I wanted to see how far AI could take a real product video — not just generate random clips. So I gave Pexo the product materials for Zen Slate, explained what I wanted, reviewed the direction, and refined it through conversation. It turned that into a complete 28-sec product video with real UI, motion graphics, voiceover, subtitles and music. What stood out to me: I didn't have to build the video piece by piece. I could just describe what needed to change and let the agent handle the production. Made with @Pexoai_offical pexo.ai #MadeWithPexo

I asked MiniMax Code to build an entire connected world from scratch. All I did was telling my idea. I put it to a creative world-building challenge: a dense forest, a central lake with an abandoned house, a flower-filled French village, and winding paths connecting everything into one cohesive visual experience. With its M3.1 Flash model, MiniMax Code really impressed me What stood out during the build: → Turning a detailed creative concept into a tangible result with an AI agent. → Bringing multiple locations and visual elements together in one connected world. → Exploring how AI can move beyond conversations and actively work on a computer. Performance matters, but so does cost. It focuses on making powerful agentic workflows more cost-effective: → 70% lower overall cost for agentic tasks compared to its predecessor. → API pricing of $0.15 per million input tokens and $0.60 per million output tokens. → Token efficiency that helps make complex, repeated workflows more economical. The goal isn’t just to build more with AI; it’s to get capable results efficiently and affordably. Want to try it yourself? M3.1 Flash open-source weights are out now. Existing MiniMax Code subscribers get unlimited M3.1 Flash usage through October 25, while new subscribers or M Plan upgrades receive 50% off their first month through October 31, subject to applicable terms. Explore MiniMax Code: agent.minimax.io/download

Elon Musk runs a 5-step first-principles algorithm for any problem: first, question and fix dumb requirements; second, delete any part or step you can (if you're not adding back 10%, you didn't cut enough); third, simplify and optimize what remains. Only then do you speed it up, and finally automate it. The order is critical : "the most common mistake of smart engineers is to optimize a thing that should not exist," so never optimize, accelerate, or automate something before trying to delete it. Watch this video fully to understand it more

Sam Altman (CEO of OpenAI): "You no longer need to write prompts." In just 38 minutes, he explains how to use ChatGPT at a level that most people can't even imagine. It's a talk he gave to Stanford students. A friend sent me the recording last night. After watching it, I realized I was only taking advantage of about 15% of what this tool can really do. Watch it in full and then read the guide I leave below on how to create a system that prompts itself.

GOOGLE HAS RELEASED SOMETHING NO ONE EXPECTED. An 8-minute tutorial on how to build your first AI agents.

best founders list to follow on X: @levelsio → GOAT @marclou → SaaS @tibo_maker → Serial Entrepreneurship @jackfriks → Micro apps @athcanft → iOS apps @wickedguro → Distribution Maxxing @robj3d3 → AI coding @llyism → SEO @DAIEvolutionHub → AI and Tech @gregisenberg → Startup Ideas @dannypostma → AI Apps @AlexFinn → AI @romanbuildsaas → Viral Growth Loops

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We've spent years asking AI to write code. Now, AI is helping build the models that write it. Recursive just introduced Flint, its first model built with help from the Eureka Machine. The system automates parts of AI research, from generating ideas to implementing and validating them. Flint is open-weight under Apache 2.0, with coding capabilities designed for local hardware. Less dependence on the cloud. More control for developers. This is what makes the next phase of AI so interesting.

Google just dropped a 1-hour course on agentic engineering from scratch: 00:00 – How to build your first AI agent 08:24 – Build agent memory (short, persistent, long) 28:34 – Agentic loops, long-running AI agents 40:04 – How to build MCP (MCP vs API) 1:00:22 – Multi-agentic systems This 1-hour watch will replace 10 paid agentic courses on the internet. Bookmark this. Watch this weekend.

GOOGLE CEO SUNDAR PICHAI: "IF YOU DON'T LEARN HOW TO ORCHESTRATE AGENTS NOW, YOU'LL SPEND 2027 CATCHING UP TO PEOPLE WHO STARTED TODAY." 30 minutes on why the best engineers stopped writing code line by line and started orchestrating agents instead. Most people think building an agent requires an engineering degree. It doesn't. It requires one guide and one afternoon. Watch the interview. Then read the article below. One guide. One afternoon. That's all it takes.

GOOGLE HAS RELEASED SOMETHING NO ONE EXPECTED. An 8-minute tutorial on how to build your first AI agents.

List of 15 best AI researchers on X: 1. @karpathy — Andrej Karpathy 2. @rasbt — Sebastian Raschka 3. @AndrewYNg — Andrew Ng 4. @drfeifei — Fei-Fei Li 5. @demishassabis — Demis Hassabis 6. @GaryMarcus — Gary Marcus 7. @DAIEvolutionHub — AI Explorer 8. @maximelabonne — Maxime Labonne 9. @chipro — Chip Huyen 10. @ilyasut — Ilya Sutskever 11. @thsottiaux — Thibault 'Tibo' Sottiaux 12. @bcherny — Boris Cherny 13. @geoffreyhinton — Geoffrey Hinton 14. @JeffDean — Jeff Dean 15. @fchollet — François Chollet

15 AI Research Voices on X @amaarora = AI papers explained through code. @cwolferesearch = Clear, in-depth LLM research breakdowns. @sedielem = Diffusion models explained deeply. @MaartenGr = Complex AI made visual. @seb_ruder = NLP and multilingual AI insights. @Tim_Dettmers = Quantization and efficient LLMs demystified. @arankomatsuzaki = Research papers distilled into takeaways. @srush_nlp = Transformers explained with hands-on code. @DAIEvolutionHub = New AI tools, peoples and ai commentary @rasbt = LLM research translated into practical code. @natolambert = RLHF and post-training unpacked. @eugeneyan = AI research meets real-world systems. @sh_reya = AI evaluation beyond benchmark scores. @Ham elHusain = Practical, no-nonsense AI evaluation. @ch402 = Neural networks decoded from within

Your next favorite app might not come from the App Store. It might be created by AI, exactly when you need it. Imagine planning trips, organizing fitness challenges, or coordinating with friends without jumping between a dozen apps. And doing it all together in a group chat. This is where things get interesting 👀

Professor Jiang breaks down how to actually win at life using game theory, In just 4 minutes

Best 15 accounts to follow in AI: @karpathy = LLMs king @steipete = built openclaw @gregisenberg = startup ideas king @rileybrown = vibecode king @jackfriks = solo apps king @levelsio = startups king @marclou = startups king @EXM7777 = AI ops + systems king @eptwts = AI money twitter king @DAIEvolutionHub = Latest AI tools @godofprompt = prompt king @vasuman = AI agents king @AmirMushich = AI ads king @0xROAS = AI UGCs king @egeberkina = AI images king Follow them all and learn.

Andrej Karpathy: "Prompting is going away. Delete everything, keep Graph." In just 69 minutes, he shows how to build graphs and why they're the only layer that survives in the end Prompts → Agents → Loops → Graphs a loop keeps one agent running until the job is done a graph decides which agents exist and what each one passes to the next anyone can build an agent, almost nobody builds the graph that runs them watch it today, then save the full guide on graphs below before everyone starts catching up ↓