AI Trading Hackathon 2026: Win $1.88M Prize Pool with CoinGecko API (Live Market Data)

With the competition entering its decisive stage, AI Wars: WEEX Alpha Awakens — the flagship global AI trading hackathon launched by WEEX Labs is gearing up for its highly anticipated Finals. Following a fiercely contested Preliminary Round, the top-performing teams from each group will advance to the Finals, where they will face off in live-market conditions for a prize pool exceeding $1 million. The ultimate champion will claim the Bentley Bentayga S, marking one of the most prestigious grand prizes ever awarded in an AI trading competition.
As part of this expansion, the hackathon has introduced a dedicated CoinGecko API Track, supported by its own exclusive prize pool. By integrating CoinGecko’s trusted, real-time crypto market data API, participating teams gain a measurable edge in building more robust and responsive AI trading strategies, while also qualifying for additional track-specific rewards, including a full year of professional CoinGecko API access valued at over $1,500. This dual-track structure enables builders to compete simultaneously for both the main $1.88 million USDT global prize pool and CoinGecko’s dedicated incentives — a rare opportunity to turn technical excellence into multiple forms of recognition.
In AI trading, data is the weapon, execution is the test, and only real performance defines value.
Why Top AI Traders Use CoinGecko API: Real-Time Data for 24M+ Tokens
AI trading strategies live or die by data quality. The CoinGecko API is the most comprehensive and reliable crypto market data API available, providing access to price and market data for over 24 million+ tokens across more than 250+ blockchains and 1,700+ exchanges.
Hackathon participants can eliminate the engineering overhead of fragmented data sources. Focus on strategy development instead of building price and market data infrastructure from scratch.
3 Ways to Feed Live Crypto Data to Your AI: WebSocket, MCP & REST API
CoinGecko offers three data delivery methods optimized for different AI trading workflows.
- WebSocket API: Persistent connections push price updates and on-chain trades the instant they occur. Sub-second update frequencies enable strategies that react to volatility before standard polling methods register the change.
- MCP Server: The Model Context Protocol (MCP) allows LLMs like Claude or OpenAI to query CoinGecko data directly through structured tool calls. Ideal for rapid strategy prototyping with autonomous AI agents.
- REST API: Comprehensive real-time and historical data spanning 10+ years for backtesting and deep market analysis. The various market discovery endpoints such as onchain pools Megafilter, trending search, top gainers and losers also enables traders to easily filter and uncover assets that may be worth monitoring.
$1,500+ in Prizes: How to Win a Year of Pro API Access (Even as a Beginner)
Every participant approved for the CoinGecko API Dedicated Track receives a complimentary 2-month Analyst Plan API key valued at $258. This grants access to all exclusive endpoints that CoinGecko API has to offer, including the WebSocket API for real-time streaming during the period of the competition.
Track Prizes
The CoinGecko API track awards the top 10 builders in addition to the main WEEX Hackathon prize pool.
Each of the 10 winners receives a 1-year CoinGecko Analyst API Plan valued at $1,548, plus global media exposure across CoinGecko's official channels including X, their website, and newsletters.
These prizes stack with main WEEX AI Wars rewards. A strong submission can win both tracks simultaneously.
Step-by-Step Guide: From Registration to Submission in 72 Hours
Step 1: Complete the CoinGecko API Dedicated Track Registration Request Form with your details and intended API usage.
Step 2: Build your strategy using CoinGecko API’s data in a meaningful manner such as for market discovery, backtesting, or risk monitoring.
Step 3: Submit your project via the CoinGecko API Track Submission Form with your DoraHacks BUIDL link, GitHub repository, and an explainer walkthrough video.
- Track Duration: January 13, 2026 to March 3, 2026
- Registration Deadline: February 2, 2026
- Winner Announcement: TBA
The CoinGecko API track represents a clear opportunity for WEEX AI Wars participants to enhance their AI trading strategies with trusted and comprehensive crypto market data to compete effectively and qualify for additional prizes.
Click here for more details about the dedicated CoinGecko API hackathon track and visit the CoinGecko API documentation to learn more about the available data and endpoints CoinGecko has to offer.
Beyond sponsorship, CoinGecko’s involvement in WEEX Global AI trading hackathon reflects a shared commitment to raising the technical standard of AI-driven trading. By providing transparent, reliable, and institution-grade market data, CoinGecko enables builders in the WEEX AI Trading Hackathon to focus on execution and performance rather than narrative-driven signals, reinforcing a core principle of the competition: in AI trading, only real data and real markets can prove real value.
About WEEX
Founded in 2018, WEEX has developed into a global crypto exchange with over 6.2 million users across more than 150 countries. The platform emphasizes security, liquidity, and usability, providing over 1,200 spot trading pairs and offering up to 400x leverage in crypto futures trading. In addition to traditional spot and derivatives markets, WEEX is expanding rapidly in the AI era — delivering real-time AI news, empowering users with AI trading tools, and exploring innovative trade-to-earn models that make intelligent trading more accessible to everyone. Its 1,000 BTC Protection Fund further strengthens asset safety and transparency, while features such as copy trading and advanced trading tools allow users to follow professional traders and experience a more efficient, intelligent trading journey.
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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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