A whale lost 20.4 million USD after investing 23 million USD in an AI agent token on the Base blockchain, but could only sell it for 2.58 million USD, resulting in a loss of up to 88.77%. This is considered one of the largest single trade losses in the crypto industry, as each token's price plummeted by as much as 99%.
This heavy loss reflects growing concerns about the bubble in AI token investments, where the excitement and unclear adoption have caused extreme volatility in all investors' portfolios.
How did the whale lose over 20 million USD with AI agent tokens?
The blockchain data analysis platform Lookonchain has tracked this whale's portfolio across all six AI agent tokens, with the largest loss being in FAI, worth 9.87 million USD, which saw a price drop of 92.31%. Meanwhile, AIXBT incurred a loss of 7.81 million USD, or a decrease of 83.74% from its purchase price.
And the remaining positions also suffered severe losses, with BOTTO dropping 936,000 USD or 83.62% and POLY losing 839,000 USD, with prices plunging 98.63%.
NFTXBT incurred the highest loss rate, with prices dropping 99.13%, resulting in a loss of 594,000 USD. MAICRO ended with a loss of 381,000 USD, or 89.55% of the invested capital.
Currently, this investor's wallet address has only 3,584 USD in total assets, mostly in ETH, and holds small amounts of BYTE, MONK, and SANTA. This withdrawal reflects nearly total losses in AI agent tokens.
Speculation on AI Agent tokens is being closely monitored.
Coinbase's Base blockchain has become a popular platform for launching AI crypto projects. However, this sector has been criticized for being filled with exaggerated hype, and usable products remain limited.
Many AI agent tokens still lack real-world applications, putting traders at severe risk of quick gains and losses.
Several observers point out that AI agent tokens often rise in price due to promises rather than actual usage, with automated agents on the blockchain attracting attention from all investors. However, there are still very few projects delivering usable products.
When market sentiment shifts, token holders face severe risks due to low liquidity and shallow utilization.
This could be one of the worst investments ever. A whale or institution spent as much as 23 million USD buying AI agent tokens on #Base and sold everything today for just 2.58 million USD, resulting in a loss of 20.43 million USD (-88.77%), as stated by Lookonchain.
This whale exited the market at the same time as the excitement around AI tokens declined in early 2025, while this sector fell by as much as 77%.
After the AI theme investment wave at the end of 2024, investors are reassessing, as only a few projects have achieved their goals. This trend has acted as a catalyst for further price declines, especially for tokens with concentrated ownership and low liquidity.
Risk management: Lessons for investors.
This whale poured a large amount of money into AI agent tokens on Base without risk diversification and failed to manage risks at all.
The allocation of 23 million USD into 6 related assets in the same theme only increased systemic risk. When the trends reversed, everything plunged down, revealing the risks of concentrated holdings.
Typically, professional traders limit risk to avoid high losses when the market turns against them. However, failing to set stop-loss points or manage position sizes with discipline exacerbates this whale's losses.
When the time comes to close that position, recovering the original capital is nearly impossible. It requires a very high return. This case shows how quickly things can decline without careful risk analysis and planning.
With NFTXBT and POLY losing over 98%, a major recovery seems unlikely.
It is still unclear whether this will reflect broader issues for AI agent tokens. Projects with strong technical teams and real developments may survive this bad situation.
Moreover, tokens that exploit the AI trend without a solid foundation are likely to face further difficulties as market players start wanting to see real results, not just promises.
