Reflections on Palantir 關於 Palantir 的反思

A retrospective of an eight-year stint.
八年任期的回顧。

Oct 16, 2024 2024 年 10 月 16 日

Palantir is hot now. The company recently joined the S&P 500. The stock is on a tear, and the company is nearing a $100bn market cap. VCs chase ex-Palantir founders asking to invest.
Palantir 現在很熱門。該公司最近加入了標普 500 指數。股票表現強勁，市值接近 1,000 億美元。風險投資者追逐前 Palantir 創始人，希望投資。

For long-time employees and alumni of the company, this feels deeply weird. During the 2016-2020 era especially, telling people you worked at Palantir was unpopular. The company was seen as spy tech, NSA surveillance, or worse. There were regular protests outside the office. Even among people who didn’t have a problem with it morally, the company was dismissed as a consulting company masquerading as software, or, at best, a sophisticated form of talent arbitrage.
對於公司的老員工和校友來說，這種感覺非常奇怪。特別是在 2016 年至 2020 年期間，告訴人們你在 Palantir 工作是不受歡迎的。這家公司被視為間諜技術、NSA 監控，甚至更糟。辦公室外經常有抗議活動。即使在道德上沒有問題的人中間，這家公司也被視為一家偽裝成軟體公司的諮詢公司，或者最好的情況下是一種複雜的人才套利形式。

I left last year, but never wrote publicly about what I learned there. There’s also just a lot about the company people don’t understand. So this is my effort to explain some of that, as someone who worked there for eight years.
我去年離開了，但從未公開寫過我在那裡學到的東西。人們對這家公司也有很多不了解的地方。因此，這是我努力解釋其中一些的努力，作為在那裡工作了八年的人。

(Note: I’m writing this in my personal capacity, and don’t have a formal relationship with the company anymore. I’m long $PLTR.)
（備註：我以個人身份撰寫此文，並且不再與該公司有正式關係。我持有 $PLTR 的多頭頭寸。）

1. Why I joined 1. 為什麼我加入

I joined in summer 2015, initially in the newly-opened London office, before moving to Silicon Valley, and finally DC – as a forward deployed engineer. For context, the company was around 1500 people at the time; it had offices in Palo Alto (HQ), NYC, London, and a few other places. (It’s now 4000 or so people, and headquartered in Denver.)
我於 2015 年夏季加入，最初在新開設的倫敦辦公室工作，後來搬到矽谷，最後在華盛頓特區擔任前線工程師。在當時，公司大約有 1500 名員工；當時在帕洛阿爾托（總部）、紐約、倫敦和其他幾個地方設有辦公室。（現在大約有 4000 名員工，總部設在丹佛。）

Why did I join?
為什麼我加入了？

First, I wanted to work in ‘difficult’ industries on real, meaningful problems. My area of interest – for personal reasons - was healthcare and bio, which the company had a nascent presence in. The company was talking about working in industries like healthcare, aerospace, manufacturing, cybersecurity, and other industries that I felt were very important but that most people were not, at the time, working on. At the time the hot things were social networks (Facebook, LinkedIn, Quora, etc.) and other miscellaneous consumer apps (Dropbox, Uber, Airbnb) but very few companies were tackling what felt like the real, thorny parts of the economy. If you wanted to work on these ‘harder’ areas of the economy but also wanted a Silicon Valley work culture, Palantir was basically your only option for awhile.
首先，我想在真正有意義的問題上從事在‘困難’行業的工作。出於個人原因，我對醫療保健和生物領域感興趣，而公司在這方面還處於起步階段。公司當時正在談論在醫療保健、航空航天、製造業、網絡安全等行業開展工作，這些行業我覺得非常重要，但當時大多數人並沒有投入其中。當時熱門的是社交網絡（Facebook、LinkedIn、Quora 等）和其他雜項消費者應用（Dropbox、Uber、Airbnb），但很少有公司在應對經濟中感覺真正棘手的部分。如果你想在這些經濟中‘困難’的領域工作，同時又想要矽谷的工作文化，Palantir 基本上是你當時唯一的選擇。

My goal was to start a company, but I wanted (1) to go deep in one of these industries for a while first and learn real things about it; (2) to work for a US company and get a green card that way. Palantir offered both. That made it an easy choice.
我的目標是創辦一家公司，但我想（1）先在這些行業中深入一段時間，真正了解其中的事情；（2）為一家美國公司工作，通過這種方式獲得綠卡。Palantir 兩者兼具。這使得選擇變得輕鬆。

Second, talent density. I talked to some of the early people who started the healthcare vertical (Nick Perry, Lekan Wang, and Andrew Girvin) and was extremely impressed. I then interviewed with a bunch of the early business operations and strategy folks and came away even more impressed. These were seriously intense, competitive people who wanted to win, true believers; weird, fascinating people who read philosophy in their spare time, went on weird diets, and did 100-mile bike rides for fun. This, it turned out, was an inheritance from the Paypal mafia. Yishan Wong, who was early at Paypal, wrote about the importance of intensity:
第二，人才密度。我和一些早期開始醫療保健垂直領域的人（Nick Perry、Lekan Wang 和 Andrew Girvin）交談，印象深刻。然後我與一群早期業務運營和策略人員進行了面試，印象更深刻。這些人非常強烈、競爭激烈，他們想要贏，是真正的信徒；他們是怪異、迷人的人，業餘時間閱讀哲學，奇怪的飲食習慣，並且為了樂趣騎自行車 100 英里。原來，這是 Paypal 黑幫的遺產。Yishan Wong 是 Paypal 的早期成員，他寫過關於強度重要性的文章：

"In general, as I begin to survey more startups, I find that the talent level at PayPal is not uncommon for a Silicon Valley startup, but the differentiating factor may have been the level of intensity from the top: both Peter Thiel and Max Levchin were extremely intense people - hyper-competitive, hard-working, and unwilling to accept defeat. I think this sort of leadership is what pushes the "standard" talented team to be able to do great things and, subsequently, contributes to producing a wellspring of later achievements."
一般來說，當我開始調查更多初創公司時，我發現 PayPal 的人才水平對於矽谷初創公司來說並不罕見，但區別因素可能來自領導層的強烈程度：Peter Thiel 和 Max Levchin 都是非常強烈的人 - 高度競爭、勤奮工作，並且不願接受失敗。我認為這種領導風格是推動「標準」人才團隊能夠做出偉大成就的關鍵，並隨之促成後來的豐碩成就。

Palantir was an unusually intense and weird place. I remember my first time I talked to Stephen Cohen he had the A/C in his office set at 60, several weird-looking devices for minimizing CO2 content in the room, and had a giant pile of ice in a cup. Throughout the conversation, he kept chewing pieces of ice. (Apparently there are cognitive benefits to this.)
Palantir 是一個非常強烈和奇怪的地方。我記得第一次和 Stephen Cohen 談話時，他辦公室的空調設定在 60 度，房間裡有幾個看起來奇怪的設備用於減少二氧化碳含量，還有一大杯冰塊。在整個對話過程中，他一直在咀嚼冰塊。（顯然這樣做有認知益處。）

I also interviewed with the CEO, Alex Karp and talked to other members of the leadership team. I probably don’t need to convince you that Karp is weird - just watch an interview with him. I can’t say what Karp and I talked about, but he gives a good flavor for his style in a 2012 interview:
我還與首席執行官 Alex Karp 進行了訪談，並與其他領導團隊成員交談。我可能不需要說服你 Karp 很奇怪 - 只需觀看一次與他的訪談。我不能說 Karp 和我談論了什麼，但他在 2012 年的一次訪談中展現了他的風格。

I like to meet candidates with no data about them: no résumé, no preliminary discussions or job description, just the candidate and me in a room. I ask a fairly random question, one that is orthogonal to anything they would be doing at Palantir. I then watch how they disaggregate the question, if they appreciate how many different ways there are to see the same thing. I like to keep interviews short, about 10 minutes. Otherwise, people move into their learned responses and you don’t get a sense of who they really are.
我喜歡與沒有任何資料的候選人見面：沒有履歷，沒有初步討論或工作描述，只有候選人和我在一個房間裡。我會問一個相當隨機的問題，與 Palantir 的工作無關。然後觀察他們如何分解問題，看看他們是否意識到看待同一件事情有多種不同的方式。我喜歡讓面試簡短，大約 10 分鐘。否則，人們會進入他們學習的回答，你就無法真正了解他們是誰。

My interviews were often not about work or software at all – one of my interviews we just spent an hour talking about Wittgenstein. Note that both Peter Thiel and Alex Karp were philosophy grads. Thiel’s lecture notes had come out not long before (https://blakemasters.tumblr.com/peter-thiels-cs183-startup) and they discussed Shakespeare, Tolstoy, Girard (then unknown, now a cliché) and more.
我的面試通常根本不是關於工作或軟體的 - 我們其中一次面試花了一個小時談論維特根斯坦。請注意，彼得・蒂爾和亞歷克斯・卡普都是哲學畢業生。蒂爾的講義不久前就公開了（https://blakemasters.tumblr.com/peter-thiels-cs183-startup），他們討論了莎士比亞、托爾斯泰、吉拉爾（當時不知名，現在成了陳詞濫調）等等。

The combo of intellectual grandiosity and intense competitiveness was a perfect fit for me. It’s still hard to find today, in fact - many people have copied the ‘hardcore’ working culture and the ‘this is the Marines’ vibe, but few have the intellectual atmosphere, the sense of being involved in a rich set of ideas. This is hard to LARP - your founders and early employees have to be genuinely interesting intellectual thinkers. The main companies that come to mind which have nailed this combination today are OpenAI and Anthropic. It’s no surprise they’re talent magnets.1
智慧的宏偉和激烈的競爭性的組合非常適合我。事實上，今天仍然很難找到這種組合 - 許多人模仿了 “極端” 工作文化和 “這就是海軍陸戰隊” 的氛圍，但很少有智慧的氛圍，缺乏參與豐富思想集合的感覺。這很難模擬 - 您的創始人和早期員工必須是真正有趣的智慧思想家。當今成功實現這種組合的主要公司是 OpenAI 和 Anthropic。他們成為人才磁鐵並不奇怪。

2. Forward deployed 2. 前線部署

When I joined, Palantir was divided up into two types of engineers:
當我加入時，Palantir 被分為兩種工程師：

Engineers who work with customers, sometimes known as FDEs, forward deployed engineers.
與客戶合作的工程師，有時被稱為 FDEs，即前線部署工程師。
Engineers who work on the core product team (product development - PD), and rarely go visit customers.
在核心產品團隊（產品開發 - PD）工作的工程師很少拜訪客戶。

FDEs were typically expected to ‘go onsite’ to the customer’s offices and work from there 3-4 days per week, which meant a ton of travel. This is, and was, highly unusual for a Silicon Valley company.
FDEs 通常被期望 “現場工作”，在客戶辦公室工作 3-4 天，這意味著大量的出差。對於矽谷公司來說，這是非常不尋常的。

There’s a lot to unpack about this model, but the key idea is that you gain intricate knowledge of business processes in difficult industries (manufacturing, healthcare, intel, aerospace, etc.) and then use that knowledge to design software that actually solves the problem. The PD engineers then ‘productize’ what the FDEs build, and – more generally – build software that provides leverage for the FDEs to do their work better and faster.2
這個模型有很多要探討的地方，但關鍵想法是您將獲得對於困難行業（製造業、醫療保健、晶片製造、航空航太等）的業務流程的細緻知識，然後利用這些知識來設計實際解決問題的軟體。PD 工程師們接著將 FDE 們建立的東西 “產品化”，並且更廣泛地建立提供 FDE 們更好更快地完成工作的軟體。

This is how much of the Foundry product took initial shape: FDEs went to customer sites, had to do a bunch of cruft work manually, and PD engineers built tools that automated the cruft work. Need to bring in data from SAP or AWS? Here’s Magritte (a data ingestion tool). Need to visualize data? Here’s Contour (a point and click visualization tool). Need to spin up a quick web app? Here’s Workshop (a Retool-like UI for making webapps). Eventually, you had a damn good set of tools clustered around the loose theme of ‘integrate data and make it useful somehow’.
這就是鑄造產品最初形成的方式：FDEs 前往客戶現場，必須手動進行大量瑣碎工作，而 PD 工程師則建立了自動化瑣碎工作的工具。需要從 SAP 或 AWS 帶入數據嗎？這裡有 Magritte（一個數據輸入工具）。需要視覺化數據嗎？這裡有 Contour（一個點擊式視覺化工具）。需要快速啟動網頁應用程式嗎？這裡有 Workshop（一個類似 Retool 的 UI，用於製作 Web 應用程式）。最終，您將擁有一套非常好的工具，圍繞著 “整合數據並以某種方式使其有用” 的主題。

At the time, it was seen as a radical step to give customers access to these tools — they weren’t in a state for that — but now this drives 50%+ of the company’s revenue, and it’s called Foundry. Viewed this way, Palantir pulled off a rare services company → product company pivot: in 2016, descriptions of it as a Silicon Valley services company were not totally off the mark, but in 2024 they are deeply off the mark, because the company successfully built an enterprise data platform using the lessons from those early years, and it shows in the gross margins - 80% gross margins in 2023. These are software margins. Compare to Accenture: 32%.
當時，讓客戶使用這些工具被視為一個激進的舉措 - 它們當時還沒有達到那個水準 - 但現在這帶動了公司 50% 以上的收入，並被稱為 Foundry。從這個角度來看，Palantir 實現了一個罕見的服務公司→產品公司的轉變：2016 年，將其描述為硅谷服務公司並不完全準確，但到了 2024 年，這種描述已大相徑庭，因為該公司成功地利用了早期的經驗建立了企業數據平台，這在毛利率上表現出來 - 2023 年的毛利率達到 80%。這些是軟體毛利率。與埃森哲（Accenture）相比：32%。

Tyler Cowen has a wonderful saying, ‘context is that which is scarce’, and you could say it’s the foundational insight of this model. Going onsite to your customers – the startup guru Steve Blank calls this “getting out of the building” – means you capture the tacit knowledge of how they work, not just the flattened ‘list of requirements’ model that enterprise software typically relies on. The company believed this to a hilarious degree: it was routine to get a call from someone and have to book a first-thing-next-morning flight to somewhere extremely random; “get on a plane first, ask questions later” was the cultural bias. This resulted in out of control travel spend for a long time — many of us ended up getting United 1K or similar — but it also meant an intense decade-long learning cycle which eventually paid off.
泰勒・考恩有一句很棒的說法，“背景是稀缺的”，你可以說這是這個模型的基本見解。親自前往客戶現場 —— 初創業大師史蒂夫・布蘭克稱之為 “走出建築物”—— 意味著你捕捉到了他們工作方式的默默知識，而不僅僅是企業軟件通常依賴的 “需求清單” 模型。公司深信這一點：經常會接到一個來電，然後不得不立即訂一個隔天清晨的極其隨機的航班；“先上飛機，後問問題” 是文化偏見。這導致長時間旅行支出失控 —— 我們中的許多人最終成為聯合航空 1K 會員或類似的 —— 但這也意味著一個密集的長達十年的學習週期，最終取得了回報。

My first real customer engagement was with Airbus, the airplane manufacturer based in France, and I moved out to Toulouse for a year and worked in the factory alongside the manufacturing people four days a week to help build the version of our software there.
我的第一個真正的客戶參與是與法國飛機製造商空中巴士公司進行的，我搬到圖盧茲待了一年，在工廠裡和製造人員一起工作，每週四天，協助建立我們軟體的版本。

My first month in Toulouse, I couldn’t fly out of the city because the air traffic controllers were on strike every weekend. Welcome to France. (I jest - France is great. Also, Airbus planes are magnificent. It’s a truly engineering-centric company. The CEO is always a trained aeronautical engineer, not some MBA. Unlike… anyway.)
在圖盧茲的第一個月，我每個週末都無法離開這個城市，因為空中交通管制員都在罷工。歡迎來到法國。（我開玩笑 - 法國很棒。此外，空中巴士飛機真是壯觀。這是一家真正以工程為中心的公司。首席執行官總是受過航空工程師的訓練，而不是某個工商管理碩士。不像... 無論如何。）

The CEO told us his biggest problem was scaling up A350 manufacturing. So we ended up building software to directly tackle that problem. I sometimes describe it as “Asana, but for building planes”. You took disparate sources of data — work orders, missing parts, quality issues (“non-conformities”) — and put them in a nice interface, with the ability to check off work and see what other teams are doing, where the parts are, what the schedule is, and so on. Allow them the ability to search (including fuzzy/semantic search) previous quality issues and see how they were addressed. These are all sort of basic software things, but you’ve seen how crappy enterprise software can be - just deploying these ‘best practice’ UIs to the real world is insanely powerful. This ended up helping to drive the A350 manufacturing surge and successfully 4x’ing the pace of manufacturing while keeping Airbus’s high standards of quality.
首席執行官告訴我們，他最大的問題是擴大 A350 的製造規模。因此，我們最終開發了軟件來直接應對這個問題。有時我會形容它為 “Asana，但用於建造飛機”。您可以將不同來源的數據（工作訂單、缺少零件、質量問題（“不符合”））放入一個良好的界面中，具有勾選工作和查看其他團隊正在做什麼、零件在哪裡、進度如何等功能。讓他們有能力搜索（包括模糊 / 語義搜索）以前的質量問題並查看它們是如何解決的。這些都是基本的軟件功能，但您已經看到企業軟件可能有多糟糕 - 將這些‘最佳實踐’界面部署到現實世界中是非常強大的。這最終有助於推動 A350 的製造激增，成功地將製造速度提高了 4 倍，同時保持了空中巴士的高質量標準。

This made the software hard to describe concisely - it wasn’t just a database or a spreadsheet, it was an end-to-end solution to that specific problem, and to hell with generalizability. Your job was to solve the problem, and not worry about overfitting; PD’s job was to take whatever you’d built and generalize it, with the goal of selling it elsewhere.
這使得軟體難以簡潔描述 - 它不僅僅是一個數據庫或試算表，而是一個端到端的解決方案，針對特定問題，與其一般性說明無關。你的工作是解決問題，不必擔心過度配適；PD 的工作是接手你所建立的任何東西並加以概括，目的是在其他地方銷售。

The A350 final assembly line, in Toulouse. I hung out here most days. It was awe-inspiring. Screenshot from here.
A350 最終裝配線，在圖盧茲。我大多數日子都在這裡晃蕩。令人敬畏。從這裡截圖。

FDEs tend to write code that gets the job done fast, which usually means – politely – technical debt and hacky workarounds. PD engineers write software that scales cleanly, works for multiple use cases, and doesn’t break. One of the key ‘secrets’ of the company is that generating deep, sustaining enterprise value requires both. BD engineers tend to have high pain tolerance, the social and political skills needed to embed yourself deep in a foreign company and gain customer trust, and high velocity – you need to build something that delivers a kernel of value fast so that customers realize you’re the real deal. It helped that customers had hilariously low expectations of most software contractors, who were typically implementors of SAP or other software like that, and worked on years-long ‘waterfall’ style timescales. So when a ragtag team of 20-something kids showed up to the customer site and built real software that people could use within a week or two, people noticed.
FDEs 傾向於編寫能快速完成任務的程式碼，這通常意味著 - 禮貌地說 - 技術債和權宜之計。PD 工程師編寫能夠乾淨擴展、適用於多種用例且不易出錯的軟體。公司的一個關鍵 “秘密” 之一是，生成深厚、持久的企業價值需要兩者兼備。BD 工程師傾向具有高痛苦忍受力，以及在外國公司深入嵌入自己並贏得客戶信任所需的社交和政治技能，以及高速度 - 您需要快速建立能提供價值核心的東西，讓客戶意識到您是真實的。客戶對大多數軟體承包商的期望非常低，他們通常是 SAP 或其他類似軟體的實施者，並按照長達數年的 “瀑布” 風格時間表工作。因此，當一隊 20 多歲的年輕人出現在客戶現場並在一兩周內建立了人們可以使用的真實軟體時，人們開始注意到。

This two-pronged model made for a powerful engine. Customer teams were often small (4-5 people) and operated fast and autonomously; there were many of them, all learning fast, and the core product team’s job was to take those learnings and build the main platform.
這個雙軌模型為一個強大的引擎。客戶團隊通常很小（4-5 人），運作迅速且自主；有許多這樣的團隊，都在快速學習，而核心產品團隊的工作是吸收這些經驗教訓並建立主要平台。

When we were allowed to work within an organization, this tended to work very well. The obstacles were mostly political. Every time you see the government give another $110 million contract to Deloitte for building a website that doesn’t work, or a healthcare.gov style debacle, or SFUSD spending $40 million to implement a payroll system that - again - doesn’t work, you are seeing politics beat substance. See SpaceX vs. NASA as another example.
當我們被允許在組織內工作時，這通常運作得非常好。障礙大多是政治上的。每當你看到政府再次向德勤公司授予 1.1 億美元的合同來建立一個無法運作的網站，或類似 healthcare.gov 的災難，或舊金山聯合校區花費 4,000 萬美元來實施一個 - 再次 - 無法運作的薪資系統時，你正在看到政治戰勝實質。另一個例子是 SpaceX 與 NASA 的對比。

The world needs more companies like SpaceX, and Palantir, that differentiate on execution - achieving the outcome - not on playing political games or building narrow point solutions that don’t hit the goal.
世界需要更多像 SpaceX 和 Palantir 這樣的公司，它們在執行上有所區別 - 實現結果 - 而不是玩政治遊戲或建立不能達到目標的狹隘解決方案。

3. Secrets 3. 秘密

Another key thing FDEs did was data integration, a term that puts most people to sleep. This was (and still is) the core of what the company does, and its importance was underrated by most observers for years. In fact, it’s only now with the advent of AI that people are starting to realize the importance of having clean, curated, easy-to-access data for the enterprise. (See: the ‘it’ in AI models is the dataset).
FDE 們所做的另一個關鍵事情是數據整合，這個術語讓大多數人感到昏昏欲睡。這是（現在仍然是）公司業務的核心，多年來大多數觀察者都低估了它的重要性。事實上，直到現在隨著人工智慧的出現，人們才開始意識到企業擁有乾淨、經過精心策劃、易於訪問的數據的重要性。（參見：AI 模型中的 “it” 是數據集）。

In simple terms, ‘data integration’ means (a) gaining access to enterprise data, which usually means negotiating with ‘data owners’ in an organization (b) cleaning it and sometimes transforming it so that it’s usable (c) putting it somewhere everyone can access it. Much of the base, foundational software in Palantir’s main software platform (Foundry) is just tooling to make this task easier and faster.
簡單來說，“數據整合” 意味著（a）獲取企業數據的訪問權，通常需要與組織中的 “數據擁有者” 協商（b）清理數據，有時轉換數據以便使用（c）將數據放在每個人都可以訪問的地方。Palantir 主要軟件平台（Foundry）中的許多基礎軟件只是為了使這項任務更容易、更快速而設計的工具。

Why is data integration so hard? The data is often in different formats that aren’t easily analyzed by computers – PDFs, notebooks, Excel files (my god, so many Excel files) and so on. But often what really gets in the way is organizational politics: a team, or group, controls a key data source, the reason for their existence is that they are the gatekeepers to that data source, and they typically justify their existence in a corporation by being the gatekeepers of that data source (and, often, providing analyses of that data).3 This politics can be a formidable obstacle to overcome, and in some cases led to hilarious outcomes – you’d have a company buying an 8-12 week pilot, and we’d spend all 8-12 weeks just getting data access, and the final week scrambling to have something to demo.
為什麼數據集成這麼困難？數據通常以不同的格式存在，這些格式並不容易被計算機分析 - 如 PDF、筆記本、Excel 文件（我的天啊，有這麼多 Excel 文件）等。但真正阻礙的通常是組織政治：一個團隊或群體控制著一個關鍵數據來源，他們存在的原因是他們是該數據來源的門戶守衛，通常通過成為該數據來源的門戶守衛（並且經常提供該數據的分析）來證明他們在公司中的存在。這種政治問題可能是一個難以克服的障礙，在某些情況下甚至導致滑稽的結果 - 你可能會看到一家公司購買了一個 8-12 周的試點項目，而我們花了整整 8-12 周的時間來獲取數據訪問權，最後一周匆忙準備演示材料。

The other ‘secret’ Palantir figured out early is that data access tussles were partly about genuine data security concerns, and could be alleviated through building security controls into the data integration layer of the platform - at all levels. This meant role-based access controls, row-level policies, security markings, audit trails, and a ton of other data security features that other companies are still catching up to. Because of these features, implementing Palantir often made companies’ data more secure, not less.4
Palantir 早期發現的另一個「秘密」是，數據訪問爭端在一定程度上是關於真正的數據安全問題，可以通過在平台的數據整合層中建立安全控制來緩解 - 在所有層面上。這意味著基於角色的訪問控制、行級政策、安全標記、審計軌跡，以及其他許多數據安全功能，其他公司仍在努力追趕。由於這些功能，實施 Palantir 通常使公司的數據更加安全，而不是更不安全。

4. Notes on culture 4. 文化備註

The overall ‘vibe’ of the company was more of a messianic cult than a normal software company. But importantly, it seemed that criticism was highly tolerated and welcomed – one person showed me an email chain where an entry-level software engineer was having an open, contentious argument with a Director of the company with the entire company (around a thousand people) cc’d. As a rationalist-brained philosophy graduate, this particular point was deeply important to me – I wasn’t interested in joining an uncritical cult. But a cult of skeptical people who cared deeply and wanted to argue about where the world was going and how software fit into it – existentially – that was interesting to me.5
公司的整體 “氛圍” 更像是一個救世主邪教，而不是一家正常的軟體公司。但重要的是，批評似乎被高度容忍和歡迎 - 有人向我展示了一封電子郵件鏈，其中一名初級軟體工程師正在與公司的一位董事進行公開的、有爭議的爭論，整個公司（約一千人）都被抄送。作為一名理性主義的哲學畢業生，這一點對我來說非常重要 - 我對加入一個不加批判的邪教不感興趣。但一群懷疑論者，他們深深關心並願意爭論世界的走向以及軟體如何在其中扮演角色 - 在存在層面上 - 對我來說是有趣的。

I’m not sure if they still do this, but at the time when you joined they sent you a copy of Impro, The Looming Tower (9/11 book), Interviewing Users, and Getting Things Done. I also got an early PDF version of what became Ray Dalio’s Principles. This set the tone. The Looming Tower was obvious enough – the company was founded partly as a response to 9/11 and what Peter felt were the inevitable violations of civil liberties that would follow, and the context was valuable. But why Impro?
我不確定他們是否仍然這樣做，但在你加入時，他們會寄給你《Improv》、《The Looming Tower》（911 書）、《Interviewing Users》和《Getting Things Done》的副本。我還收到了成為雷・達利歐《Principles》的早期 PDF 版本。這樣設定了基調。《The Looming Tower》顯而易見 —— 公司在某種程度上是作為對 911 事件的回應而成立的，彼得認為隨之而來的不可避免的侵犯公民自由，這個背景是有價值的。但為什麼是《Improv》呢？

Being a successful FDE required an unusual sensitivity to social context – what you really had to do was partner with your corporate (or government) counterparts at the highest level and gain their trust, which often required playing political games. Impro is popular with nerds partly because it breaks down social behavior mechanistically. The vocabulary of the company was saturated with Impro-isms – ‘casting’ is an example. Johnstone discusses how the same actor can play ‘high status’ or ‘low status’ just by changing parts of their physical behavior – for example, keeping your head still while talking is high status, whereas moving your head side to side a lot is low status. Standing tall with your hands showing is high status, slouching with your hands in your pocket is low status. And so on. If you didn’t know all this, you were unlikely to succeed in a customer environment. Which meant you were unlikely to integrate customer data or get people to use your software. Which meant failure.
成為成功的 FDE 需要對社會背景具有非尋常的敏感度 - 你真正需要做的是與公司（或政府）的同僚在最高層次建立夥伴關係並贏得他們的信任，這通常需要玩政治遊戲。Impro 在書呆子中很受歡迎，部分原因是它將社會行為機械化地分解。公司的詞彙中充斥著 Impro 主義 - “casting” 就是一個例子。約翰斯頓討論了同一演員如何可以通過改變其身體行為的某些部分來扮演 “高地位” 或 “低地位” - 例如，說話時保持頭部靜止是高地位，而頻繁搖頭是低地位。站得高大並展示雙手是高地位，低頭駝背並將雙手放在口袋裡是低地位。如果你不知道這一切，你在客戶環境中成功的可能性很小。這意味著你不太可能整合客戶數據或讓人們使用你的軟件。這意味著失敗。

This is one reason why former FDEs tend to be great founders. (There are usually more ex-Palantir founders than there are ex-Googlers in each YC batch, despite there being ~50x more Google employees.) Good founders have an instinct for reading rooms, group dynamics, and power. This isn’t usually talked about, but it’s critical: founding a successful company is about taking part in negotiation after negotiation after negotiation, and winning (on net). Hiring, sales, fundraising are all negotiations at their core. It’s hard to be great at negotiating without having these instincts for human behavior. This is something Palantir teaches FDEs, and is hard to learn at other Valley companies.
這就是為什麼前 FDEs 往往成為優秀的創辦人之一的原因。（每個 YC 批次中，前 Palantir 創辦人通常比前 Google 員工多，儘管 Google 員工數量大約是 Google 的 50 倍。）優秀的創辦人具有閱讀房間、群體動態和權力的直覺。這通常不被討論，但這是至關重要的：創辦一家成功公司是關於參與一次又一次的談判，並贏得（總體上）。招聘、銷售、籌款本質上都是談判。如果沒有對人類行為的直覺，很難在談判方面表現出色。這是 Palantir 教導 FDEs 的東西，在其他瓦利公司很難學到。

Another is that FDEs have to be good at understanding things. Your effectiveness directly correlates to how quickly you can learn to speak the customer’s language and really drill down into how their business works. If you’re working with hospitals, you quickly learn to talk about capacity management and patient throughput vs. just saying “help you improve your healthcare”. Same with drug discovery, health insurance, informatics, cancer immunotherapy, and so on; all have specialized vocabularies, and the people who do well tend to be great at learning them fast.
另一個是 FDE 必須善於理解事物。您的效率直接與您能多快學會說客戶的語言並深入了解他們的業務運作有關。如果您正在與醫院合作，您會很快學會談論容量管理和病人通過率，而不僅僅是說 “幫助您改善醫療保健”。藥物發現、健康保險、信息學、癌症免疫療法等等也是如此；所有這些領域都有專業詞彙，而表現出色的人往往擅長快速學習它們。

One of my favorite insights from Tyler Cowen’s book ‘Talent’ is that the most talented people tend to develop their own vocabularies and memes, and these serve as entry points to a whole intellectual world constructed by that person. Tyler himself is of course a great example of this. Any MR reader can name 10+ Tylerisms instantly - ‘model this’, ‘context is that which is scarce’, ‘solve for the equilibrium’, ‘the great stagnation’ are all examples. You can find others who are great at this. Thiel is one. Elon is another (“multiplanetary species”, “preserving the light of consciousness”, etc. are all memes). Trump, Yudkowsky, gwern, SSC, Paul Graham, all of them regularly coin memes. It turns out that this is a good proxy for impact.
Tyler Cowen 的書《天賦》中我最喜歡的見解之一是，最有才華的人往往會發展出自己的詞彙和迷因，這些詞彙和迷因成為進入由該人建構的整個智識世界的入口。Tyler 本人當然是一個很好的例子。任何 MR 讀者都可以立即舉出 10 個以上的 Tylerisms - 例如「模擬這個」、「背景是稀缺的東西」、「為均衡解決問題」、「偉大的停滯」等。你可以找到其他擅長這一點的人。Thiel 是其中之一。Elon 是另一個（例如「多行星物種」、「保存意識之光」等都是迷因）。Trump、Yudkowsky、gwern、SSC、Paul Graham，他們都經常創造迷因。結果表明，這是影響力的一個良好代理。

This insight goes for companies, too, and Palantir had its own, vast set of terms, some of which are obscure enough that “what does Palantir actually do?” became a meme online. ‘Ontology’ is an old one, but then there is ‘impl’, ‘artist’s colony’, ‘compounding’, ‘the 36 chambers’, ‘dots’, ‘metabolizing pain’, ‘gamma radiation’, and so on. The point isn’t to explain all of these terms, each of which compresses a whole set of rich insights; it’s that when you’re looking for companies to join, you could do worse than look for a rich internal language or vocabulary that helps you think about things in a more interesting way.
這種洞察力也適用於公司，Palantir 有自己龐大的術語集，其中一些足夠晦澀，以至於「Palantir 到底在做什麼？」成為網絡迷因。'Ontology' 是一個老術語，但還有 'impl'、'artist's colony'、'compounding'、'the 36 chambers'、'dots'、'metabolizing pain'、'gamma radiation' 等等。重點不是解釋所有這些術語，每個都壓縮了一整套豐富的洞察力；而是當你在尋找要加入的公司時，你可以尋找一個豐富的內部語言或詞彙，幫助你以更有趣的方式思考事情。

When Palantir’s name comes up, most people think of Peter Thiel. But many of these terms came from early employees, especially Shyam Sankar, who’s now the President of the company. Still, Peter is deeply influential in the company culture, even though he wasn’t operationally involved with the company at all during the time I was there. This document, written by Joe Lonsdale, was previously an internal document but made public at some point and gives a flavor for the type of cultural principles.
當提到 Palantir 時，大多數人會想到 Peter Thiel。但這些術語中許多是來自早期員工，尤其是現任公司總裁 Shyam Sankar。儘管 Peter 在我在公司期間並未參與業務運作，但他對公司文化有著深遠的影響。這份由 Joe Lonsdale 撰寫的文件原本是內部文件，但後來某個時候公開，展現了該公司文化原則的風格。

One of the things that (I think) came from Peter was the idea of not giving people titles. When I was there, everyone had the “forward deployed engineer” title, more or less, and apart from that there were five or six Directors and the CEO. Occasionally someone would make up a different title (one guy I know called himself “Head of Special Situations”, which I thought was hilarious) but these never really caught on. It’s straightforward to trace this back to Peter’s Girardian beliefs: if you create titles, people start coveting them, and this ends up creating competitive politics inside the company that undermines internal unity. Better to just give everyone the same title and make them go focus on the goal instead.
（我認為）從彼得那裡學到的一件事是不給人們頭銜的概念。當我在那裡時，幾乎每個人都有 “前線部署工程師” 的頭銜，除此之外還有五六位董事和首席執行官。偶爾會有人編造不同的頭銜（我認識的一個人自稱 “特殊情況主管”，我覺得很滑稽），但這些從未真正流行起來。可以很容易地追溯到彼得的吉拉爾迪安信仰：如果你創建頭銜，人們就會開始垂涎慾望，這最終導致公司內部出現競爭政治，破壞內部團結。最好只給每個人相同的頭銜，讓他們專注於目標。

There are plenty of good critiques of the ‘flat hierarchy’ stance -- The Tyranny of Structurelessness is a great one – and it largely seems to have fallen out of fashion in modern startups, where you quickly get CEO, COO, VPs, Founding Engineers, and so on. But my experience is that it worked well at Palantir. Some people were more influential than others, but the influence was usually based on some impressive accomplishment, and most importantly nobody could tell anyone else what to do. So it didn’t matter if somebody was influential or thought your idea was dumb, you could ignore them and go build something if you thought it was the right thing to do. On top of that, the culture valorized such people: stories were told of some engineer ignoring a Director and building something that ended up being a critical piece of infrastructure, and this was held up as an example to imitate.
有許多對 “扁平結構” 立場的良好批評 ——《無結構的暴政》是一個很好的例子 —— 在現代初創企業中似乎已經不再流行，你很快就會有 CEO、COO、VP、創始工程師等。但我的經驗是，在 Palantir 這種模式運作得很好。有些人比其他人更有影響力，但這種影響力通常是基於一些令人印象深刻的成就，最重要的是沒有人可以告訴別人該做什麼。因此，如果有人有影響力或認為你的想法很蠢，你可以忽略他們，並且如果你認為這是正確的事情，你可以去建立一些東西。除此之外，這種文化也讚美這樣的人：有些工程師無視一位主管的建議，建立了一些最終成為關鍵基礎設施的東西，這被視為一個值得效仿的例子。

The cost of this was that the company often felt like there was no clear strategy or direction, more like a Petri dish of smart people building little fiefdoms and going off in random directions. But it was incredibly generative. It’s underrated just how many novel UI concepts and ideas came out of that company. Only some of these now have non-Palantir equivalents, e.g. Hex, Retool, Airflow all have some components that were first developed at Palantir. The company’s doing the same for AI now – the tooling for deploying LLMs at large enterprises is powerful.
這樣做的代價是，公司常常感覺缺乏明確的策略或方向，更像是一個由聰明人建立小封地並朝著不同方向前進的皮特里皿。但這是非常有創造力的。人們往往低估了這家公司產生了多少新穎的 UI 概念和想法。現在只有一些擁有非 Palantir 對應產品，例如 Hex、Retool、Airflow 都有一些最初在 Palantir 開發的組件。這家公司現在也在為人工智慧做同樣的事情 - 用於在大型企業部署 LLMs 的工具非常強大。

The ‘no titles’ thing also meant that people came in and out of fashion very quickly, inside the company. Because everyone had the same title, you had to gauge influence through other means, and those were things like “who seems really tight with this Director right now” or “who is leading this product initiative which seems important”, not “this person is the VP of so and so”. The result was a sort of hero-shithead rollercoaster at scale – somebody would be very influential for awhile, then mysteriously disappear and not be working on anything visible for months, and you wouldn’t ever be totally sure what happened.
“沒有頭銜” 這件事也意味著公司內的人們很快就會進入和退出時尚。因為每個人都有相同的頭銜，你必須通過其他方式來衡量影響力，這些方式包括 “誰現在似乎與這位董事非常密切” 或 “誰正在領導這個看起來很重要的產品倡議”，而不是 “這個人是某某副總裁”。結果是一種規模上的英雄 - 混蛋過山車 - 有人會在一段時間內具有很大的影響力，然後神秘地消失，幾個月內不會參與任何可見的工作，你永遠不會完全確定發生了什麼事。

5. Bat-signals 5. 蝙蝠信號

Another thing I can trace back to Peter is the idea of talent bat-signals. Having started my own company now (in stealth for the moment), I appreciate this a lot more: recruiting good people is hard, and you need a differentiated source of talent. If you’re just competing against Facebook/Google for the same set of Stanford CS grads every year, you’re going to lose. That means you need a set of talent that is (a) interested in joining you in particular, over other companies (b) a way of reaching them at scale. Palantir had several differentiated sources of recruiting alpha.
我可以追溯到彼得的另一個想法是人才蝙蝠信號。現在我自己創業了（目前處於隱藏狀態），我更加珍惜這一點：招聘優秀人才很困難，你需要一個與眾不同的人才來源。如果你每年只是與 Facebook/Google 競爭同一批斯坦福 CS 畢業生，你將會輸掉。這意味著你需要一組（a）對特別想加入你的人才感興趣，而不是其他公司（b）以規模方式接觸他們的人才。Palantir 有幾個不同的招聘優勢來源。

First, there were all the people who were pro defense/intelligence work back when that wasn’t fashionable, which selected for, e.g., smart engineers from the Midwest or red states more than usual, and also plenty of smart ex-army, ex-CIA/NSA types who wanted to serve the USA but also saw the appeal in working for a Silicon Valley company. My first day at the company, I was at my team’s internal onboarding with another guy, who looked a bit older than me. I asked him what he’d done before Palantir. With a deadpan expression, he looked me in the eye and said “I worked at the agency for 15 years”. I was then introduced to my first lead, who was a former SWAT cop in Ohio (!) and an Army vet.
首先，當時支持國防 / 情報工作的人數眾多，這在當時並不時尚，這吸引了來自中西部或紅色州的聰明工程師，以及許多聰明的前軍人、前中情局 / 國家安全局人員，他們希望為美國服務，同時也看到在矽谷公司工作的吸引力。我在公司的第一天，和另一個看起來比我大一點的人一起參加了團隊的內部入職培訓。我問他在 Palantir 之前做過什麼。他面無表情地看著我，說：“我在機構工作了 15 年。” 然後我被介紹給我的第一位主管，他是俄亥俄州的前 SWAT 警察（！）和一名陸軍老兵。

There were lots of these people, many extremely talented, and they mostly weren’t joining Google. Palantir was the only real ‘beacon’ for these types, and the company was loud about supporting the military, being patriotic, and so on, when that was deeply unfashionable. That set up a highly effective, unique bat-signal. (Now there’s Anduril, and a plethora of defence and manufacturing startups).6
這些人很多，許多人才橫溢，但他們大多數並沒有加入谷歌。Palantir 是這些人的唯一真正 “燈塔”，當時公司大聲支持軍方、愛國等，而這在當時是非常不時髦的。這樣設置了一個非常有效、獨特的蝙蝠信號。（現在有 Anduril，以及眾多的國防和製造初創公司）。

Second, you had to be weird to want to join the company, at least after the initial hype wave died down (and especially during the Trump years, when the company was a pariah). Partly this was the aggressive ‘mission focus’ type branding back when this was uncommon, but also the company was loud about the fact that people worked long hours, were paid lower than market, and had to travel a lot. Meanwhile, we were being kicked out of Silicon Valley job fairs for working with the government. All of this selected for a certain type of person: somebody who can think for themselves, and doesn’t over-index on a bad news story.
其次，您必須有點古怪才會想加入公司，至少在最初的熱潮過後（尤其是在特朗普時期，當時公司被視為社會的棄兒）。部分原因是當時公司採取了積極的 “使命專注” 品牌定位，這在當時是罕見的，而且公司也公開表示人們工作時間長，薪酬低於市場水平，並且需要大量出差。與此同時，我們因為與政府合作而被踢出了硅谷的招聘會。所有這些都選擇了某種類型的人：那些能夠獨立思考，並且不會過度關注壞消息的人。

6. Morality 6. 道德

The morality question is a fascinating one. The company is unabashedly pro-West, a stance I mostly agree with – a world more CCP-aligned or Russia-aligned seems like a bad one to me, and that’s the choice that’s on the table.7 It’s easy to critique free countries when you live in one, harder when you’ve experienced the alternative (as I have - I spent a few childhood years in a repressive country). So I had no problem with the company helping the military, even when I disagreed with some of the things the military was doing.
道德問題是一個迷人的問題。這家公司毫不掩飾地支持西方，這是我大多數同意的立場 - 對我來說，一個更加支持中共或俄羅斯的世界似乎是一個糟糕的選擇，而這就是當前的選擇。在生活在一個自由國家時批評自由國家很容易，但當你體驗過其他選擇時（就像我曾經體驗過 - 我在一個壓迫的國家度過了幾年的童年），這就變得更難了。因此，即使我不同意軍方的一些做法，我也不會對公司幫助軍方感到困擾。

But doesn’t the military sometimes do bad things? Of course - I was opposed to the Iraq war. This gets to the crux of the matter: working at the company was neither 100% morally good — because sometimes we’d be helping agencies that had goals I’d disagree with — nor 100% bad: the government does a lot of good things, and helping them do it more efficiently by providing software that doesn’t suck is a noble thing. One way of clarifying the morality question is to break down the company’s work into three buckets – these categories aren’t perfect, but bear with me:
但軍方有時不是做壞事嗎？當然 - 我反對伊拉克戰爭。這就是問題的關鍵所在：在公司工作既不是 100% 道德上正確 - 因為有時我們會幫助一些我不同意目標的機構 - 也不是 100% 壞的：政府做了很多好事，透過提供不差勁的軟體讓他們更有效率地完成這些事是一件高尚的事。澄清道德問題的一種方法是將公司的工作分為三個類別 - 這些分類並不完美，但請耐心等待：

Morally neutral. Normal corporate work, e.g. FedEx, CVS, finance companies, tech companies, and so on. Some people might have a problem with it, but on the whole people feel fine about these things.
道德上中立。正常的企業工作，例如聯邦快遞、CVS、金融公司、科技公司等等。有些人可能對此有意見，但整體而言，人們對這些事情感覺良好。
Unambiguously good. For example, anti-pandemic response with the CDC; anti-child pornography work with NCMEC; and so on. Most people would agree these are good things to work on.
毫無疑問地好。例如，與疾控中心合作的抗疫應對工作；與 NCMEC 合作的打擊兒童色情工作；等等。大多數人都會同意這些是值得投入精力的好事。
Grey areas. By this I mean I mean ‘involve morally thorny, difficult decisions’: examples include health insurance, immigration enforcement, oil companies, the military, spy agencies, police/crime, and so on.
灰色地帶。我的意思是指「涉及道德棘手、困難的決定」：例如健康保險、移民執法、石油公司、軍事、間諜機構、警察 / 犯罪等。

Every engineer faces a choice: you can work on things like Google search or the Facebook news feed, all of which seem like marginally good things and basically fall into category 1. You can also go work on category 2 things like GiveDirectly or OpenPhilanthropy or whatever.
每位工程師都面臨著一個選擇：你可以從事像 Google 搜尋或 Facebook 新聞動態等看似邊緣好事並基本上屬於第一類的工作。你也可以轉而從事像 GiveDirectly 或 OpenPhilanthropy 等第二類事物的工作。

The critical case against Palantir seemed to be something like “you shouldn’t work on category 3 things, because sometimes this involves making morally bad decisions”. An example was immigration enforcement during 2016-2020, aspects of which many people were uncomfortable with.
對 Palantir 的關鍵指控似乎是類似於 “你不應該從事第三類事務，因為有時這涉及做出道德上不良的決定”。一個例子是在 2016 年至 2020 年期間的移民執法，其中的某些方面讓許多人感到不舒服。

But it seems to me that ignoring category 3 entirely, and just disengaging with it, is also an abdication of responsibility. Institutions in category 3 need to exist. The USA is defended by people with guns. The police have to enforce the law, and - in my experience - even people who are morally uncomfortable with some aspects of policing are quick to call the police if their own home has been robbed. Oil companies have to provide energy. Health insurers have to make difficult decisions all the time. Yes, there are unsavory aspects to all of these things. But do we just disengage from all of these institutions entirely, and let them sort themselves out?
但對我來說，完全忽略第三類，並與之脫鉤，也是一種責任的放棄。第三類機構需要存在。美國由持槍的人保衛。警察必須執行法律，而根據我的經驗，即使對某些警察工作方面感到道德上不舒服的人，如果自己的家被搶，也會迅速報警。石油公司必須提供能源。健康保險公司必須時刻做出困難的決定。是的，所有這些事情都有不好的一面。但我們是不是應該完全與所有這些機構脫鉤，讓它們自行解決呢？

I don’t believe there is a clear answer to whether you should work with category 3 customers; it’s a case by case thing. Palantir’s answer to this is something like “we will work with most category 3 organizations, unless they’re clearly bad, and we’ll trust the democratic process to get them trending in a good direction over time”. Thus:
我不相信是否應該與第 3 類客戶合作有一個明確的答案；這是一種情況。 Palantir 對此的回答大致是 “我們將與大多數第 3 類組織合作，除非它們明顯不好，我們將信任民主過程隨著時間推動它們走向良好方向”。因此：

On the ICE question, they disengaged from ERO (Enforcement and Removal Operations) during the Trump era, while continuing to work with HSI (Homeland Security Investigations).
在 ICE 問題上，他們在特朗普時代與 ERO（執法和驅逐行動）脫鉤，同時繼續與 HSI（國土安全部調查）合作。
They did work with most other category 3 organizations, on the argument that they’re mostly doing good in the world, even though it’s easy to point to bad things they did as well.
他們與大多數其他三級組織合作，理由是他們在世界上大多數情況下都在做好事，即使也很容易指出他們做過壞事。
- I can’t speak to specific details here, but Palantir software is partly responsible for stopping multiple terror attacks. I believe this fact alone vindicates this stance.
  我無法在這裡談論具體細節，但 Palantir 軟體部分負責阻止多次恐怖襲擊。我相信這個事實本身就證明了這個立場。

This is an uncomfortable stance for many, precisely because you’re not guaranteed to be doing 100% good at all times. You’re at the mercy of history, in some ways, and you’re betting that (a) more good is being done than bad (b) being in the room is better than not. This was good enough for me. Others preferred to go elsewhere.
這對許多人來說是一個令人不舒服的立場，正因為你並不保證一直做到 100% 的好事。在某種程度上，你受歷史支配，而你打賭的是：(a) 做的好事比壞事多 (b) 在場比不在場好。這對我來說已經足夠了。其他人則更喜歡去別處。

The danger of this stance, of course, is that it becomes a fully general argument for doing whatever the power structure wants. You are just amplifying existing processes. This is where the ‘case by case’ comes in: there’s no general answer, you have to be specific. For my own part, I spent most of my time there working on healthcare and bio stuff, and I feel good about my contributions. I’m betting the people who stopped the terror attacks feel good about theirs, too. Or the people who distributed medicines during the pandemic.
這種立場的危險當然在於，它變成了一個完全一般性的論點，支持權力結構想要做的任何事情。你只是放大現有的過程。這就是「具體情況具體分析」的地方：沒有一般性答案，你必須具體問題具體分析。就我個人而言，我在那裡大部分時間都在從事醫療保健和生物相關工作，對自己的貢獻感到滿意。我打賭停止恐怖襲擊的人也對自己感到滿意。或者在大流行期間分發藥物的人。

Even though the tide has shifted and working on these ‘thorny’ areas is now trendy, these remain relevant questions for technologists. AI is a good example – many people are uncomfortable with some of the consequences of deploying AI. Maybe AI gets used for hacking; maybe deepfakes make the world worse in all these ways; maybe it causes job losses. But there are also major benefits to AI (Dario Amodei articulates some of these well in a recent essay).
盡管潮流已經轉變，並且在這些「棘手」領域工作現在很時髦，這些問題對技術人員仍然很重要。人工智慧是一個很好的例子 - 許多人對部署人工智慧的一些後果感到不舒服。也許人工智慧被用於黑客攻擊；也許深偽造使世界在所有這些方面變得更糟；也許它導致失業。但人工智慧也有重大好處（Dario Amodei 在最近的一篇文章中清楚地表達了其中一些）。

As with Palantir, working on AI probably isn’t 100% morally good, nor is it 100% evil. Not engaging with it – or calling for a pause/stop, which is a fantasy – is unlikely to be the best stance. Even if you don’t work at OpenAI or Anthropic, if you’re someone who could plausibly work in AI-related issues, you probably want to do so in some way. There are easy cases: build evals, work on alignment, work on societal resilience. But my claim here is that the grey area is worth engaging in too: work on government AI policy. Deploy AI into areas like healthcare. Sure, it’ll be difficult. Plunge in.8
與 Palantir 一樣，從事人工智慧可能不是 100% 道德良好，也不是 100% 邪惡。不參與其中 - 或呼籲暫停 / 停止，這是一種幻想 - 不太可能是最佳立場。即使你不在 OpenAI 或 Anthropic 工作，如果你是一個可能從事人工智慧相關問題的人，你可能想以某種方式參與其中。有一些簡單的情況：建立評估，致力於對齊，致力於社會韌性。但我在這裡提出的是，灰色地帶也值得參與：從事政府人工智慧政策工作。將人工智慧應用於醫療等領域。當然，這將是困難的。踏入其中。8

When I think about the most influential people in AI today, they are almost all people in the room - whether at an AI lab, in government, or at an influential think tank. I’d rather be one of those than one of the pontificators. Sure, it’ll involve difficult decisions. But it’s better to be in the room when things happen, even if you later have to leave and sound the alarm.
當我想到當今在人工智慧領域中最具影響力的人時，幾乎都是在房間裡的人 - 無論是在人工智慧實驗室、政府部門，還是在具有影響力的智庫。我寧願成為其中之一，而不是成為那些唯我論者之一。當然，這將涉及艱難的決定。但最好是在事情發生時在場，即使之後不得不離開並發出警報。

7. What next? 7. 接下來呢？

Do I remain bullish on the company? Yes.
我對這家公司仍然持樂觀態度嗎？是的。

The big productivity gains of this AI cycle are going to come when AI starts providing leverage to the large companies and businesses of this era - in industries like manufacturing, defense, logistics, healthcare and more. Palantir has spent a decade working with these companies. AI agents will eventually drive many core business workflows, and these agents will rely on read/write access to critical business data. Spending a decade integrating enterprise data is the critical foundation for deploying AI to the enterprise. The opportunity is massive.
這個人工智慧時代的巨大生產力增長將在人工智慧開始為製造業、國防、物流、醫療保健等行業的大型企業提供槓桿時出現。Palantir 已花費十年與這些公司合作。人工智慧代理將最終推動許多核心業務工作流程，這些代理將依賴對關鍵業務數據的讀寫訪問。花費十年整合企業數據是將人工智慧應用於企業的關鍵基礎。機會是巨大的。

As for me, I’m carrying out my long-awaited master plan and starting a company next. Yes, there will be a government component to it. The team is great, and yes we’re hiring. We even talk about Wittgenstein sometimes.
至於我，我正在實施我期待已久的總體計劃，接著要創辦一家公司。是的，這將包含政府部分。團隊很棒，是的，我們正在招聘。有時我們甚至會討論維特根斯坦。

Thanks to Rohit Krishnan, Tyler Cowen, Samir Unni, Sebastian Caliri, Mark Bissell, and Vipul Shekhawat for their feedback on this post.
感謝 Rohit Krishnan、Tyler Cowen、Samir Unni、Sebastian Caliri、Mark Bissell 和 Vipul Shekhawat 對這篇文章的反饋。

Both OpenAI and Palantir required backing by rich people with deep belief and willingness to fund them for years without any apparent or obvious breakthroughs (Elon/YC Research, and Peter Thiel, respectively). Palantir floundered for years, barely getting any real traction in the gov space, and doing the opposite of the ‘lean startup’ thing; OpenAI spent several years being outdone (at least, hype-wise) by DeepMind before language models came along. As Sam Altman pointed out:
OpenAI 和 Palantir 都需要富有且深信不疑、願意長期資助而又沒有明顯突破的富豪支持（分別是 Elon/YC Research 和 Peter Thiel）。Palantir 在多年間一直處於困境，幾乎沒有在政府領域取得實質進展，並且做了與「精益創業」相反的事情；OpenAI 在語言模型出現之前，花了幾年時間被 DeepMind（至少在炒作方面）超越。正如 Sam Altman 所指出的：

“OpenAI went against all of the YC advice,” Altman told Stripe cofounder and fellow billionaire John Collison
“OpenAI 違背了 YC 的所有建議，” Altman 告訴 Stripe 聯合創始人兼億萬富翁 John Collison
He rattled off the ways: “It took us four and half years to launch a product. We’re going to be the most capital-intensive startup in Silicon Valley history. We were building a technology without any idea of who our customers were going to be or what they were going to use it for.”
他列舉了這些方式：“我們花了四年半的時間才推出一個產品。我們將成為矽谷歷史上資本投入最多的初創企業。我們在建立技術時並不知道客戶將是誰，以及他們將用它做什麼。”
On Saturday, Altman tweeted: "chatgpt has no social features or built-in sharing, you have to sign up before you can use it, no inherent viral loop, etc. seriously questioning the years of advice i gave to startups."
上週六，Altman 在推特上發文說："chatgpt 沒有社交功能或內建分享功能，您必須在使用之前註冊，沒有內在的病毒式循環等等。我對我給初創公司的建議多年來感到非常懷疑。"

There’s something to this correlation: by making the company about something other than making money (civil liberties; AI god) you attract true believers from the start, who in turn create the highly generative intellectual culture that persists once you eventually find success.
這種相關性有其道理：讓公司不只是為了賺錢（民事自由；AI 神），你就能從一開始吸引真正的信徒，他們又會創造高度生成的智識文化，這種文化會持續存在，直到最終取得成功。

It’s hard to replicate, though - you need a visionary billionaire and an overlooked sector of the economy. AI/ML was not hot in 2015; govtech was not hot in 2003.
雖然很難複製，但你需要一位有遠見的億萬富翁和一個被忽視的經濟領域。人工智慧 / 機器學習在 2015 年並不熱門；政府科技在 2003 年也不是熱門話題。

Ted Mabrey’s essay on the FDE model here is good:
Ted Mabrey 對 FDE 模型的文章在這裡很好：