Author: Wu Blockchain
This episode of the Wu's Uncensored Podcast features guest Didier Zheng, a frontier technology investor, discussing the recent Bitcoin decline, changes in MicroStrategy's financial strategy, the AI-driven surge in US stocks, cryptocurrency exchanges offering access to US stocks, and the macro outlook.
Didier believes the core reason for Bitcoin's recent drop is not simply macro factors or ETF redemptions. Instead, the market is beginning to reprice the expectation that MicroStrategy might consistently sell small amounts of Bitcoin under its "Bitcoin per share neutrality" principle to pay preferred stock dividends. Simultaneously, AI is reshaping labor structures, with Tokens being viewed as new factors of production, driving the continued rise of the AI industry chain in US stocks. The crypto industry might gradually shift from native altcoin speculation toward stages of real-world asset tokenization, on-chain machine economies, and more mature industrialization.
The guest's views do not represent Wu Blockchain's stance and do not constitute any investment advice. Please strictly abide by local laws and regulations. Audio transcription and translation are done by GPT and may contain errors. Please listen to the full podcast:
小宇宙 (Xiao Yu Zhou):
https://www.xiaoyuzhoufm.com/episode/6a337dbb43a22a695585c365
MicroStrategy's Bitcoin Sell-off Experiment: Persistent Selling Pressure Expectations and Market Absorption Game
Maodi: Bitcoin has fallen sharply recently, with many explanations in the market. Some say it's MicroStrategy selling Bitcoin, some blame ETF redemptions, others attribute it to macro changes or leverage liquidations. Which factor do you think is most critical?
didier: I believe the core is still MicroStrategy, but what is truly suppressing the market is not the one-off sale itself, but the market starting to expect it will continue selling Bitcoin.
At the May earnings call, MicroStrategy stated it aims to maintain Bitcoin per share neutrality. As preferred stock and debt instruments like STRC, STRZ, STRD, STRF continue to increase, Bitcoin is no longer just an asset for common shareholders; it must first cover the claims of creditors and preferred shareholders. This raises the cost of maintaining Bitcoin per share neutrality.
The market previously thought it primarily paid preferred dividends by selling stock, putting little pressure on Bitcoin; but now, the barrier to raising funds by issuing new stock is higher, shifting pressure to Bitcoin. As long as MMV remains below the neutrality threshold, it is more likely to cover cash flow through small, continuous Bitcoin sales. Especially if the dividend payment frequency increases further, the market naturally expects not an occasional sale, but regular, periodic sales.
Therefore, the key to this decline is not "how much was sold," but "will it keep selling in the future?" Under this logic, ETF selling looks more like a result, not a cause. Because once the market judges MicroStrategy will keep selling later, related funds will exit early.
Maodi: You mentioned earlier that Michael Saylor seems to be conducting a financial experiment. What is the purpose of this experiment?
didier: Essentially, he is testing the market's ability to absorb continuous, small Bitcoin sales.
From a financial perspective, when the MMV premium is not high, small Bitcoin sales cause less damage to Bitcoin per share than selling stock, making it the first-order optimal solution. The issue is that after the large-scale issuance of STRC in March, interest and dividend payments on preferred stock and perpetual instruments have significantly increased, making cash flow management a necessary problem to address. So the key is no longer whether to manage cash flow, but how to manage it.
If the market can absorb the impact of this continuous, small-scale selling, this system can continue. But if this approach depresses the stock price, lowers MMV, exacerbates depegging, and further reinforces the "continuous selling" expectation, then it may have to softly pivot—perhaps relying more on selling stock again, or using a mix of stock and Bitcoin sales. This would sacrifice some Bitcoin per share but reduce the impact on Bitcoin and stock prices, representing a second-order optimal solution.
So right now, it's essentially a game between Michael Saylor and the market. He is watching at what price level sufficient buying support emerges, and the market is waiting for lower, more certain prices before stepping in.
Maodi: Could this evolve into a "death spiral" for both MicroStrategy and Bitcoin?
didier: I think, based on this issue alone, it's unlikely to reach that point. For that to truly happen, it usually requires new macro headwinds or larger systemic shocks.
As long as a soft pivot happens later—abandoning the rigid Bitcoin selling—bargain-hunting funds will likely return. The issue is not whether there is buying support, but at what price it appears. It could be at $62k, or lower; the market is waiting for that level.
So my judgment remains cautiously optimistic: this decline is more due to structural pressure from changes in MicroStrategy's own financial structure, rather than simply triggered by macro liquidity tightening. In the absence of significant new negative catalysts, the situation can likely still be turned around and is not easy to directly evolve into a real "death spiral."
Token Viewed as Labor Force of the New Era
Maodi: Although the crypto industry is relatively sluggish now, AI is hot, especially US stocks like optical modules, semiconductors, and data centers are rising sharply. What do you think is the core driver behind this?
didier: The core is actually very simple: tokens are essentially becoming the labor force of the new era.
In the past, the core production factor for businesses was people—whether physical or mental labor was completed by humans. But now, many execution tasks previously handled by people are being replaced by AI and tokens. What will truly be scarce in the future might be a small number of people who can complete closed loops: those who can set goals, design plans, drive execution, and ultimately solve problems. Such people, combined with a large number of tokens, form the new labor system.
This will directly change corporate organizational structures. In the past, companies had many layers because information had to be passed down through people. But in the AI era, many middle management, assistants, IT, and execution roles will be compressed. What truly becomes valuable is no longer mere execution ability, but influence, decision-making power, and imagination.
So essentially, in the past, companies paid money to employees; in the future, they will increasingly pay money to tokens, to models and computing power. Model companies then reinvest that money upstream to purchase chips, energy, optical modules, and data centers. The supply from these upstream sectors is limited, failing to keep up with demand, so they become the most consistently benefited links in the AI industry chain. This is the core reason for the continuous rise of related US stocks.
The service industry will be impacted first because knowledge-based services like accounting, law, consulting, and data analysis are precisely the easiest for AI to replace. In the future, internal business operations will become increasingly automated, and machine economies may form on-chain between businesses. By then, many transactions, collaborations, and even payments will be completed by machines.
Maodi: So you mean this round of gains isn't just short-term hype but has mid-to-long-term sustainability, and we might still be in the very early stages?
didier: Yes, I believe the era of the machine economy has just begun.
Many people also misunderstand the concept of a "one-person company." It's not one person working alone, but one person operating with dozens of intelligent agents; these agents combined might match the efficiency of hundreds of people in the past. So the premise of a one-person company is actually having a large number of intelligent agents providing labor.
That's why I keep emphasizing: tokens are the new labor force. In the past, businesses spent money hiring people; now, they are increasingly shifting budgets toward tokens. As long as tokens can continuously amplify revenue, corporate profit margins will significantly increase. This is the core logic behind the market's bullishness on the AI industry chain.
So the expectation reflected in the US stock market now is essentially this: more and more companies will become AI-native, replacing labor with tokens, increasing automation levels, thereby significantly raising profit margins. This is also the most fundamental and reasonable driver of this rally.
Exchanges Shifting to US Stocks, Users Need Not Rewrite Trading Logic
Maodi: With US stocks continuously rising, many crypto exchanges have also opened access to US stocks. How do you view this? Is it because the crypto industry itself lacks excitement, forcing exchanges to create demand, or are there deeper reasons? Also, might this further lead to capital outflow from the crypto industry?
didier: I've actually said long ago that offshore CEXs ultimately only have two paths.
The first is to become prediction markets, but this path is very difficult. The leading landscape is basically formed, and most existing CEXs can hardly truly transform into the next-generation "everything exchange."
The second is to shift toward distribution channels for real-world assets, and the most important real assets today are US stocks, US Treasuries, with gold also being a significant direction.
A more fundamental reason is that after so many years, there are actually very few truly valuable crypto-native assets. Bitcoin is one, a few DeFi infrastructures and public chains count, but beyond that, most native assets lack sustained intrinsic value and cash flow support. Therefore, the trading infrastructure built around these assets will inevitably seek new, valuable targets.
So CEXs shifting to US stocks is essentially natural. I don't really think this squeezes crypto assets; it's more like the industry returning to reality: there aren't many truly valuable assets to begin with, and exchanges are just turning to things that can better support liquidity.
But in the long run, this might not be a bad thing. The core value of blockchain isn't just issuing native assets, but providing decentralized choices and more efficient, lower-cost settlement and trading methods. Tokenizing real-world assets is itself a meaningful direction.
Moreover, from a longer-term perspective, blockchain is actually more like technology designed for machines. In the next five to ten years, a more likely scenario is: humans interact with agents, and agents complete payments, transactions, and collaborations with each other on-chain. In that case, the on-chain infrastructure being built today could be directly used by machines.
So in the long run, I actually think this is beneficial for Bitcoin. Because whether it's more people or more machines, they will ultimately be exposed to on-chain assets.
Maodi: For ordinary users who have primarily traded altcoins, Bitcoin, or public chain assets in the crypto market, shifting to US stocks involves different logic. Whether it's earnings cycles, valuation systems, or regulatory rules, there are big differences. If you had to give one most important piece of advice to these users or traders who have long been in the crypto world, what would it be?
didier: Actually, I don't think they need to deliberately change much.
Because US stocks and on-chain assets are essentially similar. US stocks have both value stocks, growth stocks, and many assets with meme attributes. A core reason why this round of on-chain meme hype has weakened is that the most compelling meme assets have actually migrated to US stocks.
The stories these assets tell are essentially about "changing the world." In the past, this narrative belonged to blockchain; now, a stronger version appears in US stocks, like quantum computing, nuclear fusion, SMR. Often, these are also hard to explain solely by earnings, cash flow, or DCF; they inherently carry strong meme attributes.
So, those who used to chase altcoins and meme coins can, in US stocks, chase these long-term concepts; the logic is actually the same, and they might not necessarily feel out of place. Another group, those who originally looked at cash flow, fundamentals, and value support, can also find corresponding value and growth stocks in US stocks.
So my point is, the various styles within the crypto space actually have corresponding counterparts in US stocks. Most people don't need to forcibly change their trading patterns to find familiar asset types.
If I had to give one piece of advice, it's not to force a change in your own method just to switch markets. People who have survived until now usually have a tested way of surviving; continuing to stick with what works for them is actually more important.
The 1011 Event Severely Damaged Crypto Liquidity; Altcoin Rally Hard to Revive
Maodi: Listening to your analysis just now, a rather dramatic picture emerges in my mind. It feels like the altcoin speculation of the past period has essentially ended, because the original targets of that hype can now almost all be found in US stocks, with even stronger real-world significance. Is that a fair understanding?
didier: That's a fair understanding.
The core reason the altcoin rally has basically ended is that crypto liquidity has been destroyed too severely. The 1011 event dealt a heavy blow to the industry's vitality. Superficially, reports mention $19 billion in liquidations, but the actual number is likely far higher. Rumors of four to five hundred billion dollars seem closer to reality.
Also note, what was lost here is not paper market cap, but real cash. The total market cap of the crypto industry isn't that large to begin with, and a lot is locked up or inflated. The truly liquid supply is actually much smaller than it appears. In that context, evaporating hundreds of billions in cash in a single day deals a heavy blow to the entire industry's popularity and liquidity.
So I believe the 1011 event was the final straw that broke the altcoin rally's back.
As for why "meme assets" in US stocks can continue to be hyped, the reason is simple: because the US stock market is currently the most liquid market globally. When your own liquidity dries up, it naturally flows to markets with stronger liquidity.
From the US perspective, its support for Bitcoin and blockchain also has strategic considerations. The US version's logic is to turn blockchain, on-chain markets, and CEXs into channels for attracting global capital and hot money to US assets. So promoting the US financial system moving on-chain is essentially expanding the global financing and distribution capabilities of US assets.
Of course, this is just the US government's understanding and application. Whether the blockchain and crypto world will ultimately be completely shaped by such national will is another matter. A more realistic situation might be that the on-chain world and sovereign states will exist in a complex, long-term relationship of cooperation, utilization, and mutual博弈.
But at least so far, the US's approach is indeed gradually becoming reality.
More Cautious on H2 Macro, but Long-Term Still Bullish on AI & Web3
Maodi: What is your macro judgment for the next six months, through the end of this year? What policies might the newly appointed Fed Chair Walsh take, and how will that affect the overall market?
didier: I think market uncertainty is increasing going forward.
On one hand, the market has already risen a lot; on the other hand, several giant companies might still go public later, like SpaceX, OpenAI, and Anthropic. The real pressure isn't just from fundraising draining liquidity, but if these trillion-dollar companies are quickly included in indices, with limited liquidity, institutions might be forced to sell other heavyweight stocks for rebalancing, putting pressure on the market. So I'll be more cautious after entering June.
Another key variable is the midterm elections. If the Democrats ultimately win both chambers, that could be bearish for both Web3 and AI, as they emphasize labor rights, regulation, and oversight more than allowing frontier technologies to continue expanding rapidly.
But looking at fundamentals, I think the market might be underestimating AI's real push on the economy. AI has already penetrated many areas, but current statistical methods might not fully reflect it. So in the long run, its boost to production efficiency is still very strong.
The real problem isn't just growth, but distribution. If the distribution mechanism isn't adjusted well, an extremely polarized situation might emerge: a small number of people who can harness AI reap most of the benefits, while a large middle class is squeezed or even unemployed. In that case, although productivity increases, overall societal consumption capacity might actually decline. This is also why I lean more towards long-term deflation rather than long-term inflation.
So in the coming years, the distribution mechanism will be crucial. Things like an AI tax—I think they are highly likely to materialize within three to five years, because without new revenue sources, many future social arrangements will lack a funding base.
If we're just looking at the second half of this year to next year, I don't want to give an absolute conclusion. Short-term adjustment pressure is indeed increasing, especially potentially more pronounced around SpaceX's IPO, but I see this more as a correction, not a complete peak. As long as the capital expenditures of major companies can continue, the overall uptrend isn't over yet.
From a longer-term perspective, I'm still bullish on AI, and bullish on the combination of AI and blockchain. The broad direction of increasing automation within companies and the possible formation of on-chain machine economies between businesses hasn't changed.
So I still believe blockchain and Web3 have great prospects, but the playbook will become more mature. The phase of mindlessly rushing in and making money might be over; the future looks more like an era of industrialization and institutionalization.
