Matthew Anorkplim Loh

Built a Ghana Sign Language LMS leveraging Google MediaPipe for motion tracking, then internationalized it for any country's sign language. Planning to open source it, but what to do about data entry, the massively demanding task of creating course content; text, images, videos?

The ability to ask questions, to set aside the fear of judgment, to ask questions like we are some curious toddlers all over again is probably the greatest gift the developers of AI have handed humanity.

The ability now to tend to your app project like something you were baking in the oven is phenomenal. You set the instructions, then go do something else, then come back to turn it over or check how done it is. Sweet!

Software products change fast. Not necessarily the technology. WordPress is still written in PHP. VS code is still electron based

A quick @code tip you may not know: you can select bracket and string content with a simple double-click 🖱️

I have ADHD 2E, no medication, and a brain that refuses to sit still. After years of trying every productivity hack on the internet (twice), I built the tool I could not find. Here is what happened. x.com/iam_multiman/s…

@trondw @NotebookLM @GoogleLabs You gained a new follow. Nothing beats working at the very cutting edge of tech. Wish @NotebookLM was a thing in my early student years. Mind-blowing stuff

I have some news: I’ve started a new chapter helping lead product for @NotebookLM at @GoogleLabs NotebookLM is a genuine partner for research, learning, and project organization, built entirely from your own sources. That transparency is why I believe it’s a core pillar of Google’s AI future. My mission is to scale this product while ensuring our commitment to grounding and user trust remains our North Star. Huge thanks to @joshwoodward, @tokumin and the NLM team for the incredible foundation of trust. I’m excited to build in the open, stay close to your feedback, and continue building this with you. Let's get to work! 🚀

Imagine being lost in the woods, hearing this.

So I built something in @GoogleAIStudio. Here's the problem though; any time I asked the AI to review the codebase, it found something to fix or improve. Over 10 iterations, it still finds something to edit (largely bugs). I've lost count. Try that with your coding agent

Hot take: anyone who claims AI can clone any SaaS product has never actually cloned a SaaS product. At least not a closed source one.

@shub0414 The approach is not taken

Every idea feels taken. Every API already exists. Every SaaS has 12 competitors. So what do we even build now?

@zuess05 What do you mean Claude automates the logic problem? The fun part is identifying the problem and figuring out the best solution. At least for many engineers that's the real challenge. AI still doesn't do that very well. What it does well is automate the routine parts.

Genuine question. We got into software because solving complex logic problems was genuinely fun. Now Claude instantly solves the fun parts. If we accidentally automated the creative work and kept the garbage work... what exactly are we going to be doing all day?

The former director of AI at Tesla stood up at Y Combinator's AI Startup School in June 2025 and said something that made half the room of young developers realize they had been preparing for the wrong future. His name is Andrej Karpathy, and he is one of the only people alive who has been in the room for all three of the paradigm shifts that built modern AI. He was a founding member of OpenAI. He led the Autopilot team at Tesla. He designed and taught the first deep learning class at Stanford, which grew from 150 students in 2015 to 750 by 2017 and then escaped onto the internet where millions of people have watched it since. When he said something had fundamentally changed, the people in that room had every reason to listen. Here is the framework he walked through, and why it is the clearest map anyone has drawn of what just happened to software. He said there have now been three distinct eras of programming, and they are not replacements of each other. They are layers on top of each other, each one eating into the work that used to require the one below it. Software 1.0 is what almost everyone still means when they say code. A human being sits down, writes explicit step-by-step instructions in Python or C or JavaScript, and the computer does exactly what those instructions say. For seventy years, this was the only kind of software there was. Software 2.0 is the shift Karpathy himself named in a 2017 essay. He watched it happen in real time at Tesla. The team stopped writing explicit rules for how the car should recognize a stop sign and started showing a neural network millions of examples until it figured the pattern out on its own. The code was no longer the instructions. The code was the dataset and the network architecture, and the actual logic lived in the weights that came out of training. He wrote at the time that Software 2.0 was eating Software 1.0 one function at a time, and inside Tesla, he was watching hand-coded computer vision logic get deleted and replaced by learned weights week after week. Software 3.0 is the one that just arrived, and it is the one almost nobody has the right framework for yet. He said the line carefully. "The hottest new programming language is English." Not a metaphor. A literal statement about how software is now being built. You no longer need to write Python to produce behavior. You write a prompt in plain language, and a large language model executes the intent. The prompt is the program. The English is the source code. And the thing that makes this more than a productivity improvement is what he said next. Software 3.0 is eating Software 1.0 and Software 2.0 at the same time. Every traditional rule-based function that used to require a team of engineers can now be replaced by a prompt and a model call. Every narrow machine learning model that used to require millions of labeled examples can be replaced by a large model that was already trained on a significant fraction of the internet. The entire stack is being compressed upward into natural language. The implication he drew from this is the one that matters most for anyone trying to figure out what to build next. He said we are living through the single biggest expansion of accessibility in the history of computing. For seventy years, programming required learning a formal language that fewer than one percent of humans could ever become fluent in. In the span of about three years, the barrier has collapsed. The only language you need to program a computer now is the one you already speak. He used a phrase for this that sounded almost silly until you realize what it actually means. Vibe coding. The act of describing the program you want in loose natural language and letting the model handle the syntax, the structure, the boilerplate, and the integration. You do not need to know Swift to describe the iOS app you want to build. You describe the vibe, and the LLM handles the rest. But he was careful not to oversell it. He said LLMs are what he calls people spirits. Stochastic simulations of human reasoning with an emergent psychology and a set of very specific weaknesses that every builder now has to design around. They have jagged intelligence, meaning they can do astonishingly hard things and then fail at something a child could handle. They have anterograde amnesia, meaning they cannot form new long-term memory the way a human coworker would. They hallucinate. They get confused. They need supervision. Which means the job of a developer is not disappearing. It is changing shape. The best developers in the Software 3.0 era are not the ones who write the most code. They are the ones who can think in systems, design the right prompts, build the validation layers that catch the model when it drifts, and orchestrate an entire pipeline of specialized AI agents the way a conductor handles an orchestra. The specific line he kept coming back to is the one I keep thinking about. We are no longer just writing code. We are managing behavior. The people who will build the important things in the next decade are not the ones with the cleanest syntax. They are the ones who figured out, earlier than everyone else, that when English becomes a programming language, the bottleneck is no longer how well you can speak to the compiler. The bottleneck is how clearly you can think about what you actually want the machine to do. And that has always been the real skill. It is just that for seventy years, we had the luxury of hiding it behind the syntax.

The proof of AGI would be when an AI model writes code and all other frontier models find zero issues after a thorough review

claude —dangerously-skip-permissions

@rodydavis @SaiNemani1 @antigravity Can't find an auto-continue option for when AI models have capacity issues. It should stop completely only on quota exhaustion

@iam_multiman @SaiNemani1 @antigravity Do you have the antigravity settings adjusted correctly? Also there should be an auto continue option. Only model capacity errors will stop it completely

Honestly, I have been using @antigravity for quite a while now for some of my projects, and it's doing great. They have pretty good models, and generous limits imo. I don't see the real problem with it?

@mamagnus00 Is this integrated in browser-use MCP?

The simplest and most powerful thing we shipped: github.com/browser-use/br…

Your agent can record its own product demos now. Feels like watching it take a selfie. I asked it to demo, film & cut itself. With this flavor every agent becomes a magic horse🐎 and can do anything in the browser👇👇

This prompt or a variation may consume a lot of tokens... and may be quite frustrating but run it until there are no issues being reported in your codebase (which may be never 😅): "thoroughly review the whole codebase, to determine if there are any issues we missed"

@GoogleAIStudio The Figma killer. Well, I doubt it will kill Figma but if the AI proves to be capable of turning the architecture into code that works as the app is conceived to, we'll be welcoming a truly autonomous AI graphic designer.

What are you vibe coding this weekend?