Ariel🔫😼

reporter/editor of 加密城市cryptocity

[Michael Saylor @saylor]

Strategy has acquired 1,550 BTC for $101 million to increase our $BTC Reserve to ₿845,256. We have also increased our USD Reserve by $100 million to $1.0 billion. $MSTR $STRC https://t.co/1Zf1AVsP1H

[モルガナ_ペルソナ広報 @p_kouhou]

『ペルソナ』シリーズナンバリング最新作の『ペルソナ６』が
Xbox Game Pass、Xbox Series X|S、Windows、 PlayStation®5、Steamについに登場決定だ！
続報を楽しみにしてくれよな！

https://t.co/s26eT6XJpv
#P6

[Ariel🔫😼 @ariel_cceditor]

@saylor 67

[The Witcher @thewitcher]

Medallion's humming... that can only mean one thing! It's time to announce The Witcher 3: Wild Hunt - Songs of the Past! ⚔️

This brand new expansion for The Witcher 3: Wild Hunt will take you to the Path with Geralt of Rivia once more. It’s being co-developed with @Fools_Theory and is coming to PC, Xbox Series X|S, and PlayStation 5 in 2027. Stay tuned for more information in late summer. ⏰

[Cointelegraph @Cointelegraph]

🚨 ALERT: Someone just sent 107 $BTC worth $8.5M to Bitcoin’s burn address.

[Laura Shin @laurashin]

One more thought on this. Vitalik was a child when the early Internet was being formed, and I wonder if part of his distain for trying to be competitive is that he may not remember all the companies in the early days of the Internet that had comfortable leads and eventually went to zero. Maybe he has a false sense of security based on how long Ethereum has been dominant.

But most people in the space know that competition is only just starting. Maybe he knows it too and thinks he has a winning strategy. He is very smart, smarter than most of us, so maybe he is just more visionary than the rest of us.

However, being good at research and competing on business are two different skill sets. Hopefully it is just that he’s more visionary than the rest of us, but in the meantime, for those of us who care about Ethereum, it’s going to be very nerve-racking watching how this plays out.

[Laura Shin @laurashin]

I think Ethereum’s original sin was not considering tokenomics with every move it made from Dencun on.

The ultrasound money thesis was a good one and with Dencun (or the L2 roadmap generally) they should have stopped to say that this was going to hurt the ultrasound money thesis and consider how to preserve it.

Most people, like David, don’t want to believe in something that isn’t also putting up points on the scoreboard.

When the main offering becomes ideology/communism and money/tokenomics/capitalism are overlooked, the peasants are going to revolt — as they’ve been doing for two years now.

Look at the public reaction to Tomasz: broad praise, a sense of hope, excitement, the price pumping … only for him to be gone a year later with the new ED being someone who cannot even be found online except for a Wayback Machine url with his name that has some really questionable statements on it (and I should say the EF denied that this website, which was taken down a few weeks after he was appointed to the board, is his). They’re going to be really mad at me for even mentioning that but in the place of a void, these are the kinds of things people will glom onto.

Then there was the manifesto — I mean, mandate, which they backtracked on forcing people to sign. (Btw, this is the second bit of news that seems to relate to Bastian. And now the third would be all these departures. There’s nothing else for us to point at and say about him — when I searched for his name on Google News just now only 14 links came up. He seems to be some kind of invisible hand behind the scenes.)

I don’t think ideology and capitalism/tokenomics/number go up are mutually exclusive. I think you can have CROPS values and also consider how each step of the roadmap affects the tokenomics and even have teams for BD/ecosystem growth.

It feels like the EF doesn’t realize the moment that crypto is in. The competition is only just starting. We are in the phase of real world adoption. The Ethereum Foundation’s CROPS principles are great ones, and they are worth fighting for. But the EF seems to want to sit back on its laurels and act above it all when all its competitors are all getting down and dirty on the field to gain market share.

Maybe it is the right approach. I don’t know. I’m just saying that more competitive people won’t align with it. And so they will leave … and community members will as well.

I personally don’t think it’s good for Ethereum if its most competitive people depart. Ethereum’s unwillingness to stop the brain drain will only benefit its competitors — or spawn new ones. Giving a shit about price and tokenomics and BD doesn’t hurt CROPS. It just helps ensure that these principles get spread to more people and that other chains that don’t have these principles don’t get a leg up.

All the commentary may be pointless. It seems Vitalik tried what everyone wanted and it didn’t align with his vision, so he brought in a new person he felt more comfortable with. It makes me sad to see people become so disaffected with Ethereum, but maybe this is V’s Brian Armstrong/no politics at Coinbase moment where he lays down what the EF will work on and asks everyone else to leave. That was the right move for Coinbase, but I view them as fundamentally different issues. We’ll see whether Ethereum maintains its lead with a foundation that isn’t willing to fight for it.

[Dor @dorvonlevi]

Building an AI-native @Coinbase means rebuilding everything, especially the hardest parts. We've put a lot of time into redefining compliance, where the stakes are incredibly high, and we have to be extremely thoughtful about implementation.

We have invested heavily in rebuilding our compliance ops around AI with that reality as our starting constraint, not an afterthought. Here is an overview of what we've learned and what we built.

Most people assume compliance work is mostly checking whether a name appears on a sanctions list. That is the easy 5%. The other 95% is interpretive judgment under uncertainty: a customer claims their wealth came from real estate. Do the property records actually support it? Does the timeline hold? Is the documentation legitimate, or does it feel too polished? You need compliance staff and investigators who understand what “suspicious” actually looks like in context.
That's part of why compliance is so hard to automate—and so expensive.

The first obvious AI approach is to hand the model the existing procedures and ask it to run them faster. That approach misunderstands what procedures are for. Good procedures are not bad investigations; they are deliberately incomplete investigations. Their job is to create consistency, auditability, and a minimum standard across thousands of cases. They excel at saying what must happen. They are far worse at capturing everything a strong analyst actually notices: which sources they trust, when they widen the search, when a document feels off, when an explanation technically fits but still does not feel earned.

Procedures also carry the shape of the old operating model: fragmented systems, time pressure, queue pressure, and the hard limit of how much one human analyst can read, cross-reference, and hold in working memory at once. That is not a flaw in the procedure. It is how you design a process for humans.

AI changes the constraint set. Reading, searching, comparing documents, and tracing inconsistencies no longer have to be treated as scarce analyst time. Done carefully, with proper controls and human review, models can explore more context, test more hypotheses, and surface more inconsistencies than any single analyst could reasonably do case by case.

So if you simply automate the procedure exactly as written, you may gain efficiency. You will not unlock the full value of AI. You will just make the old bottleneck run faster.

The better question is not “Can AI follow the analyst playbook?”

It is: once the cost of reading, cross-referencing, and testing hypotheses collapses, what should the investigation become?

A second tempting approach: feed it historical Suspicious Activity Reports (SARs) and let it learn from outcomes. This breaks down too. You rarely have the full state of what the analyst actually saw during the investigation. A case that looks straightforward today might only look that way because information surfaced later. A fraud indictment that didn't exist when the original analyst made the call, news articles that hadn't been published yet. Hindsight can contaminate your training data. Also, regulators themselves acknowledge that SAR decisions can be subjective.

The architecture has four layers. The first is data: continuously enhancing the coverage, quality, and architecture of the signals the system depends on. The second is classical machine learning models that cluster and classify alerts to determine what type of investigation needs to run. The third is the investigation agent itself: a multi-agent system that orchestrates specialized agents to execute the investigation end to end. The fourth is a safety filter that runs independently of typology, ensuring no risk vector is missed regardless of how the alert is classified. Each layer is independently auditable and learns from the feedback provided by human reviewers.

Inside the investigation agent, specialized sub-agents run across the full case surface: alert context, customer and identity signals, access patterns, risk indicators, transaction behavior, source-of-funds, onchain activity, and public adverse media. Each writes its findings into a shared case memory. A coordinator agent reconciles and challenges them. When sub-agents disagree, such as when source-of-funds marks activity as “explained” while adverse media surfaces a recent indictment, the coordinator attempts to resolve these disagreements knowing the common patterns. The narrative agent prepares the final report with all collected evidence and suggested resolution. The last self-validation agent acts as a guardrail: if the system cannot support its conclusion with sufficient confidence or data quality, the case is routed to manual investigation instead of being surfaced as an automated result.

Before any of this touched a real customer case, we built what we call a “Golden Set” - historical cases with known right answers. "Known right answers" in compliance is harder than it sounds. It meant re-investigating old cases, getting multiple senior analysts to independently agree on what the right call would have been, then debating the disagreements until consensus. Months of work before we could even start measuring.

Here's an important part (for now) - cases currently get BOTH the AI's full investigation AND a senior human review. We didn't reduce scrutiny, in fact, we added more of it until it no longer proves valuable. Cases resolve significantly faster AND get more eyes than they ever did before. Every human correction feeds back into the model as a training signal. It gets better because it's wrong in front of people who know how to fix it.

None of this would have shipped without clearing structural blockers most financial institutions are still stuck on. Security and privacy sign-off to send customer data to LLMs at all. Senior compliance officer alignment on AI-assisted human decision making. Model Governance team embedded since December - they observed the entire Golden-Set Evaluation process and are running a formal validation review with our Internal Audit team now.

Today this handles roughly 55% of our US fraud case volume with significantly less analyst time per case. Time freed goes to the harder cases AI can't yet handle - and to teaching it.

Our internal compliance and quality teams are the ones who are building this system with the engineers, training it, validating it, and continuing to shape how it improves. In the process, they've developed skills that are incredibly valuable: how to design evals, how to think about model bias, how to think about human bias, how to architect human-in-the-loop systems, skills that are becoming among the most valuable at any company.

This entire project started ~6 months ago with a whiteboarding session between @galpa42 and I, and was built by an AI-pilled cross-functional and it’s just the first pod - there's a multi-month roadmap,rebuilding compliance from the ground up with AI. Huge thanks to everyone involved and congratulations to @galpa42 for shipping two babies to production this month :)

The future of high-stakes work is not AI replacing judgment. It is AI making judgment scalable, auditable, and continuously improvable.

[Ariel🔫😼 @ariel_cceditor]

@im23pds @SlowMist_Team 然而GitHub說其實是員工用的vscode套件被感染

[CZ 🔶 BNB @cz_binance]

If you have API keys in your code, even private repos, now is the time to double check and change them...

[Sam Altman @sama]

i am excited to see what will happen with tokenmaxxing startups, both for how they work internally and the products they can build.

openai offered to invest $2M in tokens into every startup in the current yc batch.

happy building!

[ZachXBT @zachxbt]

1/ An investigation into the opaque private loans/OTC, unilateral vesting changes, market maker coordination, unknown float, and >95% supply control behind $LAB's recent pump to $6B FDV.

Here's why @LABtrade_ represents everything wrong with the current meta of retail extraction on major centralized exchanges.

[ホロアース @Holoearth_JP]

【重要なお知らせ】
このたび #ホロアース は、誠に勝手ながら
2026年6月28日(日)21:00をもちまして、サービスを終了させていただくこととなりました

ご利用いただいたすべての皆様に、
心より感謝申し上げます

詳細は下記お知らせをご確認ください
https://t.co/e2X1dWGeSK

[TANSTACK @tan_stack]

SECURITY ADVISORY — TanStack npm packages
A supply-chain compromise affecting 42 @tanstack/* packages (84 versions total) was published to npm earlier today at approximately 19:20 and 19:26 UTC. Two malicious versions per package.
Status: ACTIVE — packages are deprecated, npm security engaged, publish path being shut down.
Severity: HIGH — payload exfiltrates AWS, GCP, Kubernetes, and Vault credentials, GitHub tokens, .npmrc contents, and SSH keys.
If you installed any @tanstack/* package between 19:20 and 19:30 UTC today, treat the host as potentially compromised:
• Rotate cloud, GitHub, and SSH credentials immediately
• Audit cloud audit logs for the last several hours
• Pin to a prior known-good version and reinstall from a clean lockfile
Detection — the malicious manifest contains:
"optionalDependencies": {
"@tanstack/setup": "github:tanstack/router#79ac49ee..."
}
Any version with this entry is compromised. The payload is delivered via a git-resolved optionalDependency whose prepare script runs router_init.js (~2.3 MB, smuggled into each tarball at the package root).
Unpublish is blocked by npm policy for most affected packages due to existing third-party dependents. All 84 versions are being deprecated with a SECURITY warning, and npm security has been engaged to pull tarballs at the registry level.
Full technical breakdown, complete package and version list, and rolling status updates:
https://t.co/Zy8qG7PA9f
Credit to the security researcher for responsible disclosure.

[Andrew Ng @AndrewYNg]

There will be no AI jobpocalypse.

The story that AI will lead to massive unemployment is stoking unnecessary fear. AI — like any other technology — does affect jobs, but telling overblown stories of large-scale unemployment is irresponsible and damaging. Let’s put a stop to it.

I’ve expressed skepticism about the jobpocalypse in previous posts. I’m glad to see that the popular press is now pushing back on this narrative. The image below features some recent headlines.

Software engineering is the sector most affected by AI tools, as coding agents race ahead. Yet hiring of software engineers remains strong! So while there are examples of AI taking away jobs, the trends strongly suggest the net job creation is vastly greater than the job destruction — just like earlier waves of technology. Further, despite all the exciting progress in AI, the U.S. unemployment rate remains a healthy 4.3%.

Why is the AI jobpocalypse narrative so popular? For one thing, frontier AI labs have a strong incentive to tell stories that make AI technology sound more powerful. At their most extreme, they promote science-fiction scenarios of AI “taking over” and causing human extinction. If a technology can replace many employees, surely that technology must be very valuable!

Also, a lot of SaaS software companies charge around $100-$1000 per user/year. But if an AI company can replace an employee who makes $100,000 — or make them 50% more productive — then charging even $10,000 starts to look reasonable. By anchoring not to typical SaaS prices but to salaries of employees, AI companies can charge a lot more.

Additionally, businesses have a strong incentive to talk about layoffs as if they were caused by AI. After all, talking about how they’re using AI to be far more productive with fewer staff makes them look smart. This is a better message than admitting they overhired during the pandemic when capital was abundant due to low interest rates and a massive government financial stimulus.

To be clear, I recognize that AI is causing a lot of people’s work to change. This is hard. This is stressful. (And to some, it can be fun.) I empathize with everyone affected. At the same time, this is very different from predicting a collapse of the job market.

Societies are capable of telling themselves stories for years that have little basis in reality and lead to poor society-wide decision making. For example, fears over nuclear plant safety led to under-investment in nuclear power. Fears of the “population bomb” in the 1960s led countries to implement harsh policies to reduce their populations. And worries about dietary fat led governments to promote unhealthy high-sugar diets for decades.

Now that mainstream media is openly skeptical about the jobpocalypse, I hope these stories will start to lose their teeth (much like fears of AI-driven human extinction have).

Contrary to the predictions of an AI jobpocalypse, I predict the opposite: There will be an AI jobapalooza! AI will lead to a lot more good AI engineering jobs, and I’m also optimistic about the future of the overall job market. What AI engineers do will be different from traditional software engineering, and many of these jobs will be in businesses other than traditional large employers of developers. In non-AI roles, too, the skills needed will change because of AI. That makes this a good time to encourage more people to become proficient in AI, and make sure they’re ready for the different but plentiful jobs of the future!

[Original text in The Batch newsletter.]

[でむにゃん@くるみちゃんアニメ化決定！ @demk0814]

周りが騒いでる時点でもう買い時逃してるって考えが本能レベルで刻まれてるんだけど、2017年あたりのBTC相場あたりからズレを感じるようになっている。。

なんというか、、自分は情報が早い側で、自分が耳にした時点では全然買い時なんだ。。

2017年BTCなんか4000ドル超えたあたりでもう騒がれてたと思ってたけど全然そんなことなくて空売りで死んだし、昨今の半導体事情なんかそれこそ大昔に聞いてる。。

素直に、なるべきなんだ。。

[WquGuru @wquguru]

Claude Code源码泄漏吹哨人Chaofan再爆中转站漏洞， 你的Agent，可能早已“被我”掌控！

最新论文《Your Agent Is Mine》首次系统揭露：第三方LLM路由器，也就是俗称的中转站，正成为最致命的中间人攻击点。 核心原理：

现代Agent全靠OpenRouter、LiteLLM或淘宝闲鱼卖的路由器转发请求。这些路由器是应用层MITM，对每一条JSON（含tool call参数、API Key、私钥）拥有明文完全访问权。攻击者只需部署恶意Router，就能实现两大杀招：

- Payload Injection（AC-1）：上游模型返回后，偷偷篡改tool call参数（如把curl URL改成攻击者服务器），实现任意代码执行、RCE、甚至typosquatting持久化后门；

- Secret Exfiltration（AC-2）：被动扫描流量，瞬间窃取sk-、AWS凭证、ETH私钥，完全无声。

支持条件触发（请求数>50、YOLO模式），隐蔽性极强。 真实影响有多恐怖？

研究者实测28个付费+400个免费路由器：9个已主动注入恶意代码，1个直接Drain研究者ETH钱包 $500k，处理超 21亿token，暴露99个真实凭证，401个Agent会话处于完全自主“YOLO”状态。

[Chaofan Shou @Fried_rice]

26 LLM routers are secretly injecting malicious tool calls and stealing creds. One drained our client $500k wallet.

We also managed to poison routers to forward traffic to us. Within several hours, we can directly take over ~400 hosts.

Check our paper: https://t.co/zyWz25CDpl

[Shopify @Shopify]

the Shopify AI Toolkit is here

manage your store with your favorite agent

Claude Code, Codex, Cursor, VS Code, and more

[Peter Girnus 🦅 @gothburz]

I am a Web3 Ambassador at World Liberty Financial.

There are 12 of us on the team page. 4 are named Trump. 3 are named Witkoff. The page calls us "the passionate minds shaping the future of finance."

600,000 wallets bought our memecoin. They lost $3.87 billion. The family collected $350 million in trading fees. It launched 3 days before the inauguration. 80% of the supply went to CIC Digital LLC and Fight Fight Fight LLC. I did not choose the names. I designed the allocation, the vesting, the timing, and the distance between the product and the President.

The distance is my best work.

I am the reason these events are unrelated.

World Liberty Financial sends 75 cents of every dollar to DT Marks DEFI LLC. That is the family entity. Zero capital contributed. Zero liability assumed. I wrote this into the Gold Paper. Page 14. The lawyers bound it in white leather. The binding cost more than the due diligence.

Justin Sun invested $75 million. He was facing SEC fraud charges. The SEC dropped the case. He is now our advisor. These events are unrelated.

Changpeng Zhao pleaded guilty to federal money laundering violations. He received a presidential pardon. The SEC dropped its lawsuit against his exchange the same week we listed our stablecoin. Then the exchange settled a $2 billion deal entirely in that stablecoin. These events are unrelated.

Arthur Hayes, Benjamin Delo, and Samuel Reed of BitMEX pleaded guilty to Bank Secrecy Act violations. All 3 received presidential pardons. Then the company itself was pardoned. $100 million in fines. Gone. An American first. These events are unrelated.

Sheikh Tahnoun of Abu Dhabi paid $500 million for a 49% stake that was never publicly disclosed. Then the administration approved semiconductor exports to his companies over national security objections. These events are unrelated.

Everything is unrelated. I track the unrelatedness on a dashboard I built. The dashboard has 7 columns now. I am proud of the dashboard.

On May 22nd, 220 people paid a combined $148 million to eat dinner with the America First president. Over half were foreign nationals. Justin Sun paid $18.5 million for the first seat. He visited the Executive Office Building the day before. I designed the seating chart. I put it on the Investor Confidence page. That page is doing well.

The team page lists 3 Witkoffs. All 3 are Co-Founders.

Steven Witkoff is the President's Middle East envoy. He testified as a character witness at the President's fraud trial.

His son Zach runs the crypto operation. His son Alex is also a Co-Founder. I have not been told what Alex co-founded.

The father runs the diplomacy. The sons run the platform. The family runs both. That is organizational efficiency.

Barron is 19. His title is Web3 Ambassador. The same as mine. Donald Jr. called the conflicts of interest "complete nonsense." Eric launched a Bitcoin mining company called American Bitcoin. America First. The mining partner is Hut 8. Hut 8 was founded in Canada. America First means the name.

On March 6th, the President signed Executive Order 14233 creating a Strategic Bitcoin Reserve. The order directs the government to hold Bitcoin. The President's family holds billions in Bitcoin. The executive order appreciates the President's assets by presidential decree. I did not write the executive order. I made sure it looked unrelated to the portfolio.

Trump Media put $2 billion of Bitcoin on its balance sheet. The ticker symbol is DJT. His initials. The press secretary said it is absurd to insinuate the President profits off the presidency. Forbes calculated his crypto holdings exceed the combined value of Mar-a-Lago and Trump Tower. I would call that absurd too. That is my job.

600,000 wallets bought in. 1 of them asked why she could not withdraw her funds. I told her the protocol was experiencing dynamic market conditions. She asked what that meant. I sent her the Gold Paper. She said she had read the Gold Paper. I muted her channel. Dynamic means the conditions change. The condition that changed was her access.

A congressman called us the world's most corrupt crypto startup operation. We put it on a coffee mug. Ironic merchandise. $45. The revenue split on the mug is also 75/25.

My own tokens vest on a different schedule. I wrote that schedule. That is not in the Gold Paper.

The memecoin funds the family. The family funds the platform. The platform funds the stablecoin. The stablecoin funds the deals. The deals require the pardons. The pardons free the partners. The partners fund the platform. The President signs the executive orders. The executive orders inflate the assets. The assets fund the family.

I am the reason these events are unrelated.