#Programmer

#Programmer in training! Credit: @DrEugeniaCheng

How do you take your programming skills from the screen to the physical world? Robotics for Programmers by @a_bihlmaier explores building robotic systems, from automated assembly to environmental sensing. Watch the First Chapter Summary:

Algorithms — Free PDF (472 Pages!) Want to strengthen your problem-solving skills and become a better programmer? This 472-page Algorithms book is a great resource for anyone interested in understanding how algorithms work and how to solve computational problems efficiently. What you can learn: ✅ Algorithm design and problem-solving ✅ Time and space complexity ✅ Efficient approaches to computational problems ✅ A stronger foundation for Data Structures & Algorithms (DSA) ✅ Skills useful for coding interviews and competitive programming Perfect for Python developers, computer science students, software engineers, and aspiring programmers! Get the free PDF here:

Day 300/365 of GPU Programming Can't believe it's already been 300 days since I started this challenge... When I first started I had no what all these acronyms like PTX, TMA, SM, CTA, MMA, CLC, etc stand for, and now I feel like I have at least a somewhat broad overview of the topic at large. I'm still nowhere near expert level and there's so much more to learn but given this has been a fun part-time challenge I picked up as a side quest, I'm fairly happy about where I'm at in my learning journey. I've also had the opportunity to participate in a few kernel competitions (ranked in top 10 and 15 a couple of times), learn how to create an agent harness around kernels and study what the top kernel engineers do in those specific environments. At some point, I'd love to take time off and study GPUs full time. Maybe in 2027! I genuinely find the topic endlessly fascinating and the amount of unexplored territory/research seems to have no bounds (just look at what comes out of Hazy, Cursor, Together AI, Hao AI Lab, etc), so I'm excited to continue learning past the 365 days I originally committed to this journey. As a celebration of this small milestone, I'll spend some time today going through the past 300 days and reviewing materials & learnings I've picked up along the way. Also huge thanks to everyone who's shared resources and pointed me towards places I wouldn't have discovered on my own.

Day 299/365 of GPU Programming Submitted another attempt at the Muse kernel challenge today after being away from the desk the last few days. Made it into the top 50 cutoff (which get 8×H200 priority during phase 2 of the competition) but not sure I'll continue from here. I don't really have extra compute, so will probably just play around with the individual kernels for fun when I have time.

I built an absolute monster. My crazy idea to merge all the most powerful AI tools together made me $832 while I was asleep opus 5.5 + REA + Jev + Dots + Grok Bot + Obsidian Half a dozen utilities. A single unified ecosystem. Zero human intervention Opus 5.5 -> acts as the core intellect, designing every assignment Grok bot -> monitors X around the clock to spot emerging patterns REA -> conducts deep analysis on any subject within a four-minute window Jev -> executes concepts autonomously, turning them into reality Dots -> weaves all six components into a seamless workflow Obsidian -> functions as the archive containing 1,260 records with zero data loss Before heading to bed, I assigned it a single objective: discover a profitable market gap and launch a working product by sunrise, keeping the expenses under $15 I went to sleep at 11:40 PM, and here is what unfolded over the course of seven hours: 12:12 AM: Grok bot uncovers 1,900 distinct posts from delivery workers venting about a shared frustration: tracking their income across three separate platforms 1:05 AM: REA evaluates the competitive landscape, finding 14 existing paid solutions starting at $19 monthly, with users universally criticizing the exact same two software glitches 2:30 AM: Opus 5.5 drafts an application architecture designed to resolve both flaws, consisting of nine screens and a single database, without asking me a single question 4:10 AM: Jev programs the software, deploys it live, and writes the promotional landing page. 5:45 AM: Dots generates a 30-second promotional animation and publishes it alongside three forum threads 7:20 AM: Obsidian logs every single action, financial expense, and misstep along the way Upon waking up, I discovered a fully functioning application, 243 registrations, and 31 paying customers subscribed at $9 each, bringing in $832 before my morning meal The entire nightly overhead amounted to $5.10 for API tokens plus a $4 web domain, totaling $9.10 -> yielding a 91x return while I slept The system even exercised self-control: when Jev attempted to purchase a $55 web address, it hit the preset $15 threshold and automatically opted for a $4 alternative instead The primary misconception is that individuals turn to AI merely for answers: instead, I provided mine with a clear objective, a strict timeline, and a financial ceiling I did not author a single line of programming code, nor did I open a single browser tab: I simply went to sleep While everyone else is holding out for artificial general intelligence, I already have six autonomous utilities pulling the night shift

Oh my god... Majority of nodal interfaces are bad because they are designed by programmers who don't use or understand visual programming. We simply aren’t exploring this area properly, and we are tasking the wrong people to implement them. Dan is the right person. Wow!

okay, I did @ggsimm's wire-tie thing because that's the standard now right?

my first real chance to go down in history for a programming law

Teejs Law

“If you provide an API client that doesn’t include rate limiting, you don’t really have an API client. You’ve got an exception generator with a remote timer.” — Richard Schneeman

Anthropic CEO Answers the Question Everyone Cares About Most: Should You Still Learn Programming Now? 1. Programming will be the first to be eliminated. AI is already writing code, debugging errors, and building applications. The shift toward automating entire software engineering workflows is already underway. Learning to code just to secure your job may no longer be enough. 2. Even if you only do 5% of the work, it still has value. AI handles 95% of the work, and you handle the remaining 5%. Your productivity could increase dramatically. Knowing how to direct AI and make the right decisions is becoming more valuable than doing everything yourself. 3. The most promising careers are human-centered. Careers that combine human interaction, real-world expertise, and analytical thinking could have an advantage. Healthcare, robotics, and other fields that require judgment and human understanding are worth watching. 4. Critical thinking may be the most important skill in the next decade. AI can generate convincing answers, but convincing doesn't always mean correct. The ability to question information, verify facts, and make independent decisions will become increasingly valuable. 5. If you don't use AI well, it will make you dumber. Relying on AI for every answer without understanding the reasoning can weaken your ability to solve problems independently. The goal isn't just to get work done faster. It's to use AI while continuing to build your own skills. 6. He's bullish on semiconductors as capitalism's victory in the next decade. AI needs physical infrastructure to scale. Chips, computing power, energy, and advanced manufacturing could create major opportunities. The next wave of AI growth won't be limited to software.

🚨 SOMEONE LEAKED THE PROMPT THAT MAKES CLAUDE CODE CREATE ITS OWN SKILLS AND WORK BETTER EVERY DAY WITHOUT YOU TOUCHING ANYTHING No programming. Just paste. A single prompt does it all: Time needed: 2 minutes Actions: copy and paste into Claude Code The mistake 90% of people make with Claude: explaining the same thing to it every day. The same tone, the same steps, the same corrections. And the next day it starts from scratch again. → Detects what you repeat: reviews your project and asks you what tasks you do every week → Creates a skill for each one: instructions, templates, and examples that Claude loads only when it needs them → Tests them before giving them to you: runs each skill with a real case and fixes it if it fails → Learns from your corrections: every time you correct something, it updates the skill so it doesn't repeat the error → Zero code: you tell it what you do and Claude builds its own library of skills Before, this meant writing manuals, templates, and processes for weeks. Now it's just Ctrl+V. Save it before they delete it 🔖 Follow @tomcruise824458 for more...

Low-Level Design is dead. AI has made coding obsolete. No one cares about the programming language we use. What matters is engineering: making a system reliable, cheap, and scalable. In the past 3 months, I have worked on dozens of side projects and built custom frameworks for myself. I hadn't written code professionally since 2019, and yet I was blazing through projects in 2026. My system design fundamentals helped. My business fundamentals also helped. Coding didn't. I haven't written a single line myself. In 2026, code is all generated. If you are a software engineer, you must transition to AI now. All the best, my brethren.

Python Quiz: What is the Output? A) 5 B) 7 C) 8 D) 4

Learn Coding by playing games 1. Kubernetes 2. DevOps 3. Linux 4. Git 5. Python 6. CSS & HTML 7. Cybersecurity 8. Mobile Coding (like Duolingo) 9. For Complete Beginners 10. 25+ Programming Languages

The only programming language I'll be using in the next 2 years is probably Excel

Software Engineer V/S Product Designer #Programming #Coding #programmer #coder #code #CodeNewbies #AI #CodeNewbie #Java #Python #javascript #100DaysOfCode #MachineLearning #SoftwareEngineer

Best YouTube Playlists to learn Programming: C C++ Python Java C# SQL Go PHP Swift Kotlin Dart Ruby Rust TypeScript R React Next.js Node.js HTML/CSS Machine Learning Deep Learning DSA Follow @Arina_sharmi for more

Free eBook: Guide to Competitive Programming • Algorithm Design • Time Complexity • Sorting and Binary Search • Data Structures • Complete Search • Greedy Algorithm • Dynamic Programming • Graph Algorithms • Shortest Paths • Tree Algorithms • Range Queries • Bit Manipulation • Number Theory • Combinatorics • String Algorithms • Computational Geometry Antti Laaksonen’s guide explores how to design, implement, and test efficient algorithms for programming contests. From sorting and data structures to dynamic programming and graph algorithms, the material helps readers strengthen problem-solving, coding, and debugging skills. For readers who want to start with a free resource, the author’s Competitive Programmer’s Handbook provides an introduction to many of the same concepts with examples in C++. #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #Mathematics #DataScientist #Linux #Books #Programming #Coding #100DaysofCode Free Complete Book — Competitive Programmer’s Handbook: Amazon:

Anthropic CEO Answers the Question Everyone Cares About Most: Should You Still Learn Programming Now? 1. Programming will be the first to be eliminated. AI models are already doing this. Broader software engineering tasks will take a bit longer, but they're also receding. If you're learning programming just to keep your job, you're heading in the wrong direction. 2. Even if you only do 5% of the work, it still has value. AI does 95%, you do 5%, and your productivity can increase 20-fold. The power of comparative advantage is astonishing, even with huge gaps. 3. The most promising careers are human-centered. Jobs that combine interpersonal skills, the physical world, and analytical abilities. He cited radiologists as an example: doctors who understand patients and context, not just those who can read scans. 4. Critical thinking may be the most important skill in the next decade. When AI can generate anything, the ability to discern truth from falsehood becomes scarce and precious. You don't want to hold false beliefs or be deceived. This is his practical advice to 25-year-old young people. 5. If you don't use AI well, it will make you dumber. Anthropic has done related research. Depending on how you use the models, the decline in coding ability is measurable and real. The problem isn't the tool—it's misuse. 6. He's bullish on semiconductors as capitalism's victory in the next decade. The physical world, traditional engineering, direct AI dividends. Not software, but chips.

i'm a seriously good programmer. like actually really good at it. it's kind of crazy how good i am at programming. like sometimes i sit back in my chair in total disbelief. damn .

I'm not sure a lot of people understand what game coders actually do. We're not spending 9 hours a day finely hand crafting artisan software and expressing our inner dreams... 90% of the time we are fighting compilers and existing architecture, having to work out how undocumented code works, and tracking down obscure bugs and behavioural issues. Most of game programming is just difficult, tedious, laborious grunt work, and the cognitive load we have to endure to get anything done is tiring and frustrating. No game coder is doing it for this 90% of the job. We make games because the 10% that IS actually about making things fun and expressing ourselves is so incredibly rewarding it makes the other 90% bearable. Now imagine if there was a tool, some kind of AI agent maybe, which could do most of the 90% grunt work for you, leaving you to just make all the decisions and express your creativity. How amazing would that be. How completely revolutionary would that be.