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Gothica is live on #Twitch#! 🔞🩸HAPPY WIGGLE WED - VR HEADSET IS HEREEE ⚰️TTS IS ON ♡ PARTNER PUSH ♡ Follow & Support ❤︎ !discord ✦ !gift ✦ !donate 🦇💀🖤🌙 #wigglewed# #vtuber# #vrchat# #gothmommy# #envtuber# #vr#

I explained the Chinese real estate & debt crisis in much detail in 2024 on my Substack. Nothing has changed since. China is in what we call "the largest balance-sheet recession the world has ever seen". And it will take years to get out of it and assuming the CCP's investment-led growth model does not dig the next hole in the meantime - a likely. The FT published added some colour to it two days ago: "Housing is important to every economy. But to China, it’s extra important. According to the PBoC, 96% of urban households own a home, and 41% own at least two. The average household owns 1.5 properties. And as such, property constitutes around 70% of China’s private wealth. The comparable figure for the US is around 30%. So when Chinese property prices fall, the authors make a pretty compelling case that this has all sorts of particularly bad economic spillovers. And fall they have. The negative wealth effect is substantial, and “effects are amplified by elevated household debt, much of which consists of mortgage obligations”. This — and the weaker income expectations that the falls generate — goes some way to suppressing consumption. Moreover, declining land-sale revenues constrain local government budgets, “limiting their capacity to finance developmental projects and maintain existing public infrastructure”. And this is even before any credit impacts from rising non-performing loans and mortgages on bank balance sheets are considered. Tl;dr: bad bad bad. Of course, China isn’t the first soon-to-be-global-economic-hegemon-East-Asian-power staring down demographic oblivion to have piled its savings into a property boom. Back in 1991, the world was fretting over the rise and rise of Japan. And the Japanese were buying Japanese residential real estate at outlandish prices. Japan’s house prices peaked back in 1991 and spent the next 30 years on a downward trajectory. We’re only a few years into the Chinese property bust, and its ultimate trajectory is both unknown and unknowable. But Rogoff and Yang have pulled together some cool data they kindly shared with Alphaville, allowing us to make this chart below. So far, it looks like prices in Chinese cities are falling at around the same pace as they did over the first five-to-10 years of Japan’s bust. Japan’s property crash is associated with a lost decade (or two) of economic growth. In the 10 years leading up to 1991, Japanese real annual GDP growth averaged 4.4%. In the subsequent 10 years it averaged only 0.9% per annum. The same numbers for China, with 2021 marking its property zenith, are 7.0% per year and 4.6% per year (so far). If the IMF’s forecasts turn out right, this latter number will fall to around 4.0% per annum. While the levels are different, the before-and-after drop looks comparable. Was it housing wot dun it? Rogoff and Yang reckon that a 40% decline in house prices translates into a total consumption loss of 2-4% of GDP. Not nothing, but not a single answer explaining life, the universe and wiggles in the decadal pace of real economic growth. To get here, they construct a historical dataset comprising subnational data across 47 prefectures, and input and output data at granular industry levels. They then use this to examine the macroeconomic implications of Japan’s real estate bust. And the authors argue that: a housing bust can generate substantial adverse effects on the economy via real channels. . . . overbuilding during the boom can trigger a demand-driven recession with limited reallocation and low output. Unlike financial channels, which amplify shocks through leverage, bank balance sheets, credit constraints, or fire sales, real channels operate directly through investment, consumption, labour markets, or productivity. In Japan’s case, the housing market collapse depressed activity through three key real channels: investment, consumption, and sentiment. This is all pretty intuitive. But using city-level and household-level Chinese data plus some whizzy maths, they put meat on the bone for these three channels. They find that Chinese cities that overbuilt housing the most are less keen on new building, suppressing investment. Sounds legit. Chinese household consumption is estimated to be more responsive to house price changes than it was in either Japan or the US given its outsized role in private wealth. And it looks to the authors like people have scrambled to rebuild precautionary savings they thought they had amassed in property. Understandable. Then, on the sentiment side, Rogoff and Yang use an LLM to gauge market perceptions of the housing market. And by incorporating city-specific perceptions, they double the estimated effect of house price changes on consumption. Huh. While China is not Japan, 1991 was not 2021, and a *lot* of other things are/were going on, it’s interesting to see that the overall magnitude and pace of property price falls — as well as the aggregate drop in the pace of headline GDP growth — has (so far) been spookily similar. And as for the big question — are we there yet? "If China’s adjustment unfolds in a similar way as Japan’s, it would mean China has not gone half way through the transition. By contrast, if China’s path is eventually comparable to the United States, it appears to have already covered roughly two-thirds of the adjustment before reaching the bottom." So more to come.

Same move. Same hand on the heart, same wave to the crowd. Musk did it and gets called a Nazi to this day. Mamdani does it and those same people have not said a word. Well, not exactly. Once the side by side clips went viral, some of them did speak up. Not to apologize to Musk. To defend Mamdani. Suddenly the gesture is not the gesture. Suddenly we need to talk about arm speed. Whether the fingers wiggled at the end. Whether he was smiling. Whether his grandparents were in the right party. A year ago none of that mattered. The hand went up, the verdict came down. Now we get a forensic seminar on millimeters and microseconds to prove Mamdani's arm moved slower. Mamdani's own press office said "in no way was this a Nazi salute." Funny. Musk said the same thing. His did not count. Mamdani's did, instantly. That tells you everything. The "Nazi salute" thing was never about the gesture. If it were, they would be screaming right now. They are not. It was about Musk. They hate him because he is the richest man in the world and he was attacking their ideological piggy bank with DOGE, so they smeared him. Mamdani is on their team, so he gets a pass, plus a defense team running stopwatch analysis. Same hand, opposite verdict. A wave is a wave. The rule does not change based on who is waving. When it does, you are not watching principle. You are watching a hit job.

Funny enough, this is already the third post in my Waza skill design series. Today’s one is about /think, the skill I use for solution design before writing code. I have two settings in Claude Code that I find especially useful. The first is /model opusplan, which means planning is done with Opus while execution runs on the regular Sonnet model. That helps me save Max usage for the places where it matters more. The second is that I usually run Claude Code with alias c="claude --dangerously-skip-permissions". I would not recommend that to less technical users. I use it because I know what it is doing, and mostly because I am lazy. Back to /think. How do you get the strongest model to produce better technical plans? It starts with the model itself. Models tend to avoid taking a position. I prefer engineers who can give a clear recommendation. So the first thing I do is require the model to have a point of view. It must state its recommendation, explain what evidence could overturn it, and avoid empty lines like “There are many ways to think about this.” Giving two or three options is fine, but it has to make a clear recommendation, and it must always include a minimal option. But a plan is not done just because it sounds good. The second step is to make it argue against itself. Under what conditions would this plan fail? If those problems can be fixed, the fixes should be folded back into the plan and the revised version presented again. If the plan breaks under certain conditions, it has to say exactly where and why it fails. That way, by the time the plan reaches you, the tradeoffs are already visible. I also go fairly deep on validating the premises before planning starts. First, it checks whether it is even looking at the right part of the codebase. I have seen models produce plans against the wrong path. Then it looks for older technical design docs to avoid reinventing work that already exists. After that, it searches GitHub to see whether similar problems have already been solved elsewhere. Only after those three steps does it start proposing solutions. That helps prevent the entire plan from being built on a bad assumption. There is also complexity grading. If the work touches more than eight files or introduces a new service, the plan must explicitly call out the scale. If data flows across more than three components, it has to draw an ASCII diagram and look for cycles. API keys and third-party dependencies also have to be listed during the planning phase, so you do not waste time or end up with a plan that depends on shaky assumptions. There is one more hard rule. The plan cannot contain things like TBD, TODO, “we can decide this later,” or vague phrases like “similar to step N.” That goes back to model behavior again. Once you leave that kind of escape hatch, execution tends to drift, skip work, or fill in the blanks poorly. I try not to leave the model any room to wiggle out of precision. The output format is also strict: what we are doing, what we are not doing, which option was chosen and why, three to five decision factors, and a clear list of unknowns. /think does not write code. Execution only starts after the user approves the plan. When I built this skill, I was really trying to capture how strong technical experts approach solution design: investigate first, form a clear recommendation, make decisions decisively, leave no loose ends, and improve the plan immediately when something invalidates it. If you have better ideas for planning and solution design, feel free to contribute to Waza.

🍰BrownDust2 | Wiggle's Birthday 🎉 It’s Wiggle’s birthday—the fun-loving skeleton who adores explosions! 🎉 『Wiggle, wiggle-wiggle. Wiggle-wiggle, wiiiigleeeeeee! Aaah! Everybody run away! Wiggle wants to express his birthday happiness with some “art.” What’s the problem, you ask? Wiggle’s idea of art is explosions!!!』 Today is Wiggle’s birthday. Isn’t it ridiculously adorable how he can’t contain his joy after being celebrated, and tries to express it with his own brand of “art”? Even though he doesn’t talk and his way of responding to your birthday wishes might be a little(?) dangerous, it just means your good vibes have made him so happy that even a skeleton could dance. So today, let’s wish Wiggle an explosively happy birthday! A friendly greeting—like “Happy birthday, Wiggle-wiggle!”—is all he needs to make his day brighter. #HappyBirthday# #Wiggle#

📅 BrownDust2 | April Birthday Calendar It’s time to celebrate our favorite characters with April birthdays! Share your best wishes and help us fill the month with joy, surprises, and unforgettable memories. Let’s make this April extra special together! 🎂🎉 #Wiggle# #Lucrezia# #Teresse# #Loen# #Yuri# #Rou#