Written by: JW, Techub News
We often say the cryptocurrency market is a “dark forest.” If everyone holds a machine gun called “AI,” will this forest become safer or will it be destroyed?
These days, AI is the hot topic worldwide. Seedance-generated videos are flooding Twitter, but in our circle, the topic of “cryptocurrency” seems to have been forgotten by the market. All groups are asking the same question: “What did your AI do for you today?” or looking for speculative projects related to AI concepts. But I don’t want to talk about this “shovel thinking”—finding projects that pretend to be decentralized computing power but are actually just hype. That’s the realm of speculators. I want to discuss something truly sexy, even a bit terrifying.
Nowadays, social media is full of bloggers claiming: “The market is too boring now; we’re trying to let Agents find prey on the chain by themselves.” That statement sends chills down the spine. We’re used to treating AI as an asset to speculate on, but few stop to think: if AI isn’t just a hype object but is sitting across the table playing poker with you, how would you play?
This is the thought experiment I want to explore today: when the trading agents in the crypto market shift from “humans” to “silicon-based beings,” and retail investors, institutions, and market makers all hold AI Gatling guns, what will this dark forest become?
You think “quantitative” is just a crippled calculator
Before predicting the future, we must clear the most stubborn misconception—many veteran traders still don’t distinguish between “quantitative” and “AI.” On social media, you still see comments like: “Aren’t those automated trading bots just AI?”
That’s a misconception. Currently, 99% of so-called “quantitative bots” are essentially “Excel sheets with automation.” Their logic is linear and rule-based: sell when RSI exceeds 80, stop loss when price drops below MA120. The problem with this rigid approach is that it can’t understand context.
For example: suppose Vitalik suddenly tweets tomorrow that the Ethereum Foundation plans to sell 100,000 ETH. Traditional quantitative bots will still be watching candlesticks because the price hasn’t dropped yet, indicators are still okay, and they might even trigger a “buy” signal due to a small rebound, only to suffer losses when the real waterfall begins. True AI strategies, within 0.5 seconds of the tweet, the NLP module has already read the message, performed sentiment analysis, and determined “extreme panic.” The risk control module immediately issues an order to close long positions and go short. At this moment, the candlestick chart might not have even moved.
Traditional quant finds patterns in the “rearview mirror,” while AI attempts to “predict the future” through massive data (Data-driven). Now, strategies at the AlphaGo level monitor thousands of on-chain addresses in real-time, analyze hundreds of thousands of KOLs’ sentiments, and might even discover patterns you can’t understand—like “whenever Elon Musk changes his avatar and gas fees are below 15 Gwei, DOGE has an 87% chance to rise within 10 minutes.” Such nonlinear, high-dimensional correlations can only be handled by neural networks. So, comparing grid trading to AI is like comparing an abacus to a nuclear bomb.
What happens if everyone is AI?
Suppose technology becomes equalized: retail traders use GPT-5 to assist trading, institutions deploy proprietary black-box models. The outlook could be bleak: we might face a “highly fragmented liquidity” and “flash crashes becoming the norm.”
First, the “dead water effect” caused by absolute efficiency. In finance, there’s the “Efficient Market Hypothesis.” Currently, crypto profits are high because information gaps are large and many are “dumb.” But in an AI-dominated era, any tiny arbitrage opportunity (like a DEX price 0.1% slower than a CEX) will be erased in microseconds by hundreds of thousands of AIs. This means technical analysis will become obsolete. No more drawing lines; AI has already seen the patterns a hundred million times. Most of the market will turn into a stagnant pool, with prices so precise and low-volatility that it’s sleep-inducing.
Second, “synchronization” could trigger super flash crashes. This is the scariest scenario in the thought experiment. Although AI is smart, they learn from the same data sources—Binance candlesticks, Etherscan data, Bloomberg news. Input is similar, logic is alike, so will their outputs converge? When a specific market signal appears, thousands of top-tier AIs worldwide might simultaneously decide to “sell.”
Without human hesitation or luck, trillions of sell orders could flood the order book instantly, liquidity evaporates. Bitcoin could drop 90% in one second, only to be pulled back in the next second when AI realizes it underestimated. Such “algorithmic resonance” causing flash crashes, in a 24/7, no-circuit-breaker crypto market, would be a nuclear-level disaster. Even scarier, these risks won’t be pre-emptively warned because they happen within internal model thresholds, not in public sentiment.
Finally, the “Turing test” in the dark forest. Currently, market makers manipulate retail traders with chart tricks; in the future, they’ll deceive each other’s AI. This could evolve into “adversarial attacks”: institutional super AIs deliberately create complex, seemingly “accumulation” fake moves on-chain to trick retail AI models into buying. The chain will be filled with false noise, and genuine signals will be drowned in algorithm-generated illusions. This isn’t a financial market anymore; it’s an electronic battleground of silicon-based beings.
This situation could even extend beyond trading, infiltrating our proud “community governance” and “DAO.”
Imagine a new Layer 2 project airdrops tokens. In the past, “wolf attacks” involved one person controlling hundreds of wallets. That’s easy to detect by checking connections.
In the future? It will be AI-driven “super wolves.”
Behind each wallet, there’s an independent AI agent. It has its own personality, Twitter account (not just retweets, but memes, even arguing with real users), on-chain interaction habits (some like NFTs, some prefer DeFi, some even intentionally lose money to simulate real retail behavior).
You can’t tell who’s real anymore.
When you join a project’s Discord or Telegram and see lively discussions about tech and signals, 99% of those accounts might be controlled by the same big trader’s AI matrix. The so-called “consensus” is just a bubble generated by computing power.
This “failure of social Turing tests” is more terrifying than a price crash. It destroys the trust foundation of crypto. When “community” becomes a bunch of code talking to itself, Web3 becomes an empty shell.
Once trust collapses, markets won’t be arenas of gambling anymore—they’ll devolve into pure computational power clashes. Prices will be just byproducts; the real competition will be over who controls the narrative and traffic flow.
Retail “technological equality” is a false proposition
Some might argue: “Institutions have AI, so do I! ChatGPT gives us a chance to challenge institutions.”
Unfortunately, that’s a toxic illusion. In financial warfare, the more advanced the technology, the higher the barriers to entry. It’s a full-scale arms race. You use a MacBook Pro; institutions use H100 clusters next door in data centers; your AI analysis takes 3 seconds, theirs takes 5 microseconds via dedicated lines. In algorithmic trading, 1 millisecond faster wins everything; 1 millisecond slower means you’re the bagholder.
When you think “I also use AI trading” and feel proud, in the eyes of institutions, you’re just upgrading from “manual money transfer” to “automatic money transfer.” If the future crypto market becomes a pure war of computing power and algorithms, retail traders will have no chance. This is brutally true but irreversible.
The only way out: escape the “blind spots” of AI
Writing this, it seems the road is blocked. But precisely because AI is so powerful and data-dependent, it also exposes its fatal weakness. AI understands math, probability, logic, but it doesn’t understand “madness,” “faith,” or “memes.”
AI is trained on historical data; it can only predict variations of “what has happened.” But the most fascinating part of crypto is that it always creates “something from nothing.” Imagine when PEPE first appeared, or when BRC-20 inscriptions started. AI’s perspective would see this as “garbage code, no fundamentals, infinitely risky,” and avoid it. Humans, however, might think: “This frog is addictive, the community is crazy, and even if I don’t understand it, it feels like it’s going to explode,” leading to a “go all in” decision.
In the “0 to 1” phase, during the chaotic moment when narratives are just forming and emotions are just rising, AI is blind. Because there’s no data—only emotion. Only humans can empathize with human madness.
Therefore, if the future is truly fully AI-driven, I believe the market will split into two extremes: one is the mainstream coin battlefield—where gods fight, institutions AI clash, prices are extremely efficient, and retail can hardly earn Alpha; the other is the “human reserve” of memes and early-stage projects—an AI forbidden zone, the last battlefield where humans use emotion to gamble, craft narratives, and harvest bubbles.
At the end of trading, it turns out to be about humanity. When candlesticks are “calculated to death,” our only remaining advantage is understanding what’s “fun” and what’s “community.” AI can’t understand why people would pay billions for a dog meme.
The future threshold may become extremely high. We can either evolve into semi-mechanical beings, learning code and algorithms to wield tools; or revert to the most savage hunters, relying on intuition and insight into human nature. The worst are those stuck in the middle, trying to find treasures in a new world with outdated tools.
This article is just a thought experiment and not investment advice. After all, maybe next month GPT-N PRO MAX will come out, and even memes can be traded, and then we might as well just go deliver food together.
