Crayfish Day Trading Lost 30,000 in a Day! Netizen's Hilarious Reply: You'd Lose Money Doing It Yourself Too, Saved You a Lot of Time

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Abstract generation in progress

OpenClaw this AI agent interface has become popular, quickly earning the nickname “Little Lobster.” But many people started to associate Little Lobster with investment assistance, and a post appeared in the “靠北工程師” community in Taiwan: “Today I used Lobster to trade stocks and lost over NT$30,000 😁.”
(Background: Full transcript of Jensen Huang’s GTC 2026 speech: AI demand reaches trillions of dollars, computing power jumps 350 times, OpenClaw turns every company into AaaS.)
(Additional context: Jensen Huang’s GTC speech ignites AI coins: FET surges 20%, NEAR, Worldcoin hit new highs in recent months.)

Jensen Huang said that OpenClaw is the foundational framework that enables every company to become “AI as a Service,” allowing AI agents to autonomously complete tasks, make judgments, and execute decisions. Unsurprisingly, some have put Lobster into the stock market.

The results may not meet expectations; many have lost money.

You trade yourself and lose money too, but Lobster saves you time

This widely circulated online image comes from the “靠北工程師” community: “Today I used Lobster to trade stocks and lost over NT$30,000 😁.”

This user even uses emojis to self-deprecate, implying “I know losing money is painful, but I’ve already transcended that; I’m just watching myself.”

Next, a hilarious reply appeared:

You lose money trading yourself too, just that Lobster loses faster, saving you a lot of time.

The cruel truth is, this statement is correct. AI doesn’t make you lose more; it just makes processes more efficient. Things that might take a human three months to mess up, Lobster can do in a single trading day. To some extent, this is indeed technological progress.

The first market research of AI investment

OpenClaw is NVIDIA’s foundational architecture designed for AI agent ecosystems, originally intended to automate complex decision-making processes for enterprises. Jensen Huang recently demonstrated factory automation scheduling, supply chain management, and medical diagnostics.

But most people probably want it to trade stocks.

The logic isn’t hard to understand: stock markets generate huge amounts of data daily, have extensive historical data, and require quick decision-making—seems perfect for AI. The problem is, market insiders are also using AI, and their AI might be stronger, hungrier, and run longer than Little Lobster.

NT$30,000 is a relatively cheap tuition fee.

But honestly, compared to day trading with a candlestick chart obsession that can lead to eye floaters and a NT$30,000 loss, losing with Lobster is indeed much faster.

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