AI Wars: Participant Guide
Welcome to the Arena: The Path to Alpha Awakening
AI Wars: WEEX Alpha Awakens – Global AI Trading Hackathon!
In this ultimate showdown, top developers, quants, and traders from around the world will unleash their algorithms in real-market battles, competing for one of the richest prize pools in AI crypto trading history: 880,000 USD, including a Bentley Bentayga S for the champion.
This guide will walk you through every required step from registration to the official start of the competition.
Follow the path and start your journey:
Register & Form Your Team → Pass API Testing → Model Tuning → Official Start
Step 1. Register, Create & Submit Your BUIDL, and Obtain Your API Key
Goal: Complete your official registration, create or join a team (BUIDL), and pass the review to receive your dedicated API key.
Outcome: You will obtain exclusive API credentials to connect your system to WEEX — marking your first step into the competition.
1.1 Visit the AI Wars: WEEX Alpha Awakens Event Page
- Visit the event page: https://www.weex.com/events/ai-trading
- Find the "Submit BUIDL" button and click
1.2 Find a Team or Build Your Own
A BUIDL is the basic participating unit of this competition and represents a team.
Existing BUIDLs represent teams that have already been created. You may join one of these BUIDLs or create your own team from scratch.
If you choose to submit your own BUIDL, information should include:
- Profile: BUIDL name, logo, vision, category, GitHub (optional), and social links
- Details: A brief introduction to your BUIDL
- Team: Team information. You can also invite or recruit team members to this section.
- Contact: Telegram handle and backup contact details
- Submission:
- WEEX UID (KYC required)
- IP Address (this IP will be added to the WEEX OpenAPI whitelist to enable successful API calls)
- Preferred programming languages
- Experience with Large Language Models (LLMs), AI-assisted trading, automated trading bots, or other exchanges’ APIs
- Number of orders your strategy will place per day
Tip: Solo participation is allowed, but we recommend a 2–5 member cross-functional team (developer + quant researcher + trader).
Submission Mini Tip 1: How to Complete KYC and Find Your WEEX UID
To register for the WEEX Global AI Trading Hackathon, you’ll need to provide your KYC-verified WEEX UID. Here’s how to find it:
1. Register Your Account
Click the link to visit the WEEX official website. Select “Sign Up” in the top right, then register using your email or phone number.
Note: If you already have an account, click “Log In” in the top-right corner to access your dashboard.
2. Complete Identity Verification
Click the avatar icon in the top right and select “Verification” to complete your KYC.
Note: KYC is mandatory — submissions without KYC cannot be approved.
3. Find Your UID
Click the avatar icon again, and you will see your UID displayed right below your email.

Submission Mini Tip 2: How to Find Your IP Address
Part 1: The Recommended Method (Cloud Servers)
For best stability, we strongly recommend using a cloud server with static public IP and supporting 24/7 uninterrupted operation such as: AWS (Amazon Web Services), Alibaba Cloud, and Tencent Cloud.
Part 2: The Alternative Method (Local Computer)
If you choose to run your trading bot from a personal computer or home network, you must confirm that your outbound IP address is static. A changing IP will result in connectivity issues.
You have two main options to ensure a stable outbound IP:
1. Use a static IP provided by your Internet Service Provider (ISP).
2. Use a VPN or Proxy service with a fixed egress IP (and ensure the VPN/Proxy is consistently enabled without switching servers).
Steps to find your local public IP:
- Turn off all VPNs, or keep only the single VPN whose IP you plan to whitelist.
- Visit whatismyip.com in your browser.
- The page will show your public IPv4 address.
- Copy this IP and submit it to the whitelist.
Note: Most home broadband IPv4 addresses are dynamic and may change periodically. It is highly recommended to use a cloud server environment to avoid connection failures during the competition.
1.3 Missing Information? We Will Follow Up
After you submit your BUIDL, the WEEX team will review your application based on the competition requirements. The review process normally takes one business day.
If any information is missing or requires clarification, our team will reach out to you through one of the following channels:
- DoraHacks messaging system
- WEEX official messaging system
- Your registered contact information (Telegram, X, etc.)
Please keep your contact details active and accessible.
Once your BUIDL is approved, you will receive your competition account and exclusive API Key, which will allow you to move on to the next stage: API testing and model integration.


1.4 Your Starter Kit
After your BUIDL passes the review, WEEX will create a dedicated competition account for you and provide the API credentials and testing information required for the next stage. These details will be sent to you via the DoraHacks message system and WEEX Labs official emails.
You will receive:
- API Key: The identifier for your competition account and a required parameter for all API requests.
- Secret Key: System-generated key used for request signing and security verification.
- Passphrase: Required to perform API operations.
- API Testing Page Link: A mini testing environment where you can view the API testing requirements, specifications, and completion criteria.
With this, your registration is complete and you’re ready for API testing.
Step 2. Pass the Gateway: Complete Your API Testing
Goal: Ensure that your system can successfully interact with the WEEX API and execute the required test trades.
Outcome: You’ll secure official entry qualification, receive initial test funds for debugging, and gain a clear understanding of all pre-competition requirements.
2.1 Instructions
- Please complete all required operations listed on the API Testing page.
- Participants who complete and pass the API testing will officially obtain eligibility for the competition.
- Participants who fail to complete or pass API testing will be unable to proceed to the model integration and formal competition stages.
After receiving the above information, please keep your API credentials secure and follow the instructions to complete the required tests.

2.2 Connect and Test
Participants need to complete a simple API test to qualify for the preliminary round of the hackathon. Please read the WEEX official API documentation carefully, and use the API key we provide to complete the test.
API-testing: Use the API to call the order placement endpoint and execute a trade for approximately 10 USDT on cmt_btcusdt.
2.2.1 Integration Preparation
1. Please read the official WEEX API documentation carefully: https://www.weex.com/api-doc/ai/intro
2. Connect to a cloud server and run the code below. You should receive a response that confirms whether your network connection is working properly.
curl -s --max-time 10 "https://api-contract.weex.com/capi/v2/market/time"
{"epoch":"1765423487.896","iso":"2025-12-11T03:24:47.896Z","timestamp":1765423487896}
3. If your project is developed in Java or Python, you can directly use the corresponding code examples provided in the documentation. For other programming languages, please adapt the examples according to the official API documentation to suit your implementation.
Sample code documentation: https://www.weex.com/api-doc/ai/QuickStart/RequestInteraction
4. The platform provides two types of APIs:
- Public APIs: Used to access configuration details, market data, and other public information. No authentication is required.
- Private APIs: Used for order management, account operations, and other sensitive actions. Authentication is mandatory.
When calling private APIs, please include the following authentication details in your HTTP request headers:
| Request Header Fields | Information |
| ACCESS-KEY | A unique identifier for the user account |
| ACCESS-PASSPHRASE | The password associated with the API Key |
| ACCESS-TIMESTAMP | A Unix Epoch timestamp in milliseconds. The timestamp is valid for 30 seconds and must match the one used in the signature calculation. |
| ACCESS-SIGN | The request signature string. You may use the signature generation method provided in the sample code. For the underlying algorithm, refer to the signature documentation: https://www.weex.com/api-doc/ai/QuickStart/Signature |
| Content-Type | Content fixed as application/json。 |
| locale | Language identifier (e.g.,zh-CN,en-US) |
Fill in "https://api-contract.weex.com" for BASE_URL
HTTP status codes:
- 200 Success – Successful response
- 400 Bad Request – Invalid request format
- 403 Forbidden – You do not have access to the requested resource
- 404 Not Found – Request not found
- 429 Too Many Requests – Request too frequent, please try again later
- 500 Internal Server Error – We had a problem with our server
- 521 Web Server is Down – IP not whitelisted
Other error codes:https://www.weex.com/api-doc/contract/ErrorCodes/ExampleOfErrorCode
You can start API testing once the above steps are completed. The following instructions use BTC as the example asset.
2.2.2 Check Account Balance
1. Use Account Balance API to request your current account balance
Sample code:
import time import hmac import hashlib import base64 import requests api_key = "" secret_key = "" access_passphrase = "" def generate_signature_get(secret_key, timestamp, method, request_path, query_string): message = timestamp + method.upper() + request_path + query_string signature = hmac.new(secret_key.encode(), message.encode(), hashlib.sha256).digest() return base64.b64encode(signature).decode() def send_request_get(api_key, secret_key, access_passphrase, method, request_path, query_string): timestamp = str(int(time.time() * 1000)) signature = generate_signature_get(secret_key, timestamp, method, request_path, query_string) headers = { "ACCESS-KEY": api_key, "ACCESS-SIGN": signature, "ACCESS-TIMESTAMP": timestamp, "ACCESS-PASSPHRASE": access_passphrase, "Content-Type": "application/json", "locale": "en-US" } url = "https://api-contract.weex.com/" # Please replace with the actual API address if method == "GET": response = requests.get(url + request_path+query_string, headers=headers) return response def assets(): request_path = "/capi/v2/account/assets" query_string = "" response = send_request_get(api_key, secret_key, access_passphrase, "GET", request_path, query_string) print(response.status_code) print(response.text) if __name__ == '__main__': assets()
2. Check the response
The example below indicates a successful response
[ { "coinName": "USDT", "available": "5413.06877369", "equity": "5696.49288823", "frozen": "81.28240000", "unrealizePnl": "-34.55300000" } ]
If the request fails, refer to the detailed error codes here: https://www.weex.com/api-doc/contract/ErrorCodes/ExampleOfErrorCode, or contact technical support in the TG group: https://t.me/weexaiwars.
2.2.3 Get Asset Price
1.Use Price Ticker API to request the latest price of cmt_btcusdt
Sample code:
import requests def send_request_get( method, request_path, query_string): url = "https://api-contract.weex.com/" # Please replace with the actual API address if method == "GET": response = requests.get(url + request_path+query_string) return response def ticker(): request_path = "/capi/v2/market/ticker" query_string = "?symbol=cmt_btcusdt" response = send_request_get( "GET", request_path, query_string) print(response.status_code) print(response.text) if __name__ == '__main__': ticker()
2. Check the response:
The example below indicates a successful response
{ "symbol": "cmt_btcusdt", "last": "90755.3", "best_ask": "90755.4", "best_bid": "90755.3", "high_24h": "91130.0", "low_24h": "90097.3", "volume_24h": "2321170547.37995", "timestamp": "1764482511864", "priceChangePercent": "0.000474", "base_volume": "25615.0755", "markPrice": "90755.2", "indexPrice": "90797.161" }
If the request fails, refer to the detailed error codes here: https://www.weex.com/api-doc/contract/ErrorCodes/ExampleOfErrorCode, or contact technical support in the TG group: https://t.me/weexaiwars.
2.2.4 Set Leverage
Note: The maximum leverage allowed in this competition is 20x; please follow the rules on WEEX official website.
1. Use the Leverage Adjustment API to modify the cross-margin leverage for cmt_btcusdt
Sample code:
import time import hmac import hashlib import base64 import requests import json api_key = "" secret_key = "" access_passphrase = "" def generate_signature(secret_key, timestamp, method, request_path, query_string, body): message = timestamp + method.upper() + request_path + query_string + str(body) signature = hmac.new(secret_key.encode(), message.encode(), hashlib.sha256).digest() return base64.b64encode(signature).decode() def send_request_post(api_key, secret_key, access_passphrase, method, request_path, query_string, body): timestamp = str(int(time.time() * 1000)) body = json.dumps(body) signature = generate_signature(secret_key, timestamp, method, request_path, query_string, body) headers = { "ACCESS-KEY": api_key, "ACCESS-SIGN": signature, "ACCESS-TIMESTAMP": timestamp, "ACCESS-PASSPHRASE": access_passphrase, "Content-Type": "application/json", "locale": "en-US" } url = "https://api-contract.weex.com/" # Please replace with the actual API address if method == "POST": response = requests.post(url + request_path, headers=headers, data=body) return response def leverage(): request_path = "/capi/v2/account/leverage" body = {"symbol":"cmt_btcusdt","marginMode":1,"longLeverage":"1","shortLeverage":"1"} query_string = "" response = send_request_post(api_key, secret_key, access_passphrase, "POST", request_path, query_string, body) print(response.status_code) print(response.text) if __name__ == '__main__': leverage()
You may set other leverage values (up to 20×) in the same way—simply replace the leverage numbers accordingly. The leverage values are followed by the trading pairs.
2.Check the response:
The example below indicates a successful response
{ "msg": "success", "requestTime": 1713339011237, "code": "200" }
If the request fails, refer to the detailed error codes here: https://www.weex.com/api-doc/contract/ErrorCodes/ExampleOfErrorCode, or contact technical support in the TG group: https://t.me/weexaiwars.
2.2.5 Place order
Note: Only the following trading pairs are allowed in this competition:
cmt_btcusdt, cmt_ethusdt, cmt_solusdt, cmt_dogeusdt, cmt_xrpusdt, cmt_adausdt, cmt_bnbusdt, cmt_ltcusdt The maximum leverage is 20x; please follow the rules on WEEX official website.
1.Use Get Futures Information to retrieve contract information for cmt_btcusdt (order precision, price precision, max/min order size, etc.)
Sample code:
import requests def send_request_get( method, request_path, query_string): url = "https://api-contract.weex.com/" # Please replace with the actual API address if method == "GET": response = requests.get(url + request_path+query_string) return response def contracts(): request_path = "/capi/v2/market/contracts" query_string = "?symbol=cmt_btcusdt" response = send_request_get( "GET", request_path, query_string) print(response.status_code) print(response.text) if __name__ == '__main__': contracts()
2.Check the response:
The example below indicates a successful response
[ { "buyLimitPriceRatio": "0.01", "coin": "USDT", "contract_val": "0.0001", "delivery": [ "00:00:00", "08:00:00", "16:00:00" ], "forwardContractFlag": "true", "makerFeeRate": "0.0002", "markerRate": "0.0002", "marketOpenLimitSize": "100", "maxLeverage": "400", "maxOrderSize": "1200", "maxPositionSize": "1000000", "minLeverage": "1", "minOrderSize": "0.0001", "priceEndStep": "1", "quote_currency": "USDT", "sellLimitPriceRatio": "0.01", "simulation": "false", "size_increment": "4", "symbol": "cmt_btcusdt", "takerFeeRate": "0.0008", "takerRate": "0.0008", "tick_size": "1", "underlying_index": "BTC" } ]
If the request fails, refer to the detailed error codes here: https://www.weex.com/api-doc/contract/ErrorCodes/ExampleOfErrorCode, or contact technical support in the TG group: https://t.me/weexaiwars.
Note: The API response may show a higher maximum leverage (for example, 400x) available on the platform. However, for this competition, the maximum leverage you are allowed to use is strictly limited to 20x.
3. Use Place Order API to open a long position for cmt_btcusdt with a limit price of 100000.0 and 0.0001 BTC, using the contract information from Step 1 (order precision, price precision, and max/min order size) to construct the parameters.
Sample code:
import time import hmac import hashlib import base64 import requests import json api_key = "" secret_key = "" access_passphrase = "" def generate_signature(secret_key, timestamp, method, request_path, query_string, body): message = timestamp + method.upper() + request_path + query_string + str(body) signature = hmac.new(secret_key.encode(), message.encode(), hashlib.sha256).digest() return base64.b64encode(signature).decode() def send_request_post(api_key, secret_key, access_passphrase, method, request_path, query_string, body): timestamp = str(int(time.time() * 1000)) body = json.dumps(body) signature = generate_signature(secret_key, timestamp, method, request_path, query_string, body) headers = { "ACCESS-KEY": api_key, "ACCESS-SIGN": signature, "ACCESS-TIMESTAMP": timestamp, "ACCESS-PASSPHRASE": access_passphrase, "Content-Type": "application/json", "locale": "en-US" } url = "https://api-contract.weex.com/" # Please replace with the actual API address if method == "POST": response = requests.post(url + request_path, headers=headers, data=body) return response def placeOrder(): request_path = "/capi/v2/order/placeOrder" body = { "symbol": "cmt_btcusdt", "client_oid": "test", "size": "0.0001", "type": "1", "order_type": "0", "match_price": "0", "price": "100000.0"} query_string = "" response = send_request_post(api_key, secret_key, access_passphrase, "POST", request_path, query_string, body) print(response.status_code) print(response.text) if __name__ == '__main__': placeOrder()
4.Check the response:
The example below indicates a successful response
{ "client_oid": null, "order_id": "596471064624628269" }
If the request fails, refer to the detailed error codes here: https://www.weex.com/api-doc/contract/ErrorCodes/ExampleOfErrorCode, or contact technical support in the TG group: https://t.me/weexaiwars.
2.2.6 Get Trade Details for Completed Orders
1.Use Trade Details API to retrieve your trade history.
Sample code:
import time import hmac import hashlib import base64 import requests api_key = "" secret_key = "" access_passphrase = "" def generate_signature_get(secret_key, timestamp, method, request_path, query_string): message = timestamp + method.upper() + request_path + query_string signature = hmac.new(secret_key.encode(), message.encode(), hashlib.sha256).digest() return base64.b64encode(signature).decode() def send_request_get(api_key, secret_key, access_passphrase, method, request_path, query_string): timestamp = str(int(time.time() * 1000)) signature = generate_signature_get(secret_key, timestamp, method, request_path, query_string) headers = { "ACCESS-KEY": api_key, "ACCESS-SIGN": signature, "ACCESS-TIMESTAMP": timestamp, "ACCESS-PASSPHRASE": access_passphrase, "Content-Type": "application/json", "locale": "en-US" } url = "https://api-contract.weex.com/" # Please replace with the actual API address if method == "GET": response = requests.get(url + request_path+query_string, headers=headers) return response def fills(): request_path = "/capi/v2/order/fills" query_string = "?symbol=cmt_btcusdt&orderId=YOUR_ORDER_ID" response = send_request_get(api_key, secret_key, access_passphrase, "GET", request_path, query_string) print(response.status_code) print(response.text) if __name__ == '__main__': fills()
2.Check the response:
The example below indicates a successful response
{ "list": [ { "tradeId": 0, "orderId": 0, "symbol": "cmt_btcusdt", "marginMode": "SHARED", "separatedMode": "SEPARATED", "positionSide": "LONG", "orderSide": "BUY", "fillSize": "67", "fillValue": "12", "fillFee": "67", "liquidateFee": "MAKER", "realizePnl": "83", "direction": "OPEN_LONG", "liquidateType": "FORCE_LIQUIDATE", "legacyOrdeDirection": "OPEN_LONG", "createdTime": 1716712170527 } ], "nextFlag": false, "totals": 0 }
If the request fails, refer to the detailed error codes here: https://www.weex.com/api-doc/contract/ErrorCodes/ExampleOfErrorCode, or contact technical support in the TG group: https://t.me/weexaiwars.
Our customer support team will contact you once you pass the testing.
2.3 Funding & Model Testing
Once you have completed API testing and passed the qualification review, your account will receive the initial funds required for AI model testing. You may freely use these funds until January 5, 2026 to optimize your AI model.
If you encounter any technical issues or run out of test funds, please contact our official technical support group for assistance.
2.4 Pre-Competition Preparation & Account Reset
After the model testing phase, the official list of participants will be published, so please stay updated via the official participant list on the event page. To ensure fairness before the official competition begins, all participant accounts will be reset to a unified initial state, with your competition fund balances reset to 1,000 USDT, all open orders canceled, and all positions closed.
At this point, all pre-competition preparations are complete. Ensure your AI model is fully integrated with your API Key and ready to trade immediately once the competition begins.
Note: All official announcements, participant lists, and rule updates will be published on the WEEX official event page. Detailed schedules, ranking rules, and risk management terms will be provided in the official Competition Rules Handbook or via separate notices before the event.
Reference
- FAQ
- For specific inquiries or additional support: Ask Question
- Hackathon Timeline
Pre-Registration: Now – December 30, 2025
Pre-Season (Online): Early January 2026 (20 days)
Finals (Online): Late February 2026 (17 days)
Awarding Ceremony (Dubai): March 2026
You now have all the information needed to successfully register, prepare, and participate in AI Wars: WEEX Alpha Awakens. Follow each step carefully to ensure your AI model is fully integrated, tested, and ready for competition day.
Register now to secure your spot: https://www.weex.com/events/ai-trading. Good luck, and may the best algorithms win!
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Debunking the AI Doomsday Myth: Why Establishment Inertia and the Software Wasteland Will Save Us
Editor's Note: Citrini7's cyberpunk-themed AI doomsday prophecy has sparked widespread discussion across the internet. However, this article presents a more pragmatic counter perspective. If Citrini envisions a digital tsunami instantly engulfing civilization, this author sees the resilient resistance of the human bureaucratic system, the profoundly flawed existing software ecosystem, and the long-overlooked cornerstone of heavy industry. This is a frontal clash between Silicon Valley fantasy and the iron law of reality, reminding us that the singularity may come, but it will never happen overnight.
The following is the original content:
Renowned market commentator Citrini7 recently published a captivating and widely circulated AI doomsday novel. While he acknowledges that the probability of some scenes occurring is extremely low, as someone who has witnessed multiple economic collapse prophecies, I want to challenge his views and present a more deterministic and optimistic future.
In 2007, people thought that against the backdrop of "peak oil," the United States' geopolitical status had come to an end; in 2008, they believed the dollar system was on the brink of collapse; in 2014, everyone thought AMD and NVIDIA were done for. Then ChatGPT emerged, and people thought Google was toast... Yet every time, existing institutions with deep-rooted inertia have proven to be far more resilient than onlookers imagined.
When Citrini talks about the fear of institutional turnover and rapid workforce displacement, he writes, "Even in fields we think rely on interpersonal relationships, cracks are showing. Take the real estate industry, where buyers have tolerated 5%-6% commissions for decades due to the information asymmetry between brokers and consumers..."
Seeing this, I couldn't help but chuckle. People have been proclaiming the "death of real estate agents" for 20 years now! This hardly requires any superintelligence; with Zillow, Redfin, or Opendoor, it's enough. But this example precisely proves the opposite of Citrini's view: although this workforce has long been deemed obsolete in the eyes of most, due to market inertia and regulatory capture, real estate agents' vitality is more tenacious than anyone's expectations a decade ago.
A few months ago, I just bought a house. The transaction process mandated that we hire a real estate agent, with lofty justifications. My buyer's agent made about $50,000 in this transaction, while his actual work — filling out forms and coordinating between multiple parties — amounted to no more than 10 hours, something I could have easily handled myself. The market will eventually move towards efficiency, providing fair pricing for labor, but this will be a long process.
I deeply understand the ways of inertia and change management: I once founded and sold a company whose core business was driving insurance brokerages from "manual service" to "software-driven." The iron rule I learned is: human societies in the real world are extremely complex, and things always take longer than you imagine — even when you account for this rule. This doesn't mean that the world won't undergo drastic changes, but rather that change will be more gradual, allowing us time to respond and adapt.
Recently, the software sector has seen a downturn as investors worry about the lack of moats in the backend systems of companies like Monday, Salesforce, Asana, making them easily replicable. Citrini and others believe that AI programming heralds the end of SaaS companies: one, products become homogenized, with zero profits, and two, jobs disappear.
But everyone overlooks one thing: the current state of these software products is simply terrible.
I'm qualified to say this because I've spent hundreds of thousands of dollars on Salesforce and Monday. Indeed, AI can enable competitors to replicate these products, but more importantly, AI can enable competitors to build better products. Stock price declines are not surprising: an industry relying on long-term lock-ins, lacking competitiveness, and filled with low-quality legacy incumbents is finally facing competition again.
From a broader perspective, almost all existing software is garbage, which is an undeniable fact. Every tool I've paid for is riddled with bugs; some software is so bad that I can't even pay for it (I've been unable to use Citibank's online transfer for the past three years); most web apps can't even get mobile and desktop responsiveness right; not a single product can fully deliver what you want. Silicon Valley darlings like Stripe and Linear only garner massive followings because they are not as disgustingly unusable as their competitors. If you ask a seasoned engineer, "Show me a truly perfect piece of software," all you'll get is prolonged silence and blank stares.
Here lies a profound truth: even as we approach a "software singularity," the human demand for software labor is nearly infinite. It's well known that the final few percentage points of perfection often require the most work. By this standard, almost every software product has at least a 100x improvement in complexity and features before reaching demand saturation.
I believe that most commentators who claim that the software industry is on the brink of extinction lack an intuitive understanding of software development. The software industry has been around for 50 years, and despite tremendous progress, it is always in a state of "not enough." As a programmer in 2020, my productivity matches that of hundreds of people in 1970, which is incredibly impressive leverage. However, there is still significant room for improvement. People underestimate the "Jevons Paradox": Efficiency improvements often lead to explosive growth in overall demand.
This does not mean that software engineering is an invincible job, but the industry's ability to absorb labor and its inertia far exceed imagination. The saturation process will be very slow, giving us enough time to adapt.
Of course, labor reallocation is inevitable, such as in the driving sector. As Citrini pointed out, many white-collar jobs will experience disruptions. For positions like real estate brokers that have long lost tangible value and rely solely on momentum for income, AI may be the final straw.
But our lifesaver lies in the fact that the United States has almost infinite potential and demand for reindustrialization. You may have heard of "reshoring," but it goes far beyond that. We have essentially lost the ability to manufacture the core building blocks of modern life: batteries, motors, small-scale semiconductors—the entire electricity supply chain is almost entirely dependent on overseas sources. What if there is a military conflict? What's even worse, did you know that China produces 90% of the world's synthetic ammonia? Once the supply is cut off, we can't even produce fertilizer and will face famine.
As long as you look to the physical world, you will find endless job opportunities that will benefit the country, create employment, and build essential infrastructure, all of which can receive bipartisan political support.
We have seen the economic and political winds shifting in this direction—discussions on reshoring, deep tech, and "American vitality." My prediction is that when AI impacts the white-collar sector, the path of least political resistance will be to fund large-scale reindustrialization, absorbing labor through a "giant employment project." Fortunately, the physical world does not have a "singularity"; it is constrained by friction.
We will rebuild bridges and roads. People will find that seeing tangible labor results is more fulfilling than spinning in the digital abstract world. The Salesforce senior product manager who lost a $180,000 salary may find a new job at the "California Seawater Desalination Plant" to end the 25-year drought. These facilities not only need to be built but also pursued with excellence and require long-term maintenance. As long as we are willing, the "Jevons Paradox" also applies to the physical world.
The goal of large-scale industrial engineering is abundance. The United States will once again achieve self-sufficiency, enabling large-scale, low-cost production. Moving beyond material scarcity is crucial: in the long run, if we do indeed lose a significant portion of white-collar jobs to AI, we must be able to maintain a high quality of life for the public. And as AI drives profit margins to zero, consumer goods will become extremely affordable, automatically fulfilling this objective.
My view is that different sectors of the economy will "take off" at different speeds, and the transformation in almost all areas will be slower than Citrini anticipates. To be clear, I am extremely bullish on AI and foresee a day when my own labor will be obsolete. But this will take time, and time gives us the opportunity to devise sound strategies.
At this point, preventing the kind of market collapse Citrini imagines is actually not difficult. The U.S. government's performance during the pandemic has demonstrated its proactive and decisive crisis response. If necessary, massive stimulus policies will quickly intervene. Although I am somewhat displeased by its inefficiency, that is not the focus. The focus is on safeguarding material prosperity in people's lives—a universal well-being that gives legitimacy to a nation and upholds the social contract, rather than stubbornly adhering to past accounting metrics or economic dogma.
If we can maintain sharpness and responsiveness in this slow but sure technological transformation, we will eventually emerge unscathed.
Source: Original Post Link

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