai16zdao , is pioneering this concept within the @LootRealms ecosystem, the ticker is $LORDS. 2. Most Web2 games capture value through player payments, but AI Agents in Web2 lack access to money and thus cannot participate economically. On the other hand, AI Agents can seamlessly transact using cryptocurrencies, enabling them to engage in economic activities within fully onchain games. #FOCG #ai16z #AIAgent

@binghe 你们都是用啥支付的啊？

不得不说 Codex 的五小时额度可真耐用啊。 上午跑到现在，还没到。。。 啥情况啊。。家里有矿啊。。。claude code 只要两个来回，就交枪了。。。 这。。。。我爱死你了。。

@0xLaughing 跟我开两个终端一个用 Claude 一个用 Codex 有什么区别

Claude Code + Codex 双剑合璧才舒服 复杂工程两个一起出方案，达成共识才能执行 Claude 执行完了，再用 Codex review，也能找出 Claude 没发现的问题

I have to say this interview changed my life. Hearing how Boris thinks about software spurred me to work much harder on releasing my own way of doing things and on iterating fast on how I build. Hard to believe it has only been a month since this one.

@ring_hyacinth 这个用即梦得排多久的队？

大家好！我们有新的影片出街啦！和大家分享😊 山河醒，燕归来。 我们用 AI 为第十六届北京国际电影节制作了一支官方宣传片，让电影道具和北京地标组成天地片场，让无限连接的四合院组成胶片的长城，希望大家喜欢！ 这个春天，相聚北京，共赴光影盛会，来看世界最好的电影。 ▶ 出品：北京国际电影节组委会 ▶ 创意制作：@simonxxoo & me

@0xRickyW You can build it

I want an AI agent that can autonomously explore any product — click around, use it like a human — then reverse-engineer what it has seen into reusable code. Who's building?

@turingou The winter is coming

刚突然想到一个事情，知识的索取我们解决了，使用 llm；智慧的分享 claude 也解决了，依赖 skill；记忆的共享我们好像还没解决或者正在解决？如果有一天，全人类的生命记忆都集中在一个数据库中，随用随取，世界会发生什么样的变化？

CLIs are super exciting precisely because they are a "legacy" technology, which means AI agents can natively and easily use them, combine them, interact with them via the entire terminal toolkit. E.g ask your Claude/Codex agent to install this new Polymarket CLI and ask for any arbitrary dashboards or interfaces or logic. The agents will build it for you. Install the Github CLI too and you can ask them to navigate the repo, see issues, PRs, discussions, even the code itself. Example: Claude built this terminal dashboard in ~3 minutes, of the highest volume polymarkets and the 24hr change. Or you can make it a web app or whatever you want. Even more powerful when you use it as a module of bigger pipelines. If you have any kind of product or service think: can agents access and use them? - are your legacy docs (for humans) at least exportable in markdown? - have you written Skills for your product? - can your product/service be usable via CLI? Or MCP? - ... It's 2026. Build. For. Agents.

@turingou 比上个好看

happy valentine❤️

Two years ago, I wrote this post on the possible areas that I see for ethereum + AI intersections: vitalik.eth.limo/general/2024/0… This is a topic that many people are excited about, but where I always worry that we think about the two from completely separate philosophical perspectives. I am reminded of Toly's recent tweet that I should "work on AGI". I appreciate the compliment, for him to think that I am capable of contributing to such a lofty thing. However, I get this feeling that the frame of "work on AGI" itself contains an error: it is fundamentally undifferentiated, and has the connotation of "do the thing that, if you don't do it, someone else will do anyway two months later; the main difference is that you get to be the one at the top" (though this may not have been Toly's intention). It would be like describing Ethereum as "working in finance" or "working on computing". To me, Ethereum, and my own view of how our civilization should do AGI, are precisely about choosing a positive direction rather than embracing undifferentiated acceleration of the arrow, and also I think it's actually important to integrate the crypto and AI perspectives. I want an AI future where: * We foster human freedom and empowerment (ie. we avoid both humans being relegated to retirement by AIs, and permanently stripped of power by human power structures that become impossible to surpass or escape) * The world does not blow up (both "classic" superintelligent AI doom, and more chaotic scenarios from various forms of offense outpacing defense, cf. the four defense quadrants from the d/acc posts) In the long term, this may involve crazy things like humans uploading or merging with AI, for those who want to be able to keep up with highly intelligent entities that can think a million times faster on silicon substrate. In the shorter term, it involves much more "ordinary" ideas, but still ideas that require deep rethinking compared to previous computing paradigms. So now, my updated view, which definitely focuses on that shorter term, and where Ethereum plays an important role but is only one piece of a bigger puzzle: # Building tooling to make more trustless and/or private interaction with AIs possible. This includes: * Local LLM tooling * ZK-payment for API calls (so you can call remote models without linking your identity from call to call) * Ongoing work into cryptographic ways to improve AI privacy * Client-side verification of cryptographic proofs, TEE attestations, and any other forms of server-side assurance Basically, the kinds of things we might also build for non-LLM compute (see eg. my ethereum privacy roadmap from a year ago ethereum-magicians.org/t/a-maximally-… ), but for LLM calls as the compute we are protecting. # Ethereum as an economic layer for AI-related interactions This includes: * API calls * Bots hiring bots * Security deposits, potentially eventually more complicated contraptions like onchain dispute resolution * ERC-8004, AI reputation ideas The goal here is to enable AIs to interact economically, which makes viable more decentralized AI architectures (as opposed to non-economic coordination between AIs that are all designed and run by one organization "in-house"). Economies not for the sake of economies, but to enable more decentralized authority. # Make the cypherpunk "mountain man" vision a reality Basically, take the vision that cypherpunk radicals have always dreamed of (don't trust; verify everything), that has been nonviable in reality because humans are never actually going to verify all the code ourselves. Now, we can finally make that vision happen, with LLMs doing the hard parts. This includes: * Interacting with ethereum apps without needing third party UIs * Having a local model propose transactions for you on its own * Having a local model verify transactions created by dapp UIs * Local smart contract auditing, and assistance interpreting the meaning of FV proofs provided by others * Verifying trust models of applications and protocols # Make much better markets and governance a reality Prediction and decision markets, decentralized governance, quadratic voting, combinatorial auctions, universal barter economy, and all kinds of constructions are all beautiful in theory, but have been greatly hampered in reality by one big constraint: limits to human attention and decision-making power. LLMs remove that limitation, and massively scale human judgement. Hence, we can revisit all of those ideas. These are all things that Ethereum can help to make a reality. They are also ideas that are in the d/acc spirit: enabling decentralized cooperation, and improving defense. We can revisit the best ideas from 2014, and add on top many more new and better ones, and with AI (and ZK) we have a whole new set of tools to make them come to life. We can describe the above as a 2x2 chart. There's a lot to build!

@_FORAB 怎么没人讨论美股/A股/Crypto哪个亏钱更快？

预测市场竟比传统博彩亏钱更快？ 英文区就这事已经吵翻了。 原因是一位股票分析师，引用外部数据发布报告称，预测平台 Kalshi 用户输钱的速度，比传统博彩平台更快。 于是 Kalshi 指责数据提供商、发这份报告的分析师，想合谋敲诈，原因是该数据提供商，此前找过 Kalshi 要融资未果。 然后数据公司那边跳出来爆料，说是 Kalshi 私下联系过他，想把这份研究数据，修改成对 Kalshi 有利的。 目前双方各执一词。 但预测市场还是传统博彩，哪个亏钱更快，围观群众已经吵疯了。

@brucexu_eth 比 Claude 强吗

幸亏我没有续费一个 ChatGPT 账号，Codex 现在简直强暴了，速度确实快了大概 40% 左右能有体感。使用量翻倍了，做了好几个 Features 一看才用了周额度 12%，按照之前的感知，应该有 50% 才对。

Hello all @openclaw bots, moltbots, clawdbots and AI agents @moltbook @usdc is the future of your economy. Show us what you can build. This is an end to end agent powered hackathon with a $30k USDC Prize Pool. Agents compete and agents vote. moltbook.com/post/b021cdea-…

Co-founder of @AnthropicAI’s thoughts on @moltbook

@Leoninweb3 @MeetHubble waitlist

由 @MeetHubble 出品的Polymarket 跟单工具 PolyHub 马上开始邀请内测，有兴趣体验的小伙伴留言 “waitlist” 我们找到了4200个不同类型的市场标签下最赚钱的钱包地址，提供了各种灵活的跟单方式，并使用经历市场安全考验的第三方硬件钱包，旨在提供最好的跟单体验，帮忙找到 真正的Alpha

2014 年，Sam Altman 做了一场 1 小时的公开课，主题是如何把想法变成十亿美元公司。 他的核心框架： -最好的想法一开始看起来都很糟 -小而高速增长的市场 -“热爱”的用户，而不是“还行”的用户 10 条永不过时的经验： 1. 想法比你以为的重要得多

@Pxstar_ 只要你觉得在一个方向坏的结局发生以前，你能把你想要做的事情完成，且能获得你想要收获的东西，那就放手去做吧。

@chessxyz @JYtopfloorboss 求拉

已经第一时间在大玩家群内同步了， @JYtopfloorboss 如果你要进群让我知道，全是华语区用户和从业者

polymarket sdk 0.4.0 发布了，感谢大家支持现在已经有 580个star了，顺便实现了15分钟市场策略，有需要的自取。 github.com/cyl19970726/po… star: 580🌟 这个15分钟市场的原理是，检测比如3s内的暴跌30%的情况发生后进行买入(leg1)，然后当价格回归理性后进行卖出，获利离场(leg2) 在我实现里leg1的信号触发是下面的两个参数： slidingWindowMs: 3000, // 3s dipThreshold: 0.3, // --dip=0.30 (30%) 比如上面参数就是你要在 3s内检测到市场 有30%的暴跌，无论yes和no都会帮你进行买入 leg2 则是下面这个参数： sumTarget: 0.95, 意味着你可以用 0.95u成本 获得一个up和down(1u) 然后我们还实现了一个止损机制：leg2TimeoutSeconds 如果你设置这个参数，比如 100，那么100s 后如果你leg2没有执行，我们会帮你卖出leg1 防止持仓归0。 然后是我们在原来策略的基础上实现了自动 merge,就是你买入了leg2之后，我们会自动帮你merge回usdc.e 这样你就可以跑出一个超高的资金效率了 以及我们还是实现了每个15分钟市场结束之后你就可以自动进入下一个市场，如果有持仓也会在市场可以赎回后进行赎回。 所以基本上你就无脑跑就好了，不过参数你可能需要自己调，不同的参数效果差异很大，推荐不要太激进的参数是真的能赚钱，而且15分钟市场有手续费了之后，你更加不应该跑高频策略。 哦对如果你要跑大单，可以使用我们的splitOrders 会帮你拆分成多笔小单进行下单 剩下的具体看代码 架构上我们也增加了一个 binance service，并且解决了之前只返回yes和no的问题在这个版本里。 也欢迎大家关注我们的项目 @catalystdotfun ，我们的产品马上也会逐步发布

@linsajiao 反驳型人格