Most AI research demos show you a polished answer. This one showed me the disagreement that happened before the answer. I gave Ling-3.0-flash @AntLingAGI a deliberately difficult question: Do four-day workweeks actually increase productivity, or do they simply compress the same workload into fewer days? Instead of asking for a quick summary, I asked it to coordinate five specialist roles: a scientist, a data analyst, a cross-validator, an archivist, and a research writer. Each role had a separate responsibility. The scientist defined the competing hypotheses. The analyst extracted comparable findings. The archivist tracked the sources. The writer could only use approved claims. And the cross-validator had one job: challenge anything that sounded more confident than the evidence allowed. That last role changed the result. The team reviewed 12 sources and challenged six major claims. Three claims were narrowed. One was rejected entirely. Even a widely repeated claim about a 40% productivity increase did not survive the evidence check. That is the part I wanted to see from an AI research workflow. Not just more information, but visible resistance to weak evidence. The final output included: - a direct executive answer - a structured research paper - a source and evidence table - a disagreement log - a six-slide executive deck - a quality-control summary The conclusion was also more useful than a simple yes or no: reduced working hours may maintain productivity and improve wellbeing under certain conditions, while compressing the same workload into fewer days can increase fatigue and intensity. The evidence did not support a universal productivity claim. What impressed me was not that Ling-3.0-flash generated a long response. Plenty of models can do that. It was the way the model maintained multiple roles, evidence standards, objections, citations, and deliverables across one extended workflow, while preserving uncertainty instead of smoothing it away. That makes Ling-3.0-flash especially interesting for work where execution matters as much as reasoning: research, search, coding, document processing, tool use, repeated checks, and other multi-step agent workflows. The strongest AI systems will not use the largest model for every task. They will combine deep planning with fast, cost-efficient execution. Ling-3.0-flash is built for that execution layer. Ling-3.0-flash is now available on OpenRouter and free to use through August 3, 2026. Try it in your coding, search, research, and tool-use workflows. Then show us what you build. Try Ling-3.0-flash: Documentation:

You have been given the same advice your whole life, and it is good advice. You cannot beat the market. Do not try. Buy a little of everything, hold it for 30 years, and do not flinch when it falls. It is true. It is also advice given, in part, by 535 people who quietly do not have to take it. In the last week of February 2020, you were told to stay calm. The market was sliding, the virus was still a rumor with a foreign name, and every steady voice said hold the line and think long term. Most of us did. We watched the retirement accounts fall and we held, because holding was the discipline and the discipline was right. That same week, senators of both parties who had sat in a closed briefing on the coming pandemic sold. Millions of dollars in stock, in the days before the drop. The Justice Department opened an investigation and closed it without a single charge. The rules held, because no one had broken them. It was not one strange month six years ago. Last year, 140 members of Congress made more than 14,000 trades worth about $720 million. They do not trade at random. The members who sit on the committees that write the defense budget trade defense contractors. The members who write Medicare and Medicaid policy trade the health insurers who live on those programs. The firms whose fortunes they shape are the firms they own. There is a law meant to stop this. It is called the STOCK Act, and when a member files a trade late, the penalty is $200. Not $200,000. $200, and even that is often waived. In all the years the law has existed, no member of Congress has ever been criminally prosecuted under it. I am not saying this to make you hate them. Hatred is cheap and it fixes nothing. I am saying it because of what we are usually handed to be angry about instead. We are pointed at the neighbor with the stimulus check, the family in line with an EBT card, the student asking to have a loan forgiven. We are taught to look sideways and down, at people who have less than we do, and to believe they are the reason the arithmetic no longer works. The edge that actually moved the money was never standing beside you in that line. It sat in a room you were not allowed to enter. Let me be careful, because this is the part that matters. There is nothing wrong with being rich. A person who starts a company, carries the risk, and builds and sells the thing is the country working as promised, and we should want more of them, not fewer. The objection here is narrow. It is a portfolio built out of a security clearance. An advantage that arrives with the seat instead of the work. We know it can be fixed, because it has been. When two Federal Reserve officials were found trading through the same 2020 crisis they were managing, they were gone within weeks, and the Fed barred its officials from trading individual stocks at all. An institution decided its credibility was worth more than its portfolios. Congress looked at the same conflict this month. The House passed a bill to ban the practice and gave it the name you wanted to hear. It lets every member keep the stock they already hold. It lets them keep buying more with the dividends. It exempts the presidency and the vice presidency. Half of Congress owns individual stock, and under this ban, half of Congress keeps it. Meanwhile the one retirement plan they manage on your behalf, the one you pay into with every paycheck, is set to fall short in 2032, 6 years from now, and to cut benefits by about 22 percent when it does. They have known for 30 years. They have not agreed on a repair. They have been more attentive to their own. They will hear the next briefing before you do. We can keep score of which party's list is longer. Or we can notice that both lists exist, and that the only person in this story who was told to hold was the one who could not afford to lose. He held. He was told that was the honest thing to do. It was.

Model Watch #1#: GPT-5.6 (Sol), for marketers We moved our whole team to GPT-5.6 Sol this week. Here's the 7-day verdict, and why it matters more to marketers than to engineers. 🧵 What Sol is? The short version: GPT-5.6 Sol (@OpenAI) finishes exactly what you spec. Give it a narrow instruction and it does that much, no detours. It's also cheaper than Fable and burns fewer tokens. Predictable means easy to trust and delegate. The one catch: hand it open-ended work and it over-reviews. Verifies before fixing, verifies after, then finds something else to inspect. The thoroughness is real, but the loop stalls actual progress. The fix is a workflow, not a prompt: • Analysis-only session first: "don't touch code, just report." • Split problems into parallel sessions • Fix sequentially, using each report as the spec Now the part we actually care about as an agency. Same shift, four marketing reads 👇 1/ Conversion comes from hands-on reviews, not spec sheets. What moved GPT-5.6 was "I used it for days" content (Lenny's, Every's Vibe Check). In KOL briefs and PR, lead with how someone's workflow changed, and let the score table sit in the appendix. 2/"Humans frame, AI executes" is your content workflow too. You own strategy, angle, tone. AI does the reps: variations, research synthesis, first drafts. Don't pile it into one session. Separate research, drafting, and polishing so it can't wander off. 3/Cheap tokens mean volume is cheap. Sol runs ~1/3 to 1/2 of Fable, output tokens down ~54%. Anyone can now pump channel variations and multilingual versions. So the differentiator moves back to the human-owned part: the angle and the insight. 4/A user-growth surge is a timing signal. Codex's single-day user growth after launch beat the prior two weeks combined. When attention floods a category, ride it: hands-on content, ambassadors, comparison reviews. "The model got better" is your best window. And build a stack, not a hero tool. We split Opus for UI, Sol for bugs. Do the same with your marketing tools: right tool per stage, humans connecting the seams.

If you want to stop impulse trading, a quick hack is to just go date people. I’m not joking. This actually works. (unless you’re married then just ignore this) I discovered this by accident during a phase where I was making absolutely dogshit trading decisions. Since then, “go date someone” has basically become an external part of my trading system. Because impulse trading isn’t really about charts or setups. It’s about getting trapped inside a sick mental tunnel against yourself. Your attention locks onto one anchor, usually the chart, and your emotions start looping. Greed, anxiety, hope, regret, all feeding each other. Once you’re in that state, using pure mental power like “discipline” or “strong willpower” to pull yourself out is almost impossible. It's like trying to tell yourself to stop thinking about a pink elephant. The more you try NOT to think about it, the more… you think of a pink elephant! I tried everything to break the cycle. Strict rules. Trading journals. Even stupid sticky notes on my desk screaming “DON’T DO IT”. Obviously, getting brutally liquidated multiple times did toughen my mentality. But that’s NOT something you can strategically repeat or rely on. It’s too destructive. Anything lighter, anything that doesn’t seriously fuck up your life, never worked consistently for me. Then something unexpected happened. A friend set me up on a blind date right in the middle of a trading day. I was pissed at first. I was still pulling out my phone every 10 minutes, checking charts like a maniac. Then she casually asked, “btw, are you into techno?” My brain just stopped. For the first time in weeks, I completely forgot about the charts. 3 hours straight. The dopamine hit from human connection completely overrode my trading obsession. Think about it like this. When you try to suppress trading urges (aka human nature), it's like pushing a beach ball underwater. It ALWAYS pops up with more force. So instead of trying to FIGHT human nature, you GO WITH IT. STOP trying to kill the desire. STOP trying to erase the energy. You REDIRECT the same energy to something else. JUST CHANGE THE TARGET. This isn't about willpower. It's about understanding that your brain needs something engaging to focus on. And faces are literally more engaging to our brains than charts could ever be. I started scheduling dates strategically during my most impulsive trading periods. My trading account literally grew more when I was actively dating because I made fewer emotional trades. The best part is you don't even need successful dates. Just the act of getting out and connecting with someone new (and someone you like😉) breaks that obsessive cycle. For married folks, maybe schedule intense social activities instead. Anything that FORCES you out of your trading bubble works. The truth is, we all know WHEN we're entering that dangerous trading mindset. We just IGNORE the warning signs. So next time you feel yourself getting sucked into chart-watching obsession, close the laptop and go on a date. Your portfolio will thank you. And hey, you might just find someone special in the process😉 Trading discipline through dating might sound ridiculous. But it's literally become an essential part of my trading system.

You paid $1,000 for a Samsung phone. Samsung pre-installed dozens of apps you never asked for. Facebook. Microsoft Office. Netflix. Samsung's own browser. Samsung's own email. Samsung's own calendar. Samsung's own notes. Samsung's own cloud. Samsung's own payment app. Samsung's own voice assistant. Duplicates of apps you already use. Running in the background. Eating your battery. Using your storage. You cannot delete them. The delete button is greyed out. You paid for the hardware. They control the software. Xiaomi is worse. Pre-installed games. Shopping apps. Some serve full-screen ads on your phone. Carriers add more. T-Mobile, Verizon, AT&T each pre-install apps you will never open. Uninstall button? Greyed out. Someone built a tool that removes every single one. No root needed. It's called Universal Android Debloater. Written in Rust. Cross-platform GUI. Plug your phone in. Click. Gone. → Remove any pre-installed app. Samsung, Xiaomi, OnePlus, Oppo, Vivo, Huawei, Motorola, Nokia. → Remove carrier bloatware. T-Mobile, Verizon, AT&T, and carriers worldwide. → No root required. → Restore anything you removed. One click. → Battery life improves immediately. → Storage freed. Gigabytes recovered. → Privacy improved. Fewer apps tracking you. → Community-maintained database of known bloatware. → Works on Windows, macOS, and Linux. Here's the wildest part: The phone you paid for is not yours. It is a billboard you carry in your pocket. The manufacturer sold you hardware and then sold your attention to their partners. This tool gives you YOUR phone back. GPL-3.0. Written in Rust. Community-maintained. But DO NOT use Universal Android Debloater. We should all keep running dozens of apps we never installed on the phone we already paid for.

This year, the EF is decreasing its budget by roughly 40%, which entails some difficult decisions. The goal of the decreases was set out in the Treasury Management Policy last year: the EF is transitioning into being a long-term-oriented endowment-based organization, shifting from its pre-2026 average of spending ~15% of its remaining funds each year, toward a post-2030 target of ~5% per year. Often, when an organization goes through something like this, people try to pretend that nothing of great value was lost, that it is an efficiency increase, that the only people cut are unproductive dead weight, and everyone else stopped partying, studied the blade, entered cracked S-tier beast mode, and this was sufficient to make up for the downside. I will not try to pretend this. I respect my EF colleagues far too much to pretend that there was not much that is lost. They are brilliant people. They are dedicated engineers of whom some have worked on the Ethereum protocol for nearly a decade. They have brought a bright light to the Ethereum ecosystem with their code, their words, their warmth as human beings and their actions. My dearest hope is that they find a path that brings them fulfillment and happiness whether inside Ethereum or outside. Hopefully many will be able to bring their excellent talents and mindset to the wider Ethereum ecosystem, or the even wider CROPS world. Instead, I will try to explain what *are* some of the grand sacrifices being made. The Ethereum Strawmap is no small thing. It is an extremely ambitious undertaking seeking to replace and augment almost every part of the protocol - consensus, proofs, privacy, account model, state, and more. This is the third iteration of Ethereum, in the same way that the Merge was the second, even if the shipping style is less Big Bang and more one-piece-at-a-time. On top of this, the EF is increasing its role in the Access Layer. We are not compromising on Ethereum being a Deeply Impressive protocol, something worthy of its place in a world with quantum computing, rockets to Mars and powerful biotech and AI, and capable of meeting the challenges that this era will bring. Some of the deficit will be recovered through more work happening outside the EF. But not all. So what are the grand sacrifices that will enable a leaner effort to accomplish all of this? I will give a few examples (though far from an exhaustive list): * The multi-client model will shift in the direction of multiple clients existing less for _redundancy_, and more for _specialization_. Up to this point, redundancy has been the main security strategy: if one client has a bug, if it has less than 33%, the chain keeps going and does not even stop finalizing. We are increasingly exploring moving more pieces of the protocol to a different security strategy: AI-assisted formal verification. Some smaller pieces of Ethereum (eg. BLS libraries) have worked this way already for a long time. But soon many more parts of Ethereum will likely function on this model. This may greatly reduce resource requirements of shipping a large number of EIPs. The resources saved by client teams can ideally instead be used to better serve different specialized user needs, including EF Access Layer goals. * PSE (Privacy and Scaling Explorations) is winding down as a unit. The number of people working on ZKPs for privacy and scaling is probably as high as ever, but they are working less on "exploration" and more on *implementing* ZKP-based privacy and scaling into the Protocol and Access Layer * Devcon will likely over time become smaller-scale, somewhat more spartan, much lower-deficit than previous years, in addition to other changes in vision in line with the Mandate. * Fewer beyond-Ethereum megaprojects coming from EF. As I announced earlier this year, I am taking on some of the responsibility of doing projects in this category that I consider valuable with my personal funds. * EF institutional work is reducing in scope, specializing more specifically on creating replicable test cases of highly CROPS-friendly deployments, even if at smaller scale. These do not explain all departures; in some cases they do not explain departures at all and rather explain _reduced need for new spending_. But they are a large part of the strategy at play. In the longer term, I personally favor a "soft lean-and-done" approach to Ethereum: once the Strawmap is completed, generally stick to security fixes and small high-value changes, and have a much higher bar for considering new feature additions to the protocol. This allows Ethereum to remain capture-resistant without demanding very large budgets. Learn less from multimillion-line-of-code behemoth projects, more from bitcoin. The past years have been a challenging era for Ethereum. However, the ecosystem is adapting, both inside the EF and outside, and I am confident that Ethereum is very well-positioned to succeed and thrive.