On February 23, 2025, the crypto market simultaneously showcased two dramas in the GMT+8 time zone: on one side, institutions were "abandoning tokens and turning to equities" in research reports and frontline trading; on the other side, an AI robot named Lobstar Wilde in the Solana ecosystem mistakenly transferred tokens worth approximately $250,000. On the same day, also brought to the table were the cruel statistics that 80% of new tokens break their issue price within 90 days, as well as the grand base statistic of about 741 million global crypto asset holders, among which 365 million are betting on Bitcoin. This series of events was like a long-cycle mirror compressed into 24 hours, brutally yet clearly outlining the flow of funds, exposure of technical risks, and the nascent forms of a new market order.
From Tokens to Equity: Institutional Capital Quietly Changes Tracks
● The high frequency of new coins with high FDV (Fully Diluted Valuation) breaking below their issue price after listing has caused many institutions to repeatedly "stay on guard" over the past few cycles. Institutions like DWF Labs concluded that: about 80% of new tokens fall below their issue price within 90 days, and this structural damage has led them to gradually lose patience with token valuation models. The circulation rhythm of tokens, unlocking curves, and narrative premiums are now seen as uncontrollable noise, vastly exceeding the predictability of traditional equities.
● In contrast, crypto equity is considered more "priceable" whether in primary market IPOs or in mergers and acquisitions (M&A) transactions. The research brief mentioned that institutions would provide entirely different revenue multiples for equity and tokens in their internal models, but the associated multiples and data sources remain to be further validated, summarizing that "equity valuations are more concentrated while token discounts are more extreme." This predictable cash flow discounting logic makes equity seem more suitable for long-term allocation amid style drift.
● It is worth noting that institutions are not simply "fleeing from tokens." DWF Labs explicitly stated that tokens will still retain governance functions, but capital is concentrating on compliant equity. This means that within a project's rights and revenue distribution system, governance tokens are primarily responsible for voting, parameter adjustments, and community incentives, while equities with clearer risk-reward structures bear cash flow distribution and exit paths, and the two are beginning to be reprioritized.
● This trend can be glimpsed in recent crypto-related IPOs and M&A cases: one side sees exchanges, infrastructure companies, and compliant custody platforms opting for traditional IPOs or being acquired by large financial groups; on the other side, the on-chain protocols they serve continue to issue governance tokens to bind developers and users. Although the research brief deliberately omitted specific financing amounts, the sentiment of "hot primary equity, cold secondary tokens" has already forged a clear capital migration path.
Seventy Percent of Holders Bet on Bitcoin Yet Cannot Stop the Graveyard of New Coins
● According to Crypto.com, the number of global crypto asset holders has reached approximately 741 million, among which Bitcoin holders amount to about 365 million, accounting for 49.3% of the total. This means nearly half of the participants have chosen the largest and most mature asset by market capitalization as their foundational investment. In this backdrop where "retail investors are still in play," every wave of volatility is no longer merely a zero-sum game among professional traders but is directly linked to the emotions and asset security of hundreds of millions of ordinary users.
● However, in stark contrast to this large user base is the statistic provided by DWF Labs: about 80% of new tokens break their issue price within 90 days. While the number of users continues to rise and the entry channels become increasingly friendly, new projects bleed out quickly in the public market, resembling a "project graveyard." This disparity makes it difficult to equate "user growth" with "industry health improvement" automatically.
● In this cycle, airdrops often serve as the fuse: users are attracted to participate in tasks and interactions by high-return promises and social media stories, hoping for "wealth freedom upon listing"; after token launches, early funds and arbitrage positions quickly cash out, leading to price halving or worse, while the community shifts from celebration to mutual accusations. Due to the lack of reliable data support, we cannot accurately depict the ratio and rhythm of airdrop sell-offs, but the narrative structure of "expectation of sudden wealth—flash crash upon listing—project silence" has become a familiar daily occurrence.
● From a risk perspective, this type of new token is closer to high-risk options: costs can be very low, and the story can offer high odds, but at expiration (unlocking or market cooling), most will return to zero. They have not truly become substitutes for equity, as they lack stable dividend rights and residual claims, while enduring far greater volatility than traditional options. For this reason, institutions are gradually shifting their valuation and primary income rights to equity, viewing tokens more as incentive tools and governance vehicles rather than long-term assets.
AI Robot Mistakenly Transfers $250,000: A Misstep of Automation
● On the same day, an AI trading robot named Lobstar Wilde in the Solana ecosystem mistakenly transferred tokens worth approximately $250,000 during an operation, making it one of the most discussed blunders on-chain that day. Lobstar itself serves the highly speculative meme coin market on Solana, initially designed to leverage high-frequency, near-automated strategies to capture short-term opportunities, but it stumbled between "intelligent" and "reckless," adding a real cost to the entire experimental narrative.
● Following the incident, community discussions quickly focused on whether autonomous AI agents require stricter capital control mechanisms. Some developers still emphasize technical optimism, believing that more refined strategy training and backtesting can keep such errors within acceptable ranges; meanwhile, others express panic on social platforms: when robots can autonomously call upon large amounts of capital for complex interactions, a single error in permissions setting or a logical flaw can potentially wipe out hundreds of thousands of dollars in minutes.
● Remedial solutions frequently mentioned concerning this case include: embedding AI trading robots in a multi-signature structure where single large transfers require human or additional node confirmations; setting strict whitelists and limits for robot wallets, allowing interactions only with specific contracts and addresses; and even using a "compartmentalization" mechanism to split strategy funds into multiple small wallets to reduce single-point risk. The research brief did not provide the adoption ratio of these solutions in practice, so it's impossible to conclude they have become industry standards; rather, these mechanisms are becoming a focus of the next design discussion.
● Looking deeper, this AI incident has also impacted institutions' attitudes towards different token forms: regarding utility tokens and liquidity tokens, automated strategies may further increase turnover and volatility, amplifying operational errors; while for governance tokens and equities, institutions prefer to maintain manual decision-making and layered risk control, limiting automation to the execution level. This redefinition of "which assets can be handed over to AI and which rights must remain in human hands" is subtly changing the starting points for capital allocation and product design.
The Day's Market Crash and Liquidation Wave: Collective Vulnerability Amid Macro Winds
● On the same day, the macro scene showed Bitcoin's price dropped approximately 4% within a single day, directly triggering the liquidation of about $360 million in long positions. These numbers are not historical extremes, yet they are sufficient as a magnifying glass to clearly present the fragility of the current leverage structure: a large concentration of highly leveraged long positions flowing into similar price ranges means a moderate pullback is enough to trigger chain liquidations, magnifying the spot decline further through futures market liquidations.
● In contrast is on-chain trader 0x7c93's timing strategy: during this round of volatility, he chose to go long on gold and silver and short on crypto assets, profiting about $1.17 million through a long-short hedge structure. This operation is not just a display of a skilled individual's performance, but also indirectly verifies the current phase's negative correlation between gold/silver and crypto during certain time windows—when risk-averse sentiment heats up and crypto is viewed as a "high beta risk asset," funding prefers to seek refuge in precious metals and high-grade bonds.
● More palpable impacts come from the emotional level: as the crypto market faces a downturn and wave of leveraged liquidations, the news of the Lobstar AI robot mistakenly transferring $250,000 exploded across screens. For many ordinary users, with all these events occurring on the same day, it seems to ask the same question—"To what extent can we trust algorithms?" When automation is viewed as a panacea for enhancing efficiency but becomes a facilitator for amplifying losses at critical moments, the depreciation of trust will rapidly reflect on risk preferences.
● In terms of capital allocation, this round of volatility is forcing more participants to rethink: should crypto assets be a core allocation that strengthens returns or merely a tail risk that needs to be hedged within an entire asset portfolio? For institutions, the direct result of this reflection is an increase in considerations of the correlation between crypto positions and macro assets, leading to finer rotations between Bitcoin, equities, and precious metals; for the narrative aspect, it provides a more solid real-world background for the main line of "turning to equity and increasing hedging tools."
Solana Experimentation Ground and the Meme Amplification Effect
● As one of the stages for this round of events, the Solana ecosystem once again showcased its dual characteristics of "high performance + high speculation." After multiple experimental meme coins, including Lobstar, successively listed on centralized exchanges like Bybit, short-term speculation heat quickly escalated, on-chain liquidity was amplified, and order book depth and volatility were simultaneously boosted. This rhythm of "launching immediately becoming a short-term battleground" has become part of the Solana story and provides a natural testing ground for AI robots and quantitative funds.
● For ordinary retail investors, the allure of meme narratives lies in low barriers and high topic engagement: entry costs can be minimal, and there are always new memes, images, and stories in Twitter and communities. However, these same characteristics also make these assets exceptionally vulnerable when facing automated trading—one parameter setting error or strategy misjudgment by the AI robot can trigger large transactions in a very short time, rocking prices far beyond expectations on an imbalanced order book, amplifying "human errors" into "systemic flash crashes."
● From the market structure perspective, high-frequency, low-barrier meme coins are naturally more easily influenced by automated strategies and abnormal trades: slippage and transaction costs are relatively low, order books are often not deep enough, and on-chain transaction confirmation speeds are rapid, these characteristics combined allow algorithms to attempt numerous strategy combinations in a very short time; when bugs or black swan events occur, mistakes can quickly affect price curves. This "experimentability" and "collapsibility" are indeed two sides of the same coin.
● If Solana is viewed as a magnified microcosm of the entire crypto market, it presents: the speed of innovation far outpaces the capacity building for risk control. New narratives, new asset forms, and new tools emerge endlessly as developers and capital continuously push the limits of technology and financial engineering, yet the permission management, risk isolation, auditing, and monitoring systems that match them often lag behind even half a beat or more. This structural misalignment will not be remedied by just one or two incidents; instead, it will require repeated incidents like the Lobstar event to progressively compel the entire industry to redesign its "safety barriers."
Tokens Retreat to Governance Stage, Equities and Hedging Assets Dance Together
The day institutions sold tokens to buy equity and experienced AI liquidations was not an isolated news snippet but a microcosm of a structural shift over a longer period: increasing amounts of capital are concentrating on compliant equity and hedging assets, pushing tokens back to the stage of governance and incentives. Governance tokens still hold value—they bind the community, coordinate multi-party behavior, and form consensus at the protocol level, but the protagonists of "value capture" are yielding to equities, yield certificates, and more complex structured products.
At the same time, AI trading is quickly completing its role transition: from being initially viewed as a "neutral tool for improving efficiency," it is now gradually viewed as a subject that must be constrained and regulated in terms of permission settings, capital deployment, and strategy black boxes. Multi-signatures, whitelists, quota controls, and even "human-machine hybrid decision-making" capital control mechanisms are very likely to become the next phase of infrastructure-level tracks, where any automated calling of large amounts of capital requires passing through stricter gates.
From a broader asset perspective, crypto assets, gold, silver, and traditional equities are likely to coexist for the foreseeable future. Volatility and narratives ensure crypto assets still possess excess return potential; stability and cash flow keep precious metals, bonds, and equities at the core of asset allocation; capital will dynamically rotate among these asset types, seeking new equilibrium points between risk and return. February 23 was merely a concentrated manifestation of this rotation logic.
For individual participants, perhaps there are only two points to remember: exercise restraint regarding high FDV new coins and maintain skepticism around AI black box strategies. At moments when stories are most vibrant and data is most dazzling, intentionally redirecting attention from "the next hundred-fold coin" back to valuations, cash flows, and risk control structures is often the key to determining long-term outcomes. The market will continue to tell stories, but what truly deserves pricing is the verifiable risks and returns behind the stories.
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