Smart AI for You

I've been quietly building something. 50 AI prompts that replace 4+ hours of copywriting work every day. Sales pages. Cold email. Ad copy. Objection handling. Full funnels. Every prompt has 3 skill levels + what you can charge using it. Free. No catch. promptbible.gumroad.com/l/CopywritingP…

@Prathkum Debugging AI code is just rereading your own prompt and realizing you were wrong the whole time.

AI rarely writes bad code randomly. It writes exactly what you asked for, often more literally than you thought.

@PeterDiamandis The plumber is safer than the lawyer right now. That's going to take a long time for education systems to process.

For years, we were told that robots would take blue-collar jobs first. Instead, AI came for office work and other creative jobs first.

@BrownCoyoteStu Fair. But the market decides, not philosophy. Bad books don't sell. That part isn't subjective.

I think the capacity for people to read bad books is just as viable as good books; good/bad is very subjective.

@mark_k The real tell: if you need AI to summarize what you just AI-generated, the original thought was a tweet all along.

There's this saying: "This book should have been a tweet!" The same is true for many articles here on 𝕏. They should have been a post instead… People use AI to inflate a nugget of information into an article, and now we need AI to compress it back. 🫠

@LuizaJarovsky Nobody wants to read bad books. AI-generated is just a new way to make them.

Nobody wants to read AI-generated books.

@r0ck3t23 Jensen just made token spend a performance metric. HR departments aren't ready for that conversation.

Jensen Huang just gave every CEO on the planet a single number to judge their engineering team by. Not lines of code. Not features shipped. Dollars burned in compute. Huang: “If that $500,000 engineer did not consume at least $250,000 worth of tokens, I am going to be deeply alarmed. And this is no different than one of our chip designers who says, ‘Guess what? I’m just gonna use paper and pencil. I don’t think I’m gonna need any CAD tools.’” Half a million dollars in salary. Five thousand dollars in token spend. That ratio should be keeping every hiring manager awake tonight. It means your most expensive engineer is solving problems by hand that a machine could close in seconds. You are paying Formula 1 money for someone pedaling a bicycle. Huang is not suggesting engineers use more AI. He is saying if they are not consuming massive volumes of inference, your organization has a structural failure it has not diagnosed yet. And if you are the engineer in that seat right now, the math is staring directly at you. Your value is no longer measured by what you can build alone. It is measured by how much machine output you can direct, evaluate, and multiply. The ones who refuse to let go of the keyboard are pricing themselves out of the conversation. Calacanis pushed him on what this looks like two or three years out. Huang didn’t give a forecast. He eliminated three assumptions the entire industry still plans around. Huang: “‘Wow, this is too hard,’ that thought is gone. ‘This is gonna take a long time,’ that thought is gone. ‘We’re gonna need a lot of people,’ that thought is gone.” Too hard. Gone. Too long. Gone. Too many people. Gone. Every planning conversation in every boardroom in the world is built on at least one of those three constraints. Huang just declared all three obsolete. Huang: “This is no different than in the last Industrial Revolution somebody goes, ‘Boy, that building really looks heavy.’ Nobody says that. Everything that’s too big, too heavy, takes too long, those ideas are all gone. You’re reduced to creativity.” The Industrial Revolution made it absurd to say an object was too heavy to move. This moment makes it absurd to say a problem is too complex to build. Once you saturate your workforce with enough inference, the only bottleneck left is the quality of the idea itself. Not the team size. Not the timeline. Not the technical difficulty. The idea. That is all that is left. Huang: “In the past, we code. In the future, we’re gonna write ideas, architectures, specifications. We’re gonna organize teams. We’re gonna define how to evaluate the definition of good versus bad. And I think that every engineer is gonna have a hundred agents.” The engineer of the next decade does not write code. They write intent. They define what good looks like. They architect the problem. They evaluate the output. They direct a hundred agents executing in parallel across every layer of the stack. The companies still hiring engineers to manually write syntax are staffing a typing pool in the age of the printing press. The engineer’s job is no longer to build. It is to command.

@Govindtwtt Same question was asked when ATMs replaced bank tellers. Teller jobs actually increased for a decade after. Then dropped. The lag hides the damage until it's too late to prepare.

Everyone says “AI will take all the jobs.” If that happens… how does this future actually work? No jobs → no income → no spending. So who buys things? Who pays rent? Who keeps the economy moving? What am I missing here?

@VraserX It's not "AI took my job." It's "Dave used AI and made 8 of us look unnecessary." That's a much harder problem to fight.

The real danger to many white collar jobs is not full replacement. It is when one cracked person with AI suddenly performs like a whole team and the CFO notices.

@mark_k The algorithm rewarding brevity and AI making it easier to write long things is a funny collision. The platform is pulling in the exact opposite direction of the tools.

I've lately noticed that the X algorithm now favors short posts more. Which is good because I like brevity. 😏

@aliByteCode Reality of the hour

Hot take: Marketing your product is harder than building it. Change my mind.

@mark_k "Glacial speed" is a choice at this point. The tools exist. The bottleneck is process, not capability.

I'm a fan of rapid application development. Nothing disappoints me more than when an app moves at a glacial speed. Every update should feel like a substantial upgrade!

@godofprompt The model is no longer the bottleneck. You are.

With the right skill claude can fking do anything now

@VraserX Every wave has a softening word. Offshoring had "efficiency." Automation had "productivity." AI got "augment." The word changes. The dynamic doesn't.

People keep saying AI will “augment” workers. That word is doing criminal amounts of PR work right now.

@rohanpaul_ai ChatGPT + Codex + Atlas browser in one desktop app is OpenAI's answer to Claude Code. One agentic surface that can chat, code, and browse without switching contexts. The workflow war just got serious.

OpenAI is building a desktop super app that merges ChatGPT, its AI browser, and the Codex coding tool into one place. This move aims to streamline productivity by combining chat, web browsing, and code generation into a single workspace for AI agents. Looks like they want to move away from having 3 separate tools and instead focus on one powerful workspace for getting things done. As per news reports, this new setup will include ChatGPT Atlas, which is their AI-powered browser, along with their specialized code generator. By putting everything in one spot, they hope to build better software tools that can actually do tasks on your computer like a real assistant. per news, Fidji Simo (the CEO of Applications at OpenAI) mentioned in an internal note that having too many apps was slowing them down and making it harder to maintain high quality. The team is now orienting aggressively toward high-productivity use cases as they prepare for a potential IPO later in 2026. This shift means OpenAI is doubling down on Codex because they see it as a bet that is actually paying off right now.

@mark_k Fidji Simo's internal memo said fragmentation was "slowing them down and making it harder to hit the quality bar." A superapp announcement is also a quiet admission that the last 12 months of product launches were a mistake.

OpenAI is working on a "mega app", merging the Codex desktop app with ChatGPT and its web browser.

@mark_k @GoogleAI Which is why the chip geopolitics story matters more than any model release. You can train a better model in 6 months. You can't build a new fab in under 5 years. The real AI race is being decided in Taiwan right now.

@SmartAIForYou @GoogleAI The problem is getting enough tpus built.

Google should build its own chip fab, just like Tesla does with the Terafab. Although @GoogleAI is usually seen as extremely rich, due to some mishaps it is currently short of enough TPUs and GPUs to meet its enormous AI inference demand. Hence the severe usage limits in Gemini.

@slow_developer This tracks. OpenAI literally designed GPT-5.4 mini for subagent workflows inside Codex - fast, cheap, parallel. For spatial reasoning and complex coding, the full GPT-5.4 handles planning. Mini executes. Wrong tool, wrong test.

gpt-5.4-mini with high reasoning is not good for coding, especially anything that needs spatial reasoning, like 3d geometry, and it wasn't close to gemini 3 flash, and costs more too i think its big advantage is speed. for agentic tasks, it's much faster than gemini 3 flash

@WesRoth Every platform promises algorithmic transparency. X is the only one actually shipping the code. Whether you trust Elon or not - that's a real differentiator.

X is set to release a significant update to its AI-driven recommendation algorithm next week, and in keeping with the platform's recent shift toward transparency, the updated code will be simultaneously open-sourced to the public.

@WesRoth The interesting part isn't open source - it's that Grok now does ALL the ranking with zero manual feature engineering. No human adjustments. Pure AI deciding what you see. That's either the most transparent feed in history or the least.

@pmddomingos Worst venture bet in tech history accidentally became the best AI infrastructure play. Zuckerberg didn't pivot - he got bailed out by timing.

Luckily for Zuck, half the money he blew on VR was for compute he can use for AI.