Author: Wu Blockchain
Wu Blockchain’s latest podcast featured frontier technology investor Didier Zheng, who discussed Bitcoin’s recent slide, changes in Strategy’s financing playbook, the AI-led rally in U.S. equities, crypto exchanges adding access to U.S. stocks, and the broader macro outlook.
Zheng said the main driver behind Bitcoin’s recent decline was not simply macro pressure or ETF outflows. In his view, the market has started repricing the possibility that Strategy, formerly MicroStrategy, may keep selling small amounts of BTC over time in order to pay dividends on preferred shares while maintaining what he described as a neutral BTC-per-share framework. He also said AI is changing labor structures, with tokens increasingly treated as a new productive input, a shift he believes is supporting the continued rise of the U.S. AI supply chain. For crypto, he said the sector may gradually move away from native altcoin speculation and toward tokenized real-world assets, machine-to-machine activity on-chain, and a more industrial phase of development.
The article notes that the guest’s comments do not represent Wu Blockchain’s views and do not constitute investment advice. It also says the audio transcript and translation were completed by GPT and may contain errors.
Why Zheng ties Bitcoin’s weakness to Strategy’s expected selling
Asked about the sharp drop in Bitcoin and the various explanations circulating in the market, including Strategy sales, ETF redemptions, macro changes and liquidations, Zheng said Strategy remained the key factor. The real pressure, he argued, did not come from one isolated sale. It came from a change in expectations, with the market starting to price in repeated sales ahead.
He pointed to Strategy’s May earnings call, where the company said it wanted to keep BTC per share neutral. As instruments such as STRC, STRZ, STRD and STRF continue to expand, he said Bitcoin no longer stands purely as an asset for common shareholders. It also has to sit behind creditors and preferred shareholders. That makes it more expensive to preserve neutrality at the per-share level.
In the past, the market largely assumed Strategy would fund preferred dividends by selling stock, which meant limited direct pressure on Bitcoin. Zheng said that threshold for raising money through new equity has now become higher, shifting more of the cash-flow burden toward BTC itself. As long as MMV stays below the neutral threshold, he said, the company becomes more likely to sell BTC in small but recurring amounts to cover cash needs. If coupon or dividend frequency rises, the market will naturally start to expect periodic sales rather than a one-off event.
Under that logic, he said the key issue in this decline is not how much BTC has already been sold. It is whether the market believes selling will continue. That is why, in his framing, ETF selling looks more like an outcome than an initial cause. If investors conclude Strategy is likely to keep selling, related capital may exit before those sales arrive.
A financial experiment and the question of a death spiral
When asked why he described Michael Saylor’s approach as a financial experiment, Zheng said the goal was essentially to test the market’s ability to absorb steady, incremental BTC sales.
From a financial standpoint, he said, when the MMV premium is not high, selling small amounts of BTC does less damage to BTC per share than issuing stock. On that basis, he called it the first-best option. The problem is that after the large-scale issuance of STRC since March, the burden from preferred shares and perpetual instruments, including interest and dividend payments, has risen noticeably. Cash-flow management is no longer optional. The issue now is not whether Strategy has to manage cash flow, but which tool it should use.
If the market can absorb continued low-volume BTC selling, he said, the structure can keep running. If that selling ends up pulling down the stock price, dragging MMV lower, worsening the dislocation and reinforcing expectations of more BTC sales, Strategy may have to make a softer turn. That could mean leaning more heavily on stock issuance again, or using a mix of equity sales and BTC sales. Zheng said that would sacrifice part of the BTC-per-share profile, but it could also reduce the hit to both the coin and the stock, making it a second-best solution.
He described the current setup as a game between Michael Saylor and the market. Saylor is watching to see at what level demand becomes strong enough to absorb supply, while the market is waiting for a lower and more certain entry point.
On whether Strategy and Bitcoin could fall into a joint “death spiral,” Zheng said this issue alone was probably not enough. In his view, that kind of outcome would usually require fresh macro negatives or a larger systemic shock on top of the current pressure.
As long as Strategy eventually makes a softer adjustment and does not keep selling BTC rigidly, he said, bottom-fishing capital would probably return. The open question is not whether buyers exist, but at what price they step in. He gave 62,000 as one possible level, while adding that the market may look lower as well. Right now, he said, participants are still waiting for that point.
His overall reading was cautiously constructive. He said the current decline looks more like structural pressure created by changes in Strategy’s financing mix than a move driven purely by tighter macro liquidity. Without a new major negative catalyst, he said, the situation is still more likely to reverse than to turn into a genuine death spiral.
AI, tokens and a new model of labor
On the rally in AI-related U.S. stocks, Zheng boiled the story down to a simple point: tokens are becoming a form of labor for a new era.
He said companies used to rely on human labor as their main productive input, whether physical work or knowledge work. Now many execution-heavy jobs that used to be done by people are being replaced by AI and tokens. In the future, he said, the scarcest people may be those who can define goals, design solutions, push execution and solve problems end to end. A small number of those people, combined with large numbers of tokens, could form a new labor system.
That shift, he said, would change company structures directly. Firms historically built many layers because information had to be passed from person to person. In an AI era, a range of middle-management, assistant, IT and execution roles could shrink. What carries more value then is not raw execution alone, but influence, decision-making and imagination.
Zheng said companies once spent money mainly on employees. Going forward, more budgets may be directed to tokens, models and compute. Model companies then spend upstream on chips, energy, optical modules and data centers. Because expansion in those segments is limited and supply cannot keep up with demand, he said, they become the most persistent beneficiaries in the AI chain. That, in his telling, is the core reason those U.S. stocks keep rising.
He added that services may be hit first, since accounting, legal work, consulting and data analysis are knowledge-heavy tasks that AI can replace relatively easily. Inside firms, operations are likely to become more automated. Between firms, machine economies may begin to form on-chain. At that stage, many transactions, collaborations and even payments could be handled by machines.
When asked whether this move is only short-term speculation, Zheng said no. He sees the machine-economy era as just beginning. He also said many people misunderstand the idea of a “one-person company.” It does not mean one individual working alone. It means one person coordinating a dozen or even dozens of agents. Together, those agents may deliver the output once associated with hundreds of workers. In that sense, the one-person company still depends on a large labor force, except that the labor comes from intelligent agents.
That is why, he said, he keeps returning to the same point: the token is the new labor unit. Companies used to spend to hire people. Now they are moving more of that budget toward tokens. If tokens can keep amplifying revenue, profit margins improve materially. He said that is the core logic behind bullishness on the AI supply chain.
His conclusion was that the U.S. market is pricing a future in which more companies become AI-native, replace labor with tokens, raise automation and, as a result, produce much higher margins. In his view, that is the deepest and most rational driver of the current rally.
Why crypto exchanges are moving toward U.S. stocks
As more crypto exchanges open access to U.S. equities, Zheng said he has long believed offshore centralized exchanges only have two paths.
The first is prediction markets, but he called that route very hard. In his view, the leadership structure is already largely in place, and most current exchanges will struggle to transform into the next all-purpose venue for trading everything.
The second path is to become a distribution channel for real-world assets. Right now, he said, the most important real assets are U.S. stocks and U.S. Treasurys, with gold as another major direction.
The deeper reason, he said, is that after all these years, truly valuable crypto-native assets remain limited. Bitcoin is one. A small number of DeFi infrastructure projects and public blockchains may also qualify. Beyond that, he said, most native assets still lack durable intrinsic value and cash-flow support. If that is the asset base, then the trading infrastructure built around it will eventually go looking for new instruments with clearer value.
From that perspective, he said, the CEX shift into U.S. stocks is natural. He does not see it mainly as a squeeze on crypto assets. He sees it more as the industry returning to reality: genuinely valuable assets are scarce, and exchanges are turning toward products that can support liquidity more effectively.
Even so, he said this is not necessarily bad for blockchain in the long run. The technology’s core value is not limited to issuing native assets. It also offers decentralized choice and a more efficient, lower-cost way to settle trades and transfer value. Putting real-world assets on-chain is meaningful in itself.
He went further, saying blockchain may ultimately look more like a technology built for machines than one built for humans. Over the next five to 10 years, he said, a more plausible picture is one where people interact with agents, and agents handle payments, trading and coordination with one another on-chain. If that happens, today’s on-chain infrastructure would be directly usable by machines.
For that reason, Zheng said he actually sees this as positive for Bitcoin over the long term, because more humans and more machines would both end up touching on-chain assets.
Moving from altcoins to U.S. equities without rewriting your playbook
Asked what advice he would give to crypto users and traders who have spent years trading altcoins, Bitcoin or public-chain assets and are now moving into U.S. equities, Zheng said he does not think they need to change much on purpose.
He argued that U.S. equities and on-chain assets are structurally more alike than they appear. U.S. stocks include value names, growth names and plenty of assets with meme-like characteristics. One reason meme activity on-chain has weakened, he said, is that the most compelling meme assets have already migrated into the U.S. stock market.
Those assets still tell the same core story: changing the world. That narrative used to belong to blockchain. Now stronger versions of it are appearing in U.S. equities, in areas such as quantum computing, nuclear fusion and SMR. He said many of those trades are also hard to justify using earnings, cash flow or discounted cash flow models alone. They carry a strong meme component as well.
That means traders who once chased altcoins or meme coins may find that pursuing far-dated concept trades in U.S. equities is not such a different exercise. Those who have always focused on cash flow, fundamentals and value support can also find their equivalents in value and growth stocks.
His point was that nearly every style found in crypto has a matching spot in U.S. equities. Most people do not need to force a change in method to find familiar assets and familiar ways of trading them.
If he had to give one direct suggestion, Zheng said it would be this: do not force yourself to change methods just because the market changes. People who have survived this long usually already have a tested way to stay alive. The important part is to keep what still works.
The “1011 event” and the blow to altcoin liquidity
On whether the altcoin speculation cycle is effectively over, Zheng said that was a fair way to read it.
He said the main reason the altcoin market has largely ended is that crypto liquidity was damaged too severely. In his account, the “1011 event” dealt a heavy blow to the industry’s strength. Public reporting put liquidations at $19 billion, but he said the real figure was probably well above that. Market talk has placed the number around $40 billion to $50 billion, and Zheng said that range may be closer to reality.
He stressed that what disappeared was not just paper market capitalization. It was real cash. Crypto’s total market cap is not that large to begin with, he said, and a significant part of it is locked up or inflated. The amount of capital that can truly move is much smaller than headline numbers suggest. Under those conditions, losing hundreds of billions of dollars in cash in a single day would be a major shock to sentiment and liquidity across the industry. In his words, the “1011 event” was the last straw that broke the altcoin cycle.
As for why meme-style assets in U.S. equities can still trade well, Zheng said the answer is straightforward: the U.S. stock market is the deepest pool of global liquidity right now. If crypto’s own liquidity is weak, money will naturally migrate to the stronger market.
He also said that from the U.S. side, support for Bitcoin, blockchain, on-chain markets and centralized exchanges comes with strategic considerations. In his framing, the U.S. logic is to turn blockchain, on-chain venues and CEX platforms into channels through which U.S. assets can attract global capital and hot money. Pushing the U.S. financial system on-chain extends the financing and distribution reach of American assets worldwide.
Zheng added that this is only one government’s way of understanding and using the technology. Whether blockchain and crypto will ultimately be fully shaped by state interests is a separate question. A more realistic outcome, he said, is a long period of coexistence in which on-chain systems and sovereign states cooperate, use one another and compete at the same time.
Still, he said that at least for now, the U.S. approach is steadily turning into reality.
More caution for the second half, but not a full top call
On the macro outlook for the next six months and through year-end, including what newly appointed Federal Reserve Chair Warsh might do, Zheng said uncertainty is rising.
One reason is that markets have already gone up a great deal. Another is that several giant companies may still list, including SpaceX, OpenAI and Anthropic. The real pressure, he said, is not only the funding they absorb. If companies on that scale are brought into major indexes quickly, institutions operating with limited liquidity may have to sell other heavyweight stocks to rebalance. That could create pressure across the market. Because of that, he said he becomes more cautious after June.
Another key variable is the midterm election. If Democrats end up taking both chambers, he said, that may lean negative for both Web3 and AI because their policy focus is more on labor rights, regulation and oversight than on allowing frontier technologies to expand at full speed.
At the same time, he said the market may still be underestimating AI’s real economic contribution. AI has already penetrated many parts of the economy, but existing statistical methods may not fully capture it. Over the long run, he still sees a strong productivity boost.
For him, the real issue is not only growth. It is distribution. If distribution mechanisms are not adjusted properly, the result could be an extreme split in which a small number of people who can harness AI take most of the gains while a large share of the middle class gets squeezed or pushed out of work. In that case, productivity rises but aggregate consumer demand weakens. That is why he leans toward long-term deflation rather than long-term inflation.
He said distribution mechanisms will therefore be crucial in the coming years. Measures such as an AI tax, in his view, are likely to arrive within three to five years because many future social arrangements will need a new tax base.
Looking only at the second half of this year into next year, Zheng said he did not want to make an overly absolute call. Short-term correction pressure is clearly rising, especially around a potential SpaceX listing, but he sees that more as an adjustment than a definitive market top. As long as capital expenditure by the largest companies continues, he said, the broader run is not over.
Over a longer horizon, he remains positive on AI and on the combination of AI and blockchain. Internal corporate processes will keep moving toward automation, and machine economies may form on-chain between companies. That larger direction, he said, has not changed.
His final point was that blockchain and Web3 still have strong prospects, but the style of the market is likely to become more mature. The old phase of indiscriminate momentum and easy gains may have passed. What comes next, in his view, looks more industrial and more institutional.