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What's Trending on X about AI
Hot take: “One source of truth” is often the wrong goal for your team. Instead train an AI agent on ALL knowledge for instant answers.
Starting to think the real edge with AI is to build Non-AI focused products using AI Build what everyone is ignoring With God-mode speed/iteration/effectiveness
two worlds: world 1: "ai might replace jobs someday" world 2: running 20 ai coding agents in parallel, shipping to production daily, building in public...
After reading @FarzaTV's fantastic "build educational machines" blog, I was inspired to create a machine for mentorship https://t.co/fOZuBn8RXs the goal of this mentor AI is it lets you define the path, then build and prove your skills. framework is simple: the AI helps you structure your plan, guides you when you get stuck and reviews your output against professional standards...
This is huge for consumer AI. China just shipped an AI assistant that actually acts. Qwen isn’t a chatbot. It’s an action layer....
Repeat after me: LLM detectors don't work. AI image detectors are bound to fail. Despite what some companies claim, AI and non-AI data will eventually be indistinguishable
Knowledge graph for AI agents to reason about codebases github.com/Jakedismo/code…
New paper ‘Hindsight’ argues that the next leap for AI agents isn’t bigger context windows, but memory that cleanly separates world facts, lived experience, and evolving beliefs. And it beats full‑context GPT‑4o doing it. Paper: arxiv.org/html/2512.1281…
This paper turns expensive trial-and-error training into a quick prediction step, then runs only the best pick. Instead of running every idea, the agent first predicts which code will win, then verifies it once. Most machine learning agents follow a generate, execute, feedback loop, they write code, run training, then fix it, and each try can take hours....
I get really optimistic about the future of AI-assisted coding. And then I ask Github Co-Pilot to review my code. It successfully detected 15 out of 3 issues in my code.
They train people at OpenAI, Anthropic, Google, and Meta on AI evals (@HamelHusain and @sh_reya). Here's their complete process: 8:27 - Why everyone needs evals...
right now, AI mostly helps with math by saving experts time in a couple of years, it will seriously reshape math research — enough that "research mathematician" becomes a much smaller job a couple more years after that, and the same kind of shift hit a lot of other fields, too
AI agents never roll like this. That's why I love my team of AI agents! No ego, no tricks, just goal alignment and results 🔥
Raspberry Pi has a new AI HAT. This time with built-in 8 GB of RAM, so you can run machine vision + LLM inference all without touching the Pi's CPU. It's $130 and a little bit of a niche item. Find out why in my video: youtube.com/watch?v=jRQaur…
Saw another "Learn AI Prompting" course advertised yesterday. $997. "Future-proof your career." Bullshit....
We'll achieve Artificial General Coding Intelligence way before AGI. The reason is simple The quality of the generic data set is super low, and it isn't easy to filter/rank it. 99% of the content on the internet is "human slop," and AI is trained on it....
Study the trends. Study the predictions. Study the emerging threats. Study the new attack vectors. Study the evolving defenses....
Everyone is scrambling to figure out how to use AI for some vague "xyz" we can't even define yet 🤯 Meanwhile, AI companies keep dropping new models and capabilities like there's no tomorrow. Feels like it's raining hamburgers. Can we actually eat it all? 🍔
GEO people - AI is becoming crazy smart, agents can do everything Also GEO people - you need rigid structured data or you won't show in LLMs and LLMs won't know what you're about
"Just spent an hour debugging an AI model, only to discover it was a minor data input error. Shows up more than it should."
Most chatbots are just fancy FAQs: single-script, reactive, and stuck in first gear. True agentic AI takes action, learns, and drives real outcomes. Ready to upgrade from chat to autonomous? #AI #Automation #NAITIVE
AnimStats is growing into a powerful AI that makes multimedia content easy to create 😍
AI "agent" is a word everyone uses, but most people have no idea what it means. I wanted to bring clarity to the term, so I asked my engineers how they would define an agent. Here are the best responses I got: ...
Most people have no idea what an AI agent actually is. I wanted to bring clarity to the term, so I asked my engineers how they would define an agent. Here are the best responses I got: ...
I've never seen the medical tech landscape shift so dramatically in my residency. AI is literally rewriting how we diagnose and treat eye diseases. We aren't just practicing medicine anymore; we are coding the future of ophthalmology. - 23, 8th-year ophthalmology resident and...
Hybrid AI isn’t a compromise anymore. It’s the operating model. From Lenovo Tech World in Las Vegas, @PatrickMoorhead and @danielnewmanUV sit down with @Lenovo ISG CMO Flynn Maloy to discuss why real-world AI runs across on-prem, cloud, and edge, and how data gravity,...
Since launching our AI for Science program, we’ve been working with scientists to understand how AI is accelerating progress. We spoke with 3 labs where Claude is reshaping research—and starting to point towards novel scientific insights and discoveries. anthropic.com/news/accelerat…
Hot take that might ruffle some feathers. The "vibe coding" debate is missing the point entirely. People arguing about whether AI-assisted building is "real" coding are having the wrong conversation. The right question isn't "is this legitimate?" It's "what can I build with it?"...
OpenAI is not open. Anthropic doesn’t use humans to code. Thinking Machines has no thinking or machines....
Google isn’t winning the AI race because of hype. It’s winning because of data. Decades of search, video, email, documents, clicks, and behavior all flow through their systems. Every search trains their models. Every YouTube view adds context. Every Chrome session adds insight. Other AI companies have to buy or scrape data. Google already owns the pipes....
AI-Mania doesn’t just create artificial worlds. It artificializes the world. That’s a bigger problem than most people realize
AGI is not just a buzzword - it's about getting AI to automate ALL WORK The AI is already more intelligent than most humans when it comes to white-collar work All that is left to do is the application of AI to real-world problems
stop acting like the em-dash is proof of AI. it’s called grammar — people have been using it to great effect for hundreds of years. read a book for once
🦔 Microsoft is shutting down its employee library and canceling subscriptions to news services, business journals, and digital publications. The physical library is closing. Digital checkouts of business books are gone. Publishers that provided reports to Microsoft's 220,000 employees for decades are getting automated cancellation emails. The replacement? An "AI-powered learning experience." My Take This is a company telling its employees to get their information from AI instead of from journalists, researchers, and publishers who do original reporting. LLMs are trained on old data and can't tell you what's actually happening in the world right now. They're useful for synthesizing information you already have, not for understanding emerging trends or breaking developments....
AI automation workflows through prompts and a visual canvas github.com/AIGeniusInstit…
Anthropic Pavel Izmailov says AI won't make independent discoveries in the life sciences yet because it cannot run physical experiments But in mathematics, where models will likely master formal proofs and languages AI will soon become better than humans at proving technical lemmas
Most AI marketing content sounds the same because most people use the same prompts. Generic inputs = generic outputs
Coding teaches you logic. Prompting teaches you communication. Building AI products teaches you user psychology. ...
AI companies are burning millions on datasets. @PerceptronNTWK flips the script: a decentralized, human-powered data network that slashes costs, maintains quality, & rewards contributors. The future of affordable, transparent AI training data?...
AI can help speed up the process of stress-testing your product. Here’s one way teams are approaching it.
Building AI agents is the most lucrative skill you can learn right now. There's 100s of manual processes waiting to be automated. Takes 30-60 days to capture the opportunity.
One interesting problem I see with using AI blindly for finding out “new things” is how much it trusts mainstream opinion. Every devtool in the market puts themselves as the BEST. For example, without targeting anyone, say there is a ORM in the market named X, and there is another query builder called Y. Any AI trained on lots and lots of blog posts praising X will always recommend and use X directly. There would be probably two blog posts by someone really burned out by X and strongly suggesting Y, which LLMs will easily skip when making a decision....
One thing I keep experiencing with AI-assisted coding is that if you have _no idea_ what you're doing, and you're never stopping to try and roughly understand what's happening, your project will turn into a pile of slop one way or another. No matter how many skills you throw in,...
Built AssistBot to keep support running 24/7. AI handles the routine questions so your team doesn't burn out. When a real human is needed, they jump in with all the context-no scrambling for details...
“the best programmers are using AI already.” here is what a senior programmer who’s been coding for decades thinks about the future of programming:
Yes, AI can trade. that’s not the hardest part but humans still choose what to trade and how much risk to take...
I am actually surprised that AI has not already automated 90% of all white-collar labor By every traditional measure of intelligence, AGI is already here > AI can speak, read, and write 100+ languages...
Don't ignore data or fear automation. What quietly worked better: Effort in understanding AI....
Excited to share new research with the inimitable @ditong_96 and @LingfeiWu, just published in Nature Communications. Discussion of job loss (and creation) in our current era of AI emergence misses the larger impact of technology on job CHANGE. We constructed a neural-network-based "skill space" trained on the co-occurrence of skills demanded across a decade of U.S. job postings—167 million ads covering 721 occupations. The result is a precision telescope trained on the skill distribution of jobs across the American economy: distances in this space correlate with the burden of shifting skills, and the education required to move from one skill set to another, letting us measure both how job requirements change and how far workers must travel in skill space to adapt. What did we find? A recent high-profile study concluded that STEM and technology-intensive occupations face the most skill volatility. Our method, which accounts for the distances between skills, reveals the opposite. Lower-skilled occupations undergo far more radical skill transformations. A programmer learning a new coding language makes a smaller cognitive leap than a food production worker suddenly needing database skills....
The coding bottleneck is gone Solo builders with AI are hitting millions of users in weeks The new constraint? Product taste...
instead of trying to know everything about ai, create a roadmap that helps you grow: step 1: learn basics (landscape, models, prompt strategies). step 2: master one tool deeply + create mini workflows....
we're almost 40 years later... and we're back here again with AI in 1986, math teachers protested calculators because they thought kids would skip learning the basics and, that wasn't a crazy concern at the time....
BREAKING: A GenAI testing agent just dropped that writes end-to-end tests like a senior QA engineer instead of a basic script generator. It's called KaneAI, and it transforms natural language into production-ready test cases across ALL major frameworks as easy as conversing with your team! This is the future of autonomous AI....
even before AI helps us with vibe-code, paying attention to syntax and small details was already slowing software teams down AI just helps us overcome this ceiling
Most people are using AI wrong. Either outsourcing their brain to it. Or refusing to touch it like it’s poison....
Had the pleasure of speaking with @ahall_research’s class at Stanford yesterday It’s an AI class…run by AI! They use a notetaker and feed the transcript into four different LLMs to analyze Then, the “Chairman” (Claude 😂) gives a final ruling they discuss at the next class
I'm sorry, but most developers are sleeping on this. We're building AI assistants when we should be building AI operating systems. Think about it - an app that lives on your machine, syncs everywhere you work, and actually connects to the stuff that matters. Your repos, your docs, your company's internal mess of tools....
I definitely get why people don't like seeing vibe coding getting into real source code bases. AI can turn a good developer into a very proficient good developer. But it can turn a bad developer into a very proficient bad developer.
Started the AI Frontrunners course. They include .md files at the end of each lesson designed specifically as context for an AI assistant. You paste it into Claude and suddenly you have a tutor who actually knows what you just learned....
knowing how to debug is still a superpower AI needs directions, correct prompts and a humen who knows the big picture
We're introducing 𝚜𝚔𝚒𝚕𝚕𝚜 – the "npm" of AI skills. Excited to see an open, agent-agnostic ecosystem of skills flourish. To get started, try: ▲ ~/ npx skills i vercel-labs/agent-skills
The question of what we should do with AI is not a computer science problem; it is a sociological one. This is why the next phase of AI development cannot be led by technologists alone.
Once the AIs can go into desktop apps and have impeccable memory it will automate a great portion of work. This will not be reliable until we can get hallucinations near zero and have some form of continual learning though
AI models don't just degrade they completely break without diverse, real-time data. Famous fails: • Google Photos 2015: tagged Black people as “gorillas” (training data lacked diversity) ...
ai is making the coolest shit ive ever seen and also making the internet feel completely dead same technology, opposite feelings...
Am I one of the last people to NOT use AI? I learn by doing, and outsourcing that just seems like a miss
been coding with AI for months now and here's what nobody tells you: AI writes the code fast. but you still gotta: - figure out what people actually want - ship something (anything!)...
AI is like having a super fast typing assistant. not a business partner. seen too many devs (including me early on) think ChatGPT = instant startup success. it doesn't work like that 😅
leadership thinks AI will cut dev time in half sure, AI helps you code faster but coding was never the slow part...
Crazy idea: An AI which reads users feedback / bugs, directs it to your coding agent, and publish them automatically for the users who gave the feedback!
AI has opened a world of possibilities for many who didn't have the skills, knowledge, or time to invest in ideas. What motivates you to use AI to build, solve, etc? I'll answer below 👇
I have endless ideas, and I've done development, but I don't have to time to learn everything I would need to learn in order to bring my ideas to life. AI allows me to bring my ideas to life, and then I can put them out into the world and see if anyone else needs it.
I built an actual AI second brain Not a digital journal or some ChatGPT prompt Not a system I have to manually update...
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