PANews

Written by: Four Pillars
Compiled by: AididaoJP, Foresight News
Key Points
Tokens ≠ Equity. When evaluating, use enterprise value / holder income, not enterprise value / protocol income.
The accrual ratio (the proportion of protocol income that holders can ultimately receive) is a key diagnostic indicator. In the projects we compare, this ratio ranges from 25% to 100%.
"Dilution" also differs. Team incentives are genuine operating costs (should be included in valuation multiples), while investor unlock sales are market events (should not be included in multiples).
Treasury value depends on "liquidity." The issue isn't "how much is in the treasury," but "can holders actually access it?"
I often see a common misconception in cryptocurrency valuation: someone pulls out a protocol with annualized revenue of $500 million.

Written by: imToken
A Question No One Has Asked Yet
The crypto industry is obsessed with public chains, tokens, and DeFi protocols. But a more fundamental transformation is approaching: Autonomous AI Agents are becoming participants in economic activities.
Today, Agents can book flights, write code, trade assets, and manage projects. Tomorrow, they will hire each other, negotiate terms, and build reputations—all without human intervention. When that day arrives, the entire economic infrastructure will need to be rethought.
Starting with wallets.
01 What Are Agents Truly Exchanging?
Beyond Fiat, Beyond Stablecoins
The intuitive answer is stablecoins—programmable, low-cost, instant settlement. But stablecoins are essentially digital wrappers of fiat currency, inheriting all the constraints of the physical world: centralized issuers, regulatory boundaries, and the implicit assumption that “end users are humans.”

Author: Joel John, Siddharth, Saurabh Deshpande
Compiled by: Felix, PANews
Under the impact of AI, the crypto industry is in a period of low sentiment, with venture capital pulling back and founders considering pivoting to AI. Is the crypto industry worth sticking with? Decentralised.co recently analyzed protocol revenue from data, pointing out that the valuation of crypto assets is returning to rationality, and the era of high premiums for infrastructure tokens has ended. Founders must abandon hollow narratives, establish business models based on real revenue and moat, and give tokens actual rights. Here are the details:
The "Fear and Greed Index" of the crypto market is at its lowest point in history. Meanwhile, its profitability has reached unprecedented heights. Since 2018

Author: Azuma, Odaily Planet Daily
Have you heard of Leopold Aschenbrenner?
He is one of the hottest names in the current AI investment circle — at just 24 years old, his Situational Awareness LP fund had a public holding size of only $225 million in Q4 2024, but in the Q4 2025 disclosure released last month, that number skyrocketed to $5.5 billion.
What many people don’t know is that Leopold Aschenbrenner was once part of the crypto world — he previously worked for FTX’s FTX Future Fund team until FTX’s bankruptcy and collapse.
A doctor’s family background producing an AI prodigy

MrBeast emphasizes that the uniqueness of content is the key to achieving 100 million views. He illustrates this by comparing the "ordinary cow" and the "purple cow," explaining that only innovative and unique ideas can attract viewers' attention. He recommends creators adopt "purple thinking" to produce fresh and original content.

Written by: Bitget Wallet
War reveals ruins to the world, but capital only cares about prices.
As the fire rekindles in the Middle East, colleagues in Dubai report bombings and air raid sirens. Missiles tearing through the sky symbolize humanity waiting for an unknown fate.
Meanwhile, on an invisible timeline, global financial markets have already begun recalculating: where should oil prices go? Will gold continue to surge? When will the stock market bottom out and rebound?
Capital shows no sympathy, nor does it anger. It simply does one thing—pricing uncertainty. For most people, it’s invisible, inscrutable, coldly logical, and ruthlessly paced.
But in turbulent times, understanding the logic of capital operations and risk pricing might be the last line of defense between ordinary people and the tide of history. Looking back at human geopolitical conflicts and financial history, you’ll find an almost unchanging pattern: in the face of war, capital markets always repeat the same script.

Author: 137Labs
In the past few years, competition in the artificial intelligence industry has almost revolved around model capabilities. From the GPT series to Claude, and then to various open-source large models, the industry's core focus has always been on parameter scale, training data, and inference ability.
However, as model capabilities gradually stabilize, a new question begins to emerge:
How can models truly complete tasks rather than just answer questions?
This question has driven the rapid development of AI Agent frameworks. Unlike traditional large model applications, Agent frameworks emphasize task execution abilities, including planning tasks, calling tools, iterative reasoning, and ultimately achieving complex goals.
Against this backdrop, an open-source project quickly gained popularity—OpenClaw. It attracted a large number of developers in a short period and became one of the fastest-growing AI projects on GitHub.

After the Lantern Festival, the core members of Alibaba Tongyi Qianwen team collectively resigned, reflecting conflicts between technological ideals and the company's resource allocation and organizational structure. Team members believe that traditional management methods cannot meet the innovative demands of the AI era, and the struggle between individuals and the platform has led to the outflow of creativity and talent, sparking a profound reflection on the management style of large corporations.

Ripple, through the acquisition of Hidden Road and gaining eligibility to participate in DTCC, has become part of the core clearing system of the U.S. financial markets. This marks that it is no longer an outsider to traditional finance and is integrating crypto assets with financial infrastructure. Despite challenges such as regulation and trust, Ripple's strategic positioning suggests that XRP could become a key asset for institutional-level settlements in the future.

Author: MetaHub Research
Introduction: Redefining the Boundaries of Prediction Markets
Prediction markets are platforms that allow participants to trade on the outcomes of uncertain future events, with contract prices reflecting the market’s consensus on the probability of those events occurring. They have demonstrated significantly higher accuracy than expert forecasts and polls in areas such as political elections, macroeconomics, sports events, cryptocurrencies, and corporate events.
At its core, a prediction market is an "information financialization" tool—prices represent probabilities. In high-uncertainty and highly subjective domains, prediction markets hold a distinct advantage.
By 2025, the total global trading volume of prediction markets is expected to reach approximately $50.25 billion. If we define maturity by trading volume rather than narrative, prediction markets will have truly transitioned from "short-term curiosity driven by events" to "sustainable markets" in 2025.
Kalshi has proven that the industry is not just "about having trading volume,"

Author: imToken
After this year's Spring Festival, do you also feel that the entire Web3 world seems to have suddenly been taken over by "Lobsters"?
Various AI Agents, automation proxies, and on-chain AI protocols are emerging one after another. From OpenClaw to a series of Agent frameworks, they have almost become the new narrative core. But if we look a little further back in the timeline, we can see that this wave actually has been foreshadowed for some time.
As early as February 25, during NVIDIA CEO Jensen Huang's latest earnings call, he made a significant statement: Agentic AI has reached a turning point. In his view, AI is undergoing a crucial transformation, no longer just a tool, but beginning to actively perceive, plan, and execute complex tasks.
And when this "autonomy" capability enters the Web3 world, a debate about control

Japan is actively promoting the Japanese Yen stablecoin to reshape its position in the global financial market, aiming to strengthen the core role of the Yen through on-chain arbitrage trading. Despite challenges such as liquidity, regulation, and retail participation, its success will bring an important non-USD asset base to on-chain finance.

Author: Lawyer Shao Shiwei
Profiting from buying and selling virtual currencies through price differences, but being prosecuted for receiving foreign exchange transfer funds—this article is based on a real case handled by Lawyer Shao, involving an OTC merchant accused of illegal business operations and concealing criminal proceeds through off-market USDT transactions.
In this case, the involved party has long been engaged in buying and selling USDT to earn price differences. During a normal transaction, he unfortunately received RMB funds transferred by an underground bank upstream, illegally exchanging currency for others. Big data analysis confirmed that this fund was identified as foreign exchange transfer funds.
The question then arises: Is simply earning from virtual currency price differences enough to be criminally liable for receiving foreign exchange transfer funds from illegal foreign exchange transactions upstream?
More notably, there are differing opinions within the case-handling agency regarding whether to apply the crime of illegal business operations or the crime of concealing and disguising criminal proceeds.
Lawyer Shao’s view is that such cases cannot be simply classified; the behavior must be assessed based on the individual's role in a layered manner.

In recent months, a quiet paradigm shift has been taking place in the AI field.
Conversational large models like ChatGPT, Claude, Gemini, etc., are essentially "advisory AI"—people ask questions and wait for answers. However, the emergence of a new class of tools is shifting AI's role from "providing suggestions" to "direct execution": they can autonomously access applications, complete workflows, and collaborate across platforms, truly becoming users' digital employees.
The core of this change is the rise of autonomous AI Agent framework ecosystems, represented by OpenClaw.
1. What are the four existing major frameworks?
OpenClaw: The most feature-rich, but also the riskiest
OpenClaw (formerly Clawdbot / Moltbot) is currently the most representative open-source autonomous AI assistant framework, and in just a few weeks, it has surpassed 2