Experienced Frontend and Aspiring Full-Stack Developer. React.js | Typescript | Node.js | Express.js | MongoDB

Punjab, Pakistan
Joined February 2020
Focus on exploring your inner child!
27
1,744
56
14,110
174,336
Abdullah Sajjad retweeted
for folks looking at improving their technical skills I rarely seen someone in the tech education put as much effort as my man moe is putting on deep-ml highly recommend
Deep-Path: The entire Deep-ML catalog, organized into one structured learning path featuring nearly 2,000 machine learning coding problems and hands-on projects. Throughout the path, you'll work through the math, implement concepts from scratch using minimal libraries like NumPy or CUDA, and build projects step by step There's also Deep-Path Essentials, a shorter version with 400 core problems and projects organized into 10 sections, covering the fundamentals of machine learning
6
68
1,468
50,394
Abdullah Sajjad retweeted
Many asked me how to make these, so I turned it into a skill~ Colorfigures: Describe an everyday object, and Claude draws it hand-inked and isometric, with buttons that actually work. You can also ask how something works and the skill will label the parts to explain how each part does its job. Free and open source 👇
Love this! If I had kids, I’d love to teach them this way. I’ve been exploring learning through play too! A Claude skill for making hand-drawn, interactive everyday objects. Here’s my little washing machine :) colorfigures.vercel.app
51
205
29
2,542
121,963
Abdullah Sajjad retweeted
Vibe coded my parents' TV this afternoon! It was showing a sponsored ad before you could even get to Netflix. Gave Claude Code the model number, it found the TV on wifi, removed 25 Xiaomi packages and wrote a new launcher. Looks like an Apple TV now lol
800
1,325
617
32,243
7,144,188
Abdullah Sajjad retweeted
Just checked this out and HOLY SHII where was it when I was learning these stuffs 😭😭
The evergreen resource - An Introduction to Distributed Systems by Kyle Kingsbury github.com/aphyr/distsys-cla…
1
40
827
46,824
Abdullah Sajjad retweeted
iPhone Duo… a whole new way to iPhone. Pre-orders start today.
1,155
1,696
314
28,476
1,584,559
Abdullah Sajjad retweeted
Six projects from the last few weeks that caught our attention: A wildfire analysis prototype that maps the fire’s spread over time and tracks hot spots, made with Opus 5.5.
632
2,290
310
34,421
2,074,293
Abdullah Sajjad retweeted
Cindy is one of the best distributed systems engineers I know, and resistant to any and all hype (also a great writer!) From her: "Claude (when given proper instructions, constraints, and context) now writes better code than me, almost always."
To create my claude.md, I had it read: - my favorite programming books + blogs - the best oss projects - the code of the engineers I respect the most Claude (when given proper instructions, constraints, and context) now writes better code than me, almost always.
75
181
9
4,218
234,650
Abdullah Sajjad retweeted
Pictionary, but with open source LLMs
52
64
13
1,360
57,482
Abdullah Sajjad retweeted
babe wake up, the text sizing guy is making weird things again
My dear friends, I’d like to show you my latest toy project Introducing Handwired: turn your regular JavaScript code into a neural net! - no training - exact outputs vs the JS program - fully differentiable All runnable in a browser, without GPU
16
46
1,513
62,252
Abdullah Sajjad retweeted
yall are too late for this
NOT EVEN THE PLAYSTATION 5 IS SAFE 🚨 Someone jailbroke a PS5 and got Qwen 3.8 27B running on its GPU at 20 tok/s. That's a real 27B AI model running locally on a games console. The same model on the PS5's CPU did about one token a minute. Meanwhile, DDR4 prices are up 24% in 3 months, AMD just raised GPU memory prices, and 5090s are basically gone. PS5 coming to a datacenter near you.
89
483
83
6,880
657,107
Abdullah Sajjad retweeted
Reverse engineered my IoT devices and vibe coded my whole apartment into the menu bar. Click a lamp in the 3D model, the real one turns on. ACs too. Why stop at one AC.
Reverse engineered my AC, and vibe coded a lil status bar app so I don't have to find the remote every time. No first world problem will remain unsolved in 2026.
163
342
56
6,628
371,217
Abdullah Sajjad retweeted
I have to admit, watched this a few times, especially to the end:) the creativity in the prompting and the model is awesome to see
Argon has this amazing natural understanding of the world. It can do so many things from first principles. Here's a pelican riding a bike, using fourier epicycles. Video made by Argon. Time-synced Lyria 3.5 music prompted by Argon.
315
537
41
9,200
938,521
Abdullah Sajjad retweeted
Argon has this amazing natural understanding of the world. It can do so many things from first principles. Here's a pelican riding a bike, using fourier epicycles. Video made by Argon. Time-synced Lyria 3.5 music prompted by Argon.
233
592
238
8,397
2,203,078
Abdullah Sajjad retweeted
Gemini 4 Argon is here. It’s available globally today for developers and enterprises in the paid tier of the Gemini API and the Gemini platform, for Ultra subscribers in Google Antigravity, and Ultra and Pro subscribers in the Gemini app and Search. Hope you all enjoy it!
1,547
2,481
1,212
28,470
5,928,341
Abdullah Sajjad retweeted
What if Spotlight actually understood the meaning inside your files? DigUp is an open-source macOS menu bar app powered by EmbeddingGemma 2 that brings 100% local, multimodal semantic search to your Mac. Instead of searching for file names, you can use natural language to: 📸 Find specific scenes in your photos ⏳ Jump to the exact timestamp in audio or video 💻 Search through your codebase by intent Everything runs locally in a single vector space.
187
655
262
9,783
845,802
Abdullah Sajjad retweeted
Introducing TrellisWM: The Fractal Window Manager for MacOS Its how the desktop should have always been. Download at TrellisWM.app
360
431
201
7,920
754,702
Abdullah Sajjad retweeted
Instead of .md specs, try this: make the system a state machine (or rather, a reducer). Ask your slopus to make an interactive diagram with real events from your flow and the real reducer. Step through them, asking the agent "whys" this and that.
38
98
14
1,887
112,410
Abdullah Sajjad retweeted
All of Sean’s blog posts are incredible, but this one’s a personal favorite
When you disagree with someone, there are two paths forward. The first is to try to engage with what they’re saying: what their reasons are, whether their position is true, what evidence could be brought to bear, and so on.
12
10
2
527
65,543
Abdullah Sajjad retweeted
Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel. - Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all. - Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract. - Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code. - And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while. The funnel is driven by a combination of factors: 1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel. 2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel. 3. Access. Free-tier, paid-tier, internal. So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.
Judging by my tl there is a growing gap in understanding of AI capability. The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code. But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along. So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions. TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.
2,111
5,829
2,231
43,490
6,657,062