Web3, once sold on high salaries, growth and big narratives, is now going through a prolonged wave of layoffs. In a report published by TechFlowPost, author Jialiu of Zhangsheng BeatZ wrote that some platforms have even treated “poaching employees from competitors with high pay” as a KPI, then dismissed those hires months later under various pretexts to disrupt rival teams and obtain intelligence and client resources.
The report places the trend inside a wider tech retrenchment. In the first half of 2026, the U.S. technology sector cut close to 140,000 jobs. Amazon reduced its workforce by 9%, while Meta cut 10%. Their official explanations were broadly similar: AI is changing everything, and companies need to streamline. The article also says that more than 56% of layoff events in 2026 explicitly cited AI, automation or machine learning as a reason, making AI the top stated cause of U.S. corporate layoffs for four straight months. At the same time, nearly 60% of companies acknowledged that layoffs or hiring slowdowns had been packaged as “AI-driven” when the real issue was financial pressure.
According to the report, the shock has not stopped in Silicon Valley. Web3, sitting between technology and finance, has been hit especially hard. Since the start of this year, and particularly in recent months, news about cuts, team reshuffles and employee movement at major trading platforms has spread across X, Reddit, Xiaohongshu, Maimai and private coffee chats among industry workers. BitMEX, once highly prominent, has largely faded from the mainstream field of view, while smaller platforms are exiting or shrinking business lines. With talent and attention being pulled toward AI, layoffs in Web3 have become a reality at many firms.
Many employees say they learned they were out only after access was shut off
One interviewee, Kevin, said he received notice of termination with only three days left before his last day. He had previously worked at a large internet company and moved into Web3 after being drawn by higher pay and the sector’s narrative. Only later did he learn that the decision to remove him had effectively been made more than a month earlier. During that period, work still appeared normal. Meetings continued. Messages were answered. Then HR contacted him, and he was let go.
Looking back, Kevin said the only possible warning sign was that two people had already left his 10-person group before him. At the time, the explanation inside the team was that they were “not a fit” or had gone to find easier jobs. He later came to believe that pressure to push them out may already have been underway.
Richard described a harsher version of the same process. After spending nine years as a full-time father, he returned to work and joined a smaller crypto trading platform. Soon after, he and many colleagues were laid off. One morning he opened his computer and found his system access had been disabled. He initially thought it was a technical problem, only to find roughly 40 colleagues in the company group chat asking the same thing: why could they no longer log in? Hours later, they received a layoff notice in their personal email accounts. The dismissal was effective immediately.
Shortly before that happened, Richard said his manager had hinted that one of the developers under him “might need adjustment.” He tried to reorganize work to make the case that the developer was indispensable. Before he could submit that proposal, both of them were gone.
Another former employee, identified as Xiaoyu, described a similar pattern. At her previous company, the first step in a layoff was to disable Slack accounts in batches and cut off email access. Whenever someone suddenly disappeared from Slack, employees would rush into private chats to exchange phone numbers and LinkedIn links because no one knew who would be next. When her own dismissal came, her manager messaged her on Slack asking whether she was free for a call. Before she could reply, all of her access had already been revoked.
Quarterly cuts, same-day last days, and disputed severance
Kevin said layoffs continued in his group for months after he left, leaving just two people. At his platform, around 10% of staff were cut each quarter, adding up to 40% over a year.
The report also mentions Coinbase. In May, the company announced about 700 global layoffs, defining the move as an “AI-native reorganization,” equal to roughly 14% of staff. But according to people cited by Zhangsheng BeatZ, the impact on Coinbase’s India office was far greater than that headline figure. One former employee said around 90% of staff in India had left, spanning all business departments rather than sales alone. Only a very small number of engineers viewed as top-tier were invited to relocate to Canada and continue working there.
According to the account cited in the report, the main reasons for the scale of the India cuts were high costs and the time gap with the U.S. Coinbase was said to be paying about 7.5 million rupees to an SDE2 in India, roughly equal to CAD 110,000, comparable to the pay of a mid-level engineer in Canada. In many high-paying product companies, the report says, architects in India can even earn more than peers in the European Union.
The article adds that at several exchanges, employees who failed to reach an agreement with HR on severance terms were told that same day would be their final workday, followed by an immediate shutdown of system access. It also says that BitMart, a trading platform that recently shut down, had already started cutting entire departments in May.
Zhangsheng BeatZ further reported that the timing of many layoffs was not random. Around June 30 was described as a peak period because July would bring a new round of financial reporting. Cutting staff and removing expenses could quickly improve the profit-and-loss statement. In that telling, layoffs were not only about reducing cost. They were also a tool of financial narrative management in front of investors.
Layoffs are often reframed as performance failures
The report argues that this contraction is not limited to a handful of firms. Across Web3, layoffs have become widespread, while only a small share of severance arrangements have been viewed as reasonable or satisfactory. Several interviewees said companies moved so fast to cut contact and permissions that workers lost access to the very channels they would have needed to argue for their rights.
According to people cited in the article, employees in operations and product roles, who were more likely to work from physical or overseas offices, sometimes still received a normal handover period and compensation. Technical staff, especially remote workers, were more exposed to direct and immediate dismissal. Many IT employees were based in mainland China while the platforms themselves were incorporated offshore, raising the practical cost of pursuing claims and making formal action unattractive for many individuals.
Even when there was a short transition period, employees still faced pressure. Kevin said HR asked him to fill in a reason for departure in the system and discouraged him from choosing “dismissed by company.” In his account, if an employee selected “personal reasons,” the company would not need to pay additional compensation. He ultimately received no severance and was only paid salary and overtime up to his last day.
The report says many platforms have tried to make layoffs look like something else. In some cases, company-issued laptops allegedly came with extensive monitoring systems capable of tracking keyboard input frequency and mouse clicks, with those records folded into performance evaluations. The article even cites one account in which an employee was dismissed the day after watching a short drama on iQIYI using a company computer.
Another common method, according to the report, was to assign KPIs that were nearly impossible to complete and then use failed reviews to justify dismissal under labels such as “poor performance” or “not meeting company standards.” A former exchange employee also said on X that during one layoff period, the company held recurring “Web3 industry knowledge” tests and forced them into the KPI framework. Failing the test could put an employee at risk of being fired.
Those who remain are not necessarily better off
Xiaoyu said survivors often envied colleagues who had already been let go because at least their uncertainty was over. Those who remained lived in a state of constant tension, never knowing whether they would be next. Since the layoffs began, she said, morale had turned deeply negative.
Richard said the atmosphere at work changed in a quieter but noticeable way. Before the cuts, the pace had been intense and product cycles aggressive, yet people were still busy with actual product updates and feature work. Later, the workload shifted toward satisfying management’s invented requirements. Assessment mechanisms intensified, staff had to check in on the hour, and meetings became even more frequent.
At his platform, daily standups were pushed to an extreme. The original point was speed. Instead, they became a drain. The team held two standups a day, but many people still had no clear sense of where the product was headed. Three project managers rotated through within half a year, and the product management team was eventually almost empty. Some projects stopped midstream because key people were dismissed in the middle of the day, at times only minutes before a meeting.
Richard also said his company used outsourced teams whose pay was notably higher than that of full-time employees. Only after speaking in person with two colleagues did he learn, he said, that an executive had withheld staff raises for two years.
Kevin described a similar feeling. In his view, the exchange he worked for increasingly resembled a stale, rigid old institution. At a time when security incidents were recurring across the exchange industry, technical teams were not given more resources. Instead, they became highly cautious and mainly focused on avoiding mistakes.
John focused on a different issue: workplace culture. From the moment he joined, he said, the company’s “Chinese culture” was especially strong. Chat records, JIRA tickets and meeting notes were almost entirely in Chinese, leaving foreign employees with weak Chinese feeling excluded. The tempo was strict, fast and tied to quarterly performance reviews. Because teams were spread across time zones, off-hour availability became routine. His team’s weekly standup was scheduled on Sunday evening, and a QA colleague in the U.S. time zone often sent messages around 11 p.m. He described the environment as “24 on call,” with little separation between work and life.
Internal power struggles and loyalty politics
Richard said he joined during the company’s strongest period and watched it unravel. What stood out most was not the product side but the increasingly naked power struggle among senior management.
By his account, the company’s partners fell into a severe trust crisis linked to government investigations and potential litigation. One side’s CTO/CFO came to believe they had been misled by the other partners, or had not received proper support when regulatory trouble emerged. The partnership eventually split. One side took a core team and one senior employee, formed a “board,” and set up a new company that became the actual developer of the old product. People once described as friends became clients within a month. By February, the new company was pushing ahead at a pace of two new products a week. This was happening around the time Richard resigned.
For employees lower down the chain, he said, there was neither a right to know nor a real choice. They became casualties of conflict and instability at the top.
Kevin made a broader point about the industry. In Web3, he said, many project founders and even exchange CEOs are only the visible figures. The real decision-makers are often behind the scenes. In that structure, the key quality for leaders is not necessarily innovation or technical ability, but loyalty. He argued that a toxic culture flows downward and tends to reward people skilled in political maneuvering, managing upward and acting tough toward subordinates.
Those not considered part of the inner circle can be eased out step by step, he said. First they stop getting invited to meetings. Then they are shifted to peripheral roles. Weekly reports are no longer required. New assignments stop coming. By the time a replacement is already in place, the sidelined employee realizes they have been hollowed out. Kevin said reviews on Glassdoor often describe colleagues as supportive and decent, yet the overall system feels like an imperial court where even wording in front of superiors must be handled carefully.
Pressure on business models, liquidity and venture capital
Kevin’s blunt conclusion in the report was that “the entire crypto business model has collapsed.” In his view, exchanges historically depended on two major revenue sources: trading fees and listing fees. When markets were hot, new projects came in, retail traders were active, and both fees rose together, supporting team expansion. That model now looks far weaker. As the article quotes him, many listed projects have effectively been shown to be there to make money and then leave.
Listing fees are a central problem in the piece. Kevin said exchanges charge project teams extremely high amounts. A small project might pay hundreds of thousands of dollars just to list, even though its post-listing market capitalization might only be in the tens of millions. In his telling, the result is a downward spiral: lower-quality projects, more tokens trading below listing expectations, retail users leaving, shrinking volume, lower fee income, and exchanges raising listing charges even more.
The rise of on-chain derivatives venues is presented as another source of pressure. The report points to Hyperliquid as an example of a platform showing that the highest-margin part of exchange business, derivatives trading, no longer has to take place inside a centralized platform’s own system.
Broader market shocks are also accelerating the decline. Multiple interviewees brought up the industry-wide liquidation event on October 10 last year. According to the report, all open positions using leverage above 2x were forcibly liquidated that day, inflicting heavy losses on retail investors, who still have not recovered.
John’s comments centered more on the capital side of the industry. He told Zhangsheng BeatZ that many mid-sized Web3 firms managing between $100 million and $500 million were shutting down, while older financing strategies and DeFi yield strategies had become harder to sustain. Since last summer, he said, the drying up of crypto liquidity had been “very serious.” In his view, almost all altcoins launched in early 2025 were drifting toward zero, with very low book value. OTC volume was weak. In market making, aside from RWA-related activity, there was little worth doing. He also described a friend running crypto-neutral strategies at a market maker who improved market share and profit per trade, yet still saw the company’s overall profit drop sharply, with earnings commonly shrinking to around 30% of prior levels. That friend was eventually laid off as part of cost cuts.
Kevin added that venture capital in Web3 has also become far more cautious in both check size and deal count. In many cases, he said, funds are effectively not investing at all. Even when they do, the amounts are much smaller than before. His estimate was that VC allocation in this cycle had fallen by 80%. At the project level, he said that aside from some companies with Web2 business income on the B2B side, most projects have neither meaningful B-side revenue nor dependable consumer-side revenue.
Where laid-off workers go next
After leaving his exchange job, Kevin joined an AI startup. The report says he is far from alone. According to Zhangsheng BeatZ, most people leaving Web3 have moved toward AI. The explanation is straightforward: AI is the hottest sector, funding is active, jobs are more plentiful, and the skills overlap is real in areas such as growth, user acquisition and global operations.
Richard’s break with Web3 was more absolute. He said the exchange he worked for was full of incompetent people from top to bottom, from feuding partners to disengaged rank-and-file staff. He also moved into AI and left crypto behind.
The article says the number of people making a real transition into traditional industries is much smaller. A minority of technically strong workers in trading systems and risk control have gone to traditional market makers and quantitative firms. Some people in operations, business development and compliance have moved into conventional brokerages while Hong Kong and U.S. equity markets are active. But those are exceptions. More often, laid-off exchange staff end up at the next tier of smaller crypto platforms.
One reason is the bias they face outside the sector. Zhangsheng BeatZ says some HR departments in traditional finance will directly reject candidates whose resumes show they are still working at a Web3 company. In the eyes of some traditional finance professionals, the crypto sector represents gray-zone regulation, speculative culture and hard-to-verify performance. The article says even parts of the AI industry hold similar reservations. Companies focused on large models and infrastructure may look skeptically at candidates from Web3, viewing that industry’s idea of “growth” as based more on speculation and narrative than on genuine technical barriers.
Even in a shrinking market, exchanges are still fighting each other
The report argues that this downturn differs from earlier crypto winters. Prediction markets such as Polymarket and Kalshi, along with retail brokerage trading, are all competing for the same retail users and the same pool of capital. Money from U.S. retail investors is flowing into AI stocks and prediction markets rather than back into crypto.
Some industry participants told Zhangsheng BeatZ that conditions are even worse than in the 2022 crypto downturn. At least in 2022, retail investors were still present. After the mass liquidation event on October 10 last year, they said, the last leveraged retail traders were wiped out as well.
Yet even in this shrunken market, rivalry among exchanges has not eased. According to people cited by Zhangsheng BeatZ, some HR departments at trading platforms made “poaching employees from competitors with high pay” a KPI. Those hires could then be fired a few months later under different pretexts, after serving to disrupt a rival’s team rhythm or provide access to intelligence and customer resources. In that setup, the poached worker becomes a disposable tool.
The report compares that behavior to earlier subsidy wars in China’s internet sector and returns to the opening point: many companies present AI as the reason for layoffs, while the real driver is financial pressure. In the Web3 industry, the article suggests, the problem is not only the cycle or AI competition. It also lies in exchange practices such as charging project teams hundreds of thousands of dollars in listing fees, bringing low-quality tokens to market, draining employee trust and creativity through opaque assessments and monitoring systems, and continuing to spend energy on poaching from rivals during an industry winter instead of looking for new business models.
In the account presented by TechFlowPost, the Web3 layoff wave is more than a straightforward cost-cutting exercise. It is the result of pressure on business models, deteriorating internal management and increasingly destructive competition hitting at the same time.