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发现了一个真正开箱即用的通用 AI Agent 随便点进去就能看到一大堆现成的专家：股票、金融、电商、生产力、内容运营……各种领域都有一键添加的 Agent，直接聊天就能用，完全不用自己配置 prompt、搭环境 还可以用最强的 Claude 4.8 模型（平台每天送 200 免费积分），也可以自己接入其他模型的 API 用，实测体验挺丝滑的 我拿最近市场最热门的存储芯片公司 —— Micron Technology（ $MU）做了一次实测,这次没有自己写 Prompt，也没有搭工作流 直接打开 @EasyClawBot，添加现成的 Stock Master Agent，然后我先安装了Serenity-skill，然后一句话： 用 Serenity 的框架研究股票，给出直接的投资建议 整个过程大概几分钟,Agent 自动完成： ✅ 市场分析 ✅ 产业链卡点变化分析 ✅ 基本面与技术面分析 ✅ 估值与风险评估 ✅ 最终投资建议输出 最后给出的核心结论让我有点意外：当前阶段不建议追高 $MU Agent 认为： 📈 基本面依然非常强 📈 AI 带动 HBM 需求持续增长 📈 存储行业景气度仍处于高位 但问题在于： 股价上涨速度已经明显快于基本面改善速度 对于不同投资者，它给出了完全不同的策略： ▶ 已持有： 考虑分批兑现利润，利用移动止盈锁定收益，而不是继续加仓 ▶ 空仓： 继续跟踪，不追高，等待周期回调带来的更优介入机会 ▶ 低风险投资者： 直接回避周期顶部区域的高波动 有意思的是，它还列出了接下来真正值得盯的三个关键指标： ① DRAM / HBM 价格是否开始走弱 ② HBM4 是否进入下一代 AI 芯片量产订单 ③ 存储巨头未来两年的资本开支节奏 这些其实正是决定存储周期下一阶段走势的核心变量 Agent给我的感觉更像是在复刻一个成熟投资人的研究流程： 热点事件 → 数据搜集 → 行业分析 → 风险判断 → 投资决策 我演示的整个投研过程几乎没有学习成本 不用研究 Prompt 不用配置环境 不用自己搭 Agent 直接选专家，直接提问 几分钟就能得到一份结构化投研报告 对于经常研究美股、AI、半导体板块的人来说，这种体验确实有点惊艳 #AIAgent# #StockMarket# #Micron# #MU# #Investing# #Semiconductors# #HBM# #Claude# #EasyClaw# #AIInvesting#

Here is my AI investing guide. Sitting here August 2026, my current best thoughts are as follows: 1. LPS (Land Power Shell) is still the most obvious and fastest path to cash on cash returns. Lots of value can be assembled and traded quickly at this layer. And as data centers get more pushback, energized land can explode in value. Very bullish here. I’ve stepped into this layer very aggressively. My partner @anitavlallian and I have acquired almost 6GW coming online in a ramp from today thru 2029 of grid power and behind the meter. 2. Silicon - I helped get @GroqInc off the ground in 2015 and we licensed it to @nvidia for $20B Dec2025. I won’t invest or incubate anything in this layer now. The perf demands of the chips are too high, manufacturing precision is too complex and supply chain influence to get adjacent components like memory isn’t possible for a startup anymore. Lots of capital will be wasted here chasing Groq and Cerebras’ success. Note that both startups made sense a decade ago when these constraints were much more modest. 3. Clouds - Clouds are very very lucrative but very hard to build and very expensive and technically complicated to maintain. And as alignment becomes a more important issue, I expect the clouds will be asked to build robust KYC and attest to it. This makes the risk:reward ratio skewed. I don’t want to be responsible when the USG says a cloud allowed a bad actor to do something bad because of poor KYC. 4. Models are complicated. The big open question is how much of the revenue being generated by them today is because of tokenmaxxing and poor model behavior. If it’s a lot, then the annualized revenues will diminish meaningfully even as token consumption inflects upwards. This is the big economic question at this layer. 5. Harnesses are where the action is and why I started @8090solutions two years ago. In a nutshell, the harness helps enterprises owns their proprietary context (what Alex Karp calls their ‘alpha’). This is an enterprise’s data, workflows, evals, and business rules. A harness that gives this to an enterprise is what creates very low model-agnostic switching costs, which further reinforces my views of #4# above. 6. Applications will be another long term winner along with harnesses. This is where the differentiation between “off the shelf” and “custom time and materials” melts away. Every company, with the right harness, can now imbue their alpha into the software that runs their company. I expect this to mean that “off the shelf” is largely replaced with custom software creating a huge opportunity to write these solutions for companies. Build once and sell repeatedly is a laggard GTM motion for a SaaS world that isn’t needed here. Think custom by design, alpha embedded, proprietary by nature. Fin. Good luck to all the players!