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An Econ PhD student at the 20th ranked program who is working on stuff they are passionate about will have a better job market than one at MIT who's been doing nothing but phd-app-maxxing since undergrad. People get confused by this because they don't observe *how* successful people came about their insane knowledge bases. It wasn't by relentlessly grinding away at stuff because they had to. They look at Scott Kominers and say "if i grind and learn as much math as he did, i will be successful." You can't! *You* can't learn as much math as Kominers because he gets energized by configuration results for type ii lattices. You will burn out if you try to do it this way. You cannot, through grind alone, learn more about the economics of cities than Glaeser, or about how to maximize a value function than Acemoglu. Research careers are long. Most people give up and stop working on research (graph is share of elite PhD graduates with at least one publication in year X after graduation). If you're starting a PhD, you're presumably doing it to have a successful 40-year research career. The number one factor in whether that happens is not which program you get into, it's whether you find a research angle that energizes you enough to push through the endless barriers an academic career throws in your path. This is why a lot of the received wisdom around PhD applications is wrong. If you're 100% consumed by the predoc rat race already, it's going to be a long, hard road ahead. Obv you still have to do admissions, you should study a lot for the GRE, sigh it seems like taking real analysis is probably worth it. But spending time on the things that energize you about economics is a no-brainer, whether it's policy, or blogging, or whatever, you gotta do the things that light your fire and make you want to be on this road.

Amazon 员工正在刷 Token Amazon 内部出现了一个新词：tokenmaxxing，意思是刷 AI 用量数据。 起因是 Amazon 今年给开发者定了硬指标：每周超过 80% 的开发者必须使用 AI 工具，并且在内部排行榜上追踪每个人的 Token（AI 模型处理的数据单位）消耗量。公司说这些数据不会用于绩效考核，但员工不信。“经理们确实在看，”一位员工说，“追踪用量会制造扭曲的激励，有些人把它当竞赛。” 于是一些员工开始用公司最近大规模部署的内部工具 MeshClaw 来刷分。MeshClaw 可以创建 AI Agent 代替用户操作办公软件，比如发起代码部署、处理邮件、操作 Slack。员工让它跑一些本来不需要 AI 做的事，纯粹为了把 Token 消耗数字刷上去。 MeshClaw 的灵感来自今年 2 月走红的开源项目 OpenClaw，后者允许用户在自己电脑上本地运行 AI Agent。Amazon 内部有三十多人参与开发了这个工具，内部文档的描述颇为科幻：“它会在夜间做梦来整合白天学到的东西，开会时帮你盯着部署，你醒来之前就把邮件分好了优先级。” 不只 Amazon，Meta 员工也在干一样的事，在内部排行榜上刷 Token 用量。 这背后是整个硅谷大厂的共同焦虑：巨额 AI 投入需要看到回报。Amazon 今年资本开支预计 2000 亿美元，绝大部分砸向 AI 和数据中心。公司需要证明这些钱花得值，最直观的方式就是让员工用起来，于是就有了指标、排行榜、和随之而来的数据注水。 也有员工对 MeshClaw 本身的安全性表示担忧。一个能代替你操作各种办公系统的 AI Agent，一旦出错或执行了非预期操作，后果可能不小。“默认的安全设置让我害怕，”一位员工说，“我不会放任它自己去干活。” 【注：tokenmaxxing 这个词模仿了网络俚语 -maxxing（把某件事做到极致）的构词法，在这里特指刷 AI Token 用量。】 来源：

The top Hermes integrations to give your agent superpowers: 1. Firecrawl Basically web search built for agents. It's better than the native Hermes web search because it gives you clean web data, so responses come back faster and uses fewer tokens. I keep this on by default. 2. Browserbase Gives Hermes browser access for actually interacting with sites. Logging in, clicking buttons, booking stuff, anything that needs a real browser session. Hermes will automatically pick between Firecrawl and Browserbase depending on what the task needs, so you just plug both in. 3. Google Workspace Gmail, Calendar, Drive, Docs, and Sheets in one connector. If Hermes can't read your inbox, see your calendar, or write to your docs, it can't really work for you. Plug this in first. 4. Reddit The best signal you'll find on what people actually think about any product, niche, or problem (bc its real opinions from real users) Amazing for market research. 5. YouTube transcripts Pulls captions from any video. Long podcasts, tutorials, interviews etc become searchable notes in seconds. Probably the highest-leverage research integration nobody plugs in. 6. Discord I host my business in Discord, so this one's huge for me. I plug Hermes into different channels and have it run specific workflows in each. Example: I have a dedicated customer support channel where Hermes scans my email every morning for support tickets and drops them in organized. 7. GitHub Code, issues, PRs. Turns Hermes into an actual engineering teammate. Non-negotiable if you write code. 8. Stripe Payments, customers, failed charges, refunds. You can just ask "why did this customer churn" and get a real answer. Also can't wait for this...Stripe is releasing agentic payments, so soon Hermes will be able to actually book stuff with your card. 9. Bland (or Twilio) Gives Hermes a voice so it can place real phone calls (like booking reservations etc). I love listening to the recordings haha 10. Apify Pre-built scrapers for X, LinkedIn, Instagram, Google Maps, etc. The way to get X data without paying $5k/mo for the official API. 11. Readwise Every highlight you've ever saved from books, articles, tweets, and podcasts, all queryable. Solves the "dead knowledge" problem. 12. Granola (or Fathom) Searchable transcripts of every meeting you've had. Hermes can answer "what did that client say about pricing last month" instantly. 13. Obsidian For Karpathy LLM wiki second-brain maxxing. If I had to set up only 5, I'd do Firecrawl, Browserbase, Google Workspace, GitHub, and Obsidian. Covers ~80% of what most people need. I use Composio to add these in one click, makes setup basically zero effort instead of messing w technical stuff. Anything I'm missing?? What's in your stack?

ABG CMO is a mindset Why is Twitter gatekeeping ABGs? We are in San Francisco. We can identity as anything Join our ABG maxxing workshop tomorrow Saturday afternoon in SF with @dear_kxtie @0xJuliechen and me!! Learn how to do makeup, farm Twitter, debate the meaning of ABG, and more Comment for invite link!