Particle Founder: The entrepreneurial insights I have gained the most from in the past year
Author: Pengyu Wang, Founder of Particle
As a founder, the most sincere and practical entrepreneurial sharing I've seen in the past year: Don't do lean startups.
Recently, I have been focusing on two main tasks:
Actively exploring and using a large number of AI products to understand the real capabilities that AI adds for entrepreneurs without a coding background, as well as the current boundaries of AI tools. I have built a complete AI workflow and independently launched a SaaS product that is even making money, which is currently in limited use. I expect to introduce it to everyone in a few days.
Summarizing the entrepreneurial insights and lessons learned over the past year. I have outlined the entrepreneurial principles I hope to always follow and the pitfalls I can try to avoid in the future.
One of the most impactful entrepreneurial principles I hope to always follow comes from a recent public sharing by a well-known entrepreneur:
"Don't release your product too early."
This was a response from Google co-founder Sergey Brin at a campus event at Stanford in December 2025.
The background is that in December 2025, during the closing event of the centennial celebration of the Stanford School of Engineering, Google co-founder Sergey Brin was invited back to campus for a dialogue. The discussion was with Stanford President Jonathan Levin and Dean of Engineering Jennifer Widom.
A student asked how to avoid pitfalls in entrepreneurship:
Brin's core answer: Don't make a big deal out of releasing your product before it's ready—he directly cited Google Glass as an example, implying that when you have a cool new hardware idea, you must first refine it thoroughly before organizing flashy release events like skydiving or airships.
This sharing was very sincere; most entrepreneurs at such events tend to share politically correct views or high-level motivational talks that sound inspiring but lack actionable steps. But Brin provided a very practical perspective.
We have spent a lot of time, made many mistakes, and incurred significant costs to understand the importance of this statement.
Because the entrepreneurial views we have always accepted are about lean startups, lightning-fast entrepreneurship, user-first approaches, and rapid iteration.
Why this might be wrong, let's first discuss Brin's core support: because once you release a product too early, it's hard to distinguish whether you are on the right path of iteration or just constantly patching up various so-called user desires. Once you start sending signals externally, it's like getting on a "treadmill"—you are bound to a delivery timeline, but you may not have enough time to complete everything that needs to be done. Meanwhile, external expectations will snowball, and you haven't given yourself enough time to digest, judge, and handle these expectations.
Combining my personal entrepreneurial experience, another important reason is that when you release a product too early, it may indicate that you haven't thought through two questions:
What drives the emergence of winners in this market segment: is there still an opportunity driven by the product?
If it is product-driven, then what are the actual functions, performance, or designs that can truly drive the product?
Taking our UniversalX as an example, we "perfectly" made these two mistakes:
We did not realize that there were still opportunities driven by the product in the market at that time (we didn't even assess this possibility), and we placed too much emphasis on the so-called time window. Essentially, we were overly opportunity-driven and fundamentally lazy in our strategic approach.
Since we did not assess whether there were still product-driven opportunities, we could not make optimal decisions in finding the core support for driving the product, so our differentiating factor was later proven to be the "multi-chain." However, the market proved that the underlying product driving for trading terminals could only rely on: information asymmetry (alpha, at least making users feel there is alpha) or time differences (performance).
We only understood 80% of this mistake when Axiom emerged, relying on product performance, and quickly captured the largest market share in a seemingly very competitive environment. Why not 100%? Because we continued to make mistakes afterward, not going all in on alpha and performance, still aligning and completing functions. And we are still paying the cost for this mistake today; yes, we are now spending time aligning performance (and this has been a year since we launched the product, with 90% of people already feeling that the trading terminal industry is meaningless).
In simple terms: when we started our business, we too easily took speed + iteration as an unbreakable truth, neglecting to think about where the decisive steps in market competition truly lie. We also too easily regarded any early feedback from users as a positive incentive, which easily led to misalignment in the direction of iteration and increased the sunk costs (time + emotion) of quickly adjusting the business (or even shutting it down) later on.
In the AI era, I believe this is even more true; tools have leveled the productivity gap and strengthened information equality. This has led to a sharp decrease in production costs for just adequate products and products without leverage in design, rendering the term "competitive entrepreneurship" meaningless.
As the saying goes: when there are magic lamps everywhere, what wishes you make are more important.
Stop lean startups, stop lightning-fast entrepreneurship, and think carefully about what your product wishes are.
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CEO Paul Yu stated: "2025 marked the company's first full year as a bitcoin mining enterprise, characterized by rapid execution and structural reshaping. We completed a comprehensive adjustment of our asset system and established a globally distributed mining network. Additionally, the company introduced a new management team, further strengthening our capabilities and competitive advantage in the digital asset and energy infrastructure space. The completion of the NYSE direct listing and USD pricing also signifies our transformation into a global AI infrastructure company."
"As we enter 2026, the company will continue to optimize its balance sheet structure and enhance operational efficiency and cost resilience through adjustments to the miner portfolio. At the same time, we are advancing our strategic transformation into an AI infrastructure provider. Leveraging EcoHash, we will utilize our capabilities in scalable computing power and energy networks to provide cost-effective AI inference solutions. The relevant site transformations and product development are progressing simultaneously, and the company is well-positioned to sustain its execution in the new phase."
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· Fair Value Loss on Bitcoin Collateral Receivables: $171.4 million
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The net loss from ongoing operations was $285 million, compared to a net profit of $2.4 million in the same period last year.
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· Revenue Cost (depreciation): $116.6 million
· Operating Expenses: $28.9 million (including related-party expenses of $1.1 million)
· Miner Impairment Loss: $338.3 million
· Bitcoin Collateral Receivable Fair Value Change Loss: $96.5 million
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As of December 31, 2025, the company's key assets and liabilities are as follows:
· Cash and Cash Equivalents: $41.2 million
· Bitcoin Collateral Receivable (Non-current, related party): $663.0 million
· Miner Net Value: $248.7 million
· Long-Term Debt (related party): $557.6 million
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• Financial Performance:
Total revenue for the full year 2025 was $688.1 million, with $179.5 million in the fourth quarter.
Bitcoin mining business revenue for the full year was $675.5 million, with $172.4 million in the fourth quarter.
Full-year adjusted EBITDA was $24.5 million, while the fourth quarter was -$156.3 million.
• Mining Operations and Costs:
A total of 6,594.6 bitcoins were mined throughout the year, averaging 18.07 bitcoins per day; of which 1,718.3 bitcoins were mined in the fourth quarter, averaging 18.68 bitcoins per day.
The average mining cost for the full year (excluding miner depreciation) was $79,707 per bitcoin, and for the fourth quarter, it was $84,552;
The all-in sustaining costs were $97,272 and $106,251 per bitcoin, respectively.
As of the end of December 2025, the company has cumulatively produced 7,528.4 bitcoins since entering the bitcoin mining business.
• Strategic Progress:
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The company's Chief Financial Officer, Michael Zhang, stated: "By 2025, the company is expected to achieve significant revenue growth through its scaled mining operations. Despite recording a net loss of $452.8 million from ongoing operations, mainly due to one-time transformation costs and market-driven fair value adjustments, the company, from a financial perspective, will reduce its leverage, optimize its Bitcoin reserve strategy and liquidity management, introduce new capital to strengthen its financial position, and seize investment opportunities in high-potential areas such as AI infrastructure while navigating market volatility."
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The total operating costs and expenses for the fourth quarter amounted to $4.56 billion, primarily attributed to expenses related to the Bitcoin mining business, as well as impairment of mining machines and fair value losses on Bitcoin collateral receivables.
This includes:
· Cost of Revenue (excluding depreciation): $1.553 billion
· Cost of Revenue (depreciation): $38.1 million
· Operating Expenses: $9.9 million (including related-party expenses of $1.1 million)
· Mining Machine Impairment Loss: $81.4 million
· Fair Value Loss on Bitcoin Collateral Receivables: $171.4 million
The operating loss for the fourth quarter was $276.6 million, a significant increase from a loss of $0.7 million in the same period of 2024, primarily due to the downward trend in Bitcoin prices.
The net loss from ongoing operations was $285 million, compared to a net profit of $2.4 million in the same period last year.
The adjusted EBITDA was -$156.3 million, compared to $2.4 million in the same period last year.
The total revenue for the full year was $6.881 billion. Of this, the revenue from the Bitcoin mining business was $6.755 billion, with a total output of 6,594.6 Bitcoins for the year. Revenue from the international automobile trading business was $9.8 million.
The total annual operating costs and expenses amount to $1.1 billion.
Specifically, they include:
· Revenue Cost (excluding depreciation): $543.3 million
· Revenue Cost (depreciation): $116.6 million
· Operating Expenses: $28.9 million (including related-party expenses of $1.1 million)
· Miner Impairment Loss: $338.3 million
· Bitcoin Collateral Receivable Fair Value Change Loss: $96.5 million
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· Cash and Cash Equivalents: $41.2 million
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