J Mueller

I am putting in 80hr weeks myself because of Claude Code. I talk to it through my mic as we build.

A Hungarian psychologist raised three daughters to prove that any child could become a chess grandmaster through early specialization. He succeeded. Two of them became grandmasters. One became the greatest female chess player who ever lived. Then a sports scientist looked at the data and found something nobody wanted to hear. His name is David Epstein. The book is called "Range." The Polgar experiment is one of the most famous case studies in the history of deliberate practice. Laszlo Polgar wrote a book before his daughters were even born arguing that geniuses are made, not born. He homeschooled all three girls in chess from age four. By their teens, Susan, Sofia, and Judit were dominating tournaments against grown men. Judit became the youngest grandmaster in history at the time, breaking Bobby Fischer's record. The story became the gospel of early specialization. Pick a domain young, drill it hard, and you can manufacture excellence. Epstein opens his book by telling that story honestly and then quietly demolishing the conclusion most people drew from it. Chess works that way. Most things do not. Here is the distinction that took him four years of research to articulate, and that almost nobody who quotes the 10,000 hour rule has ever read. There are two kinds of environments in which humans develop expertise. Psychologists call them kind and wicked. A kind environment has clear rules, immediate feedback, and patterns that repeat reliably. Chess is the cleanest example. Every game ends with a winner and a loser. Every move is recorded. The board never changes shape. The pieces never invent new ways to move. A child who plays ten thousand games will see most of the patterns that exist in the game, and pattern recognition is exactly what chess mastery is built on. A wicked environment is the opposite. Feedback is delayed or misleading. Rules shift. The patterns that worked yesterday may be exactly the wrong patterns to apply tomorrow. Most of the real world looks like this. Medicine is wicked. Investing is wicked. Building a company is wicked. Scientific research is wicked. Almost every job that involves a complex changing system with humans in it is wicked. The Polgar sisters trained in the kindest environment any human can train in. Their success was real and the method was correct. The mistake was generalizing the method to fields where the underlying structure of the environment is completely different. Epstein's research is what made the implication impossible to ignore. He looked at the careers of elite athletes outside of chess and golf and found that the pattern was almost the inverse of what people assumed. The athletes who reached the very top of their sports were overwhelmingly people who had played multiple sports as children, specialized late, and often switched disciplines well into their teens. Roger Federer played squash, badminton, basketball, handball, tennis, table tennis, and soccer before tennis became his focus. The kids who specialized in tennis at age six and trained year-round for a decade mostly burned out, got injured, or topped out at lower levels of the sport. The same pattern showed up everywhere he looked outside of kind environments. Inventors with the most patents had worked in multiple unrelated fields before their breakthrough work. Comic book creators with the longest careers had drawn for the most different genres before settling. Scientists who won Nobel Prizes were dramatically more likely than their peers to be serious amateur musicians, painters, sculptors, or writers. The skill that mattered in wicked environments was not depth in one pattern. It was the ability to recognize when a pattern from one domain applied unexpectedly in another. That kind of thinking cannot be built by drilling a single subject. It can only be built by accumulating mental models from many subjects and learning to move between them. The deeper finding is the one that should change how you think about your own career. Specialists in wicked environments often get worse with experience, not better. Epstein cites studies of doctors, financial analysts, intelligence officers, and forecasters showing that years of experience in a narrow domain frequently produce more confident judgments without producing more accurate ones. The expert builds elaborate mental models that feel comprehensive and turn out to be increasingly disconnected from the actual structure of the problem. They stop noticing what does not fit their framework. They mistake fluency for understanding. Generalists do better in wicked domains for a reason that sounds almost mystical until you understand the mechanism. They have less invested in any single mental model, so they abandon broken models faster. They are used to being a beginner, so they are not threatened by the discomfort of not knowing. They have seen enough different domains that they can usually find an analogy from one field that unlocks a problem in another. The technical name for this is analogical thinking, and the research on it is one of the most underrated bodies of work in cognitive science. The single most useful sentence in the entire book is the one Epstein puts almost as a throwaway. Match quality matters more than head start. A person who tries six different fields in their twenties and finds the one that genuinely fits them will outperform a person who picked one field at fourteen and stuck to it on willpower alone. The lost years were not lost. They were the search process that produced the match. Every field they walked away from taught them something they later imported into the field they finally chose. The reason this is so hard to accept is cultural, not empirical. We tell children to pick a path early. We reward the prodigy who knew at six. We treat the late bloomer as someone who failed to launch on time, when the data suggests they were running an entirely different and often more effective optimization process underneath. The Polgar sisters were not wrong. The conclusion the world drew from them was. If your environment is genuinely kind, specialize early and drill hard. If it is wicked, and almost every interesting human problem is, then the people who win are the ones who refused to specialize until they had seen enough to know what was actually worth specializing in. You are not behind. You were running the right experiment all along.

@o_kwasniewski @nzmrldev Could it work on swift Mac Apps too?

@nzmrldev yes! we test both mobile and web apps

this is what AUTOMATED UI testing looks like

@ValKatayev Was that ringtones?

This is so good. When I was young, a more experienced person wanted me to be CEO. I said “are you sure it shouldn’t be you running the company? “ His answer was “Val, I’ll take a bet on you batting over 500 all day long”. The company made a $10m+ net profit in its first year of existence.

@mikefutia UGC

ChatGPT Images 2.0 + Seedance 2.0 is f*cking wild 🤯 I generated this 25-second UGC ad for Barebells in under 20 minutes: creator, script, scenes, finished cut. ChatGPT Images 2.0 generates the creator. Seedance 2.0 turns it into video. Perfect for DTC brands and agencies who want to test 20 UGC angles before paying $2K per creator video. If you're briefing creator agencies every week, waiting 7-10 days for one take of one variation, and paying $150–$300+ per UGC video that still misses the brand vibe... This workflow eliminates the entire loop: → Generate your creator in ChatGPT Images 2.0 → Save her as a Character Element in Seedance so her face stays locked across every scene → Save your product as a Prop Element with brand-accurate wrapper details → Write a 3-scene script in real UGC dialogue cadence → Fire each scene to Seedance 2.0 with both elements selected → Stitch in CapCut with auto-captions, no music, hard cuts only No creator briefs. No 7-day turnarounds. No $200/video platform fees. What you get: → A finished UGC ad in your brand's voice → Infinite variations of the same concept (test 10 hooks against one product in an afternoon) → A reusable creator and product Element library that scales across every ad → A repeatable workflow your team can run in 15-30 minutes I put together a full playbook with the 5-step system, every prompt template, the Seedance scene structure, and every common failure mode and how to fix it. Want it for free? > Like this post > Comment "UGC" And I'll send it over (must be following so I can DM)

This is right. I am pitting in 14hr days with Claude building. Zero chance it could do it on its own.

@JamesZmSun Can this work for Swift mac Apps too? Or just web?

Today, we launched browser use inside Codex to further close the build & verify loop for local development! Now, you can ask Codex to build your front end, and test it like a user would by clicking through the app. Codex sees everything a user sees through vision & checks the network/console logs to help debug & fix any issues that it finds. This change brings us closer to fully autonomous coding agents that delivers high quality and tested changes. Watch Codex test my app in the browser, catch & fix a real bug, and doing that loop again with a brand new feature.

"The evils of capitalism:"

Arrêtez de payer pour Claude IA. L'IA de Mc Donald's est gratuite et répond à toutes les questions, même si elles ne sont pas sur le BIG MAC. :-) De rien.

the best

Infinite money glitch? There’s a market on which day Trump will insult someone. Each day has resolved “Yes” so far. I bought $100 on each day for the rest of the month.

Today Perplexity shipped everything Siri was supposed to be 💻 Personal computer now has access to: → iMessage → Every folder on your Mac → 400+ connected apps → Apple Mail, Calendars, Browsers etc... Underneath, Claude Opus 4.7 is the brain. It breaks your goal into subtasks and routes each one to whichever of 20 models wins at it. GPT for long context. Gemini for deep research. Grok for speed. Nano Banana for images. Veo for video. Codex for code. It runs 24/7. You can trigger it from your phone. Pretty sweet design too

Ferrari has released a new video of the interior for its first ever all-electric car, called the Ferrari Luce. It was designed with Apple's former head of design, Jony Ive, who recently said "a large touchscreen doesn't work in a car." Car info: • Four-door four-seater • 122 kWh battery • 330 miles of range (European rating methods) • 1,000 horsepower • 0-60mph: Under 2.5s • Four electric motors • OLED screens • Guess cluster screen is made up of several layers. By cutting out holes in the upper layers, Ferrari created displays where the speedometer graphic is below the level of a physical needle, which is itself behind additional drive info and beneath a curved inset lens. • Will have fake gear shifts • Weight: 5,100 lbs

There was a time on this planet when great musicians created magic.

Este video explica a la perfección porque la equidad en los recursos, no garantiza la igualdad en las condiciones

US fertility reached 1.57 last year, the lowest ever recorded, and the WSJ explanation is "uncertainty about finances, relationship stability, and the political climate" my great grandma had eleven children during the second world war, in a country being bombed, in a house with no running water, on rations. poor people have always had kids. the poorest people on earth right now still have kids and the financial excuse is a story we tell ourselves because it makes us feel good and the real one is unbearable the real mechanism is that we got rich enough to redefine children as an expense instead of the point. somewhere in the last fifty years the cultural goal inverted and a child stopped being what life is for and became a line item competing with the lifestyle. once you frame it that way the math never works, because the math isnt supposed to work. that's the point we are living in the richest moment in human history and we decided to use the surplus to buy ourselves out of the future. the most prosperous civilization that has ever existed is committing demographic suicide at the altar of personal optimization and comfort, and the official line is that we cant afford it the birthrate is a lagging indicator of a civilization that forgot why it was alive

this is possibly THE MOST Australian interview ever

Time to start paying attention to your FDIC deposit amounts as AI is about to get really good at hacking.