The thing I learned this year is that when engineers say they like working on “hard problems”, they actually don't. What they like is puzzle solving, and having a repertoire of patterns that they can pattern match onto traditionally hard problems, usually involving databases or something with scale, etc. And they know that the industry used to pay you a lot for how deep and broad this repertoire was. Unfortunately, in 2026, well, you have a cheat code machine that has infinite breadth and depth for pattern matching. So the question is, do you actually like hard problems? Because there are now hard problems that are a complection of engineering, product, society, culture, politics, and they are fairly intractable, probably unsolvable! Because if you do want to work on those actually hard problems, there is so much money that people will pay you for it. But you’ll have to face that truth about yourself first.
“Look at my incredible new factory!”
Yo that’s cool, what do you make?
“It’s highly optimised, fully automated, zero tolerance for defects and with a continuous feedback cycle”
Cool cool, so what do you actually make?
“I can interact with it on my phone, laptop, messenger, completely async, and the shared context means it’s always learning how to get better”
Very impressive, but what do you make?
“Every agent has full context, can spawn other agents, review their work, fix defects, and ship continuously.”
yes yes. WHAT DOES IT MAKE?
“Software.”
Oh nice. What software?
“Well right now we’re mostly using it to improve the factory.”
Improve it to make what?
“Anything!”
Such as?
“…a better factory.”
so will the model now have to optimize for generating the best output while also steering tokens to satisfy some statistical constraint for watermarking? probably not a big deal for normal writing, but what happens when you ask it for something like a regex or highly specific exploit payload where there’s barely any room to vary? wonder if this quietly makes the model dumber for certain tasks
غدًا، الساعة ٧ مساءً، نقيم فعالية مفتوحة للمجتمع التقني.
نأخذكم إلى كواليس رحلة @HudHudMaps ونشارككم ما تعلّمناه في الطريق، ونطلق منتجات جديدة لأول مرة.
الموعد في الكراج، بمدينة الملك عبدالعزيز للعلوم والتقنية. حيّا��م معنا.
please i'm begging you show me something you built
not another "this is my custom agent setup" post where you pretend you're doing something smarter than vanilla claude code
please
What’s funny is I’ll meet so many people in SF who’ll claim they are tokenmaxxing and have all of these subagents looping things for them..
But when I ask them “what” and for “whom” are they building, very few can give me a straight answer.
Shows that even in this insane AI era, simplicity and direction are still ridiculously important.
So before you let your tokens go brrr, take some time to think if what you’re building (for a living) is actually important.
Time is literally the only thing you don’t get back!
When we built the Dropbox storage system we had a set of production tests intentionally written by people who didn't write the storage code. If the same person writes the code and the tests it's easy to bake their bad assumptions into both.
If you're working on code that deserves review you should probably at least write the PR description yourself. That makes it clear you know what you wanted to achieve in relation to whatever was implemented.
تحية كبيرة للمنتخب المصري الشقيق على هذا الاداء الرائع في بطولة #كأس_العالم
مباريات كبيرة قدمها طوال مشواره في البطولة وروح قتالية عاليه من جميع اللاعبين
شرفتوا بلدكم وجماهيركم وشرفتوا العرب
شكراً لكم والقادم أجمل بإذن الله 🇪🇬❤️🇸🇦