Karan Checker

Random Theory ⚫💻🌞🪐🎮 What if #blackholes are Matrioshka brains powered by Dyson Spheres? What if intelligent alien life we're searching for, have evolved into digital beings living on a supercomputer that needs all the power it can get? #simulationtheory #singularity

My biggest takeaways from @danshipper: 1. The future of work will happen inside Codex or Claude Code. Instead of putting AI into your SaaS tool, you’ll use your SaaS tools inside your favorite AI agents' in-app browser. Dan spends all his time in Codex now—writing documents, managing email, doing research, everything. He's using Google Docs, PostHog, and everything he needs within the agent's in-app browser. The agent can see what he’s doing, and has all of his context, so he and his agent collaborate quickly and super effectively. 2. Automation is a lie—every automation needs a human. Dan's company doubled in size this year despite being incredibly AI-forward. Why? Because in order to make automation work well, you need humans making sure everything keeps working. This is why benchmarks are misleading—they measure AI on problems we’ve already framed and can score, but there’s always a higher frame. 3. PMs will win the AI era. Marcus, a former PM who previously ran Axios’s writing product, joined Every after getting super AI-pilled. Now he runs their product Spiral, and ships faster than anyone on the team. He pairs technical knowledge with spiky product sense, deep user empathy, and an eye for what matters. Dan thinks any PM who gets really AI-native will be incredibly dangerous because the building is done for you—what matters is figuring out what to build and if it’s great. 4. Full-stack designers are becoming superheroes. Designers used to make beautiful interactions that engineers didn’t want to build or couldn’t execute properly. Now designers don’t need to hand things off; they can build it themselves. Designers are naturally creative people, and AI is the perfect tool for them because it lets them bring their vision to life without the traditional bottlenecks. 5. SaaS is not dead. In fact, Dan is bullish on SaaS stocks. When users bring their own AI (via Codex or Claude Code) to use SaaS products, the user—not the SaaS company—pays for tokens. This saves SaaS company’s margins. Since the agents need their own seats, Dan predicts that agents will create massive new demand for SaaS because there will be tons of agents using these products at high volume. 6. Every company will have one “super-agent” inside their Slack that every employee will use. Dan initially thought every employee would have their personal work agent, like a shadow AI org chart, but he’s completely flipped his view. He realized agents need humans who care about them. When someone gets tired of maintaining their personal agent, it becomes useless. The winning model is one forward-deployed engineer or AI-savvy person who maintains a company-wide agent (like Shopify’s River or Viktor), and then it trickles down to more specialized team agents as models improve and become less fiddly. 7. The AI job apocalypse is not happening, but you do need to evolve to stay relevant. Models make yesterday’s human competence cheap. But because everyone uses the same models, it all looks the same if you use it the default way; it becomes commoditized slop. Humans then take that frozen competence and use it to make something new and interesting for their specific situation. The key: “ride the models”—use them for everything you do, try new models when they drop, keep turning over rocks. 8. We will read way more AI-generated writing, and we will like it. Human writing is incredibly important for things that matter, but for internal docs, planning, and email, AI-generated is often better because most people are bad at writing strategy documents. 9. Build software for humans and agents to use together. The current model is building a CLI that an agent uses independently. Instead, you and your agent should be using the app together. This creates new design challenges—agents can make a billion requests in three seconds, so you need approval flows, inboxes that summarize what happened, logs, and easy rollback. 10. Forward-deployed engineers are the new most essential role. The big model companies have teams of people managing their internal agents, and those teams aren’t going away. It’s different from traditional software building, and certain engineers love it. As models get better, this role will evolve—you’ll be managing more agents doing more things.

Marc Andreessen just told a story that reframes who gets to build the future. Partners at a16z who have never written a line of code are now shipping software. Not experimenting. Not learning to program. Andreessen: “Ripping out software like crazy.” One partner built an entire AI system for everything he does at work. Vibecoded the whole thing. Andreessen asked if he’d even looked at the code. Andreessen: “Hell no.” Had he ever looked at any code. Andreessen: “Hell no.” No engineering background. No technical training. No interest in acquiring either. Hyper-productive anyway. Andreessen called them AI vampires. For sixty years we confused two completely different skills. The ability to code and the ability to build. We treated them as identical. Built entire hiring systems around it. Entire degree programs. Entire professional castes. If you couldn’t write the syntax you couldn’t ship the product. That was the rule. But coding was never the skill. It was the tax. The friction between what you could see in your head and what you could put into the world. The entire history of software is people with the deepest understanding of problems waiting on people with the right syntax to approximate their vision. Watching it come back wrong. Iterating for months. Settling for good enough. That tax just dropped to zero. The person with the problem and the person who solves it just collapsed into the same human being. A hospital admin who’s understood exactly what’s broken about intake for fifteen years doesn’t need a dev team anymore. She needs a weekend. An operations lead who’s been duct-taping the same workflow since 2015 can now rebuild it from scratch. The person closest to the problem just became the most dangerous builder in any room. Not because engineering stops mattering. Deep systems still need deep expertise. But the vast majority of software that should exist and doesn’t was never an engineering problem. It was a translation problem. The people who needed it couldn’t code. The people who could code never lived inside the problem long enough to build the right thing. That gap defined the industry for six decades. It no longer exists. Andreessen’s partner didn’t ship his system because he became a programmer. He shipped it because he’d spent years inside the problem. The code was irrelevant. The understanding was everything. We built an entire industry around filtering for the wrong skill. Not “do you understand this problem deeply enough to know what should exist.” Just “can you code.” The filter just broke. And sixty years of unsolved problems just met the people who were always supposed to fix them.

@jeantimex @ybouane @threejs This is fantastisch

Everyone is talking about HTML-in-Canvas, while I was porting @ybouane's liquid glass effect to WebGPU, I decided to make it work with @threejs and HTML-in-Canvas, and it works. Btw, that inner webpage is actually loaded in an iFrame :)

@0xGideonBature @gregpr07 github.com/deepseek-ai/De…

@kchecker @gregpr07 Please can you direct me to where they released the paper?

Where can I get deepseek v4 pro api that supports images?

@Dotmeray @ClancyStudiosIN @172gamedevs

he must be very upset

@Rainmaker1973 @grok what’s the timescale in this video

Small objects can show that gravity is real. The Cavendish experiment proved that even tiny masses pull on each other, showing gravity works everywhere, not just between planets.

We are making our discount permanent! 🎉 Enjoy building with DeepSeek-V4-Pro and bring your innovative ideas to life! 🚀

@r1cA18 It must need a desktop app though, right?

スマホでパソコンのマウス操作もキーボード入力も全部できるトラックパッド作った！！！

@icanvardar We're training loser AI to turn it into AGI

ever thought why ai is free exactly.

@blueemi99 BTW... Made a teleport app (free) inspired by you Check it out likethereinreal.com/teleport

ChatGPT Images 2.0 Make me a 360 image of Paris in 1920.

I assumed there was a graceful AI only solution to creating the 3d render from the floor plan. The paper clarified that it's a manual step. I looked up a bit more and found that @Planner5D offers an API method to convert 2d floor plans to 3d models (or renders) .. But I guess it's not a public API.

PanoWorld. An interesting way to use Qwen-Edit. It converts 2D floor plans into photorealistic, consistent VR home tours. Great for real estate and interior designers. It lets you walk through a home that hasn’t been built or furnished yet. Ensures seamless 360 views via CPRoPE jjrcn.github.io/PanoWorld-proj…

Wood is the rarest material in the universe.

@blueemi99 @bindureddy 💯

@bindureddy writing gemini? its opus 4.7

Best Model For The Use Case Front-end coding - Opus 4.7 Back-end coding - GPT 5.5 xHigh Visual understanding- Flash 3.5 Cheap - DeepSeek Flash Video - Seedance 2.0 Image - GPT Image-2.0 Voice - Flash Live Writing - Gemini 3.1 Pro Real Time - Grok 4.3

@wildmindai @grok so what’s different here? Thinking image model?

Microsoft finally releases the full weights for the Lens T2I 3.8B models (Lens/Turbo/Base). - uses FLUX.2 VAE + GPT-OSS - 1440x1440 - 4-step gen with Turbo Looks pretty interesting huggingface.co/microsoft/Lens

Product Tank Chandigarh @essennassoc @_aiaiooo

@trikcode Where would you see their C++ work? And they don’t come out boasting on X.

I haven't seen a C++ vibecoder yet. I wonder why?

@ShitpostReels What’s the rush?

Time to bring back our long shelved project. Who’s excited for Karan-Arjun.com ?

@brahma_4u But he couldn’t have built anything in India, as he’s built upon the innovation of others.

India trains the engineer. America files the patents. Gurtej Sandhu was raised in Amritsar and trained at IIT Delhi. He now holds 1,299 US patents at Micron, Edison topped out at 1,093. Sandhu is the 7th most prolific inventor in American history. His titanium nitride deposition work is why every DRAM cell in your phone and every GPU training a foundation model actually holds charge. Micron, Samsung, and SK Hynix own 95% of global DRAM. None of them are Indian. We export the inventor. We import the chip.