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Three million people are now using Codex weekly – up from two million a little under a month ago. Incredible to see the growth. Thank you to all of you and to the ecosystem we’re part of. To celebrate, we’re resetting rate limits so you can keep building, and we’ll reset them every additional 1M users until we reach 10M, so we can keep celebrating along the way. Enjoy and thank you!
→ View original post on X — @ceobillionaire, 2026-04-07 23:13 UTC
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🚨AI Tools Directory Exclusive: Today, SureThing launches version 2.0—the world's first General AI Agency.
— Futurepedia – Learn to Leverage AI (@futurepedia_io) 7 avril 2026
Users discover skills they've craved for months but never mastered. Paste a link, and it transforms into a proactive employee with a real GUI dashboard and live memory.… pic.twitter.com/TiHGmUN4XJ
AI Tools Directory Exclusive: Today, SureThing launches version 2.0—the world's first General AI Agency. Users discover skills they've craved for months but never mastered. Paste a link, and it transforms into a proactive employee with a real GUI dashboard and live memory.
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I'm blown away at what ppl are using this for!!
— Farza 🇵🇰🇺🇸 (@FarzaTV) 7 avril 2026
I built it as a learning tool.
But people seem to really love using it as an AI interface that isn't chat that can work in their program of choice. Examples of usage so far:
– A Mom building her first app on Lovable
– A dentist… https://t.co/G9bnjEsLS1
I'm blown away at what ppl are using this for!! I built it as a learning tool. But people seem to really love using it as an AI interface that isn't chat that can work in their program of choice. Examples of usage so far: – A Mom building her first app on Lovable – A dentist debugging his OpenClaw setup – A photographer getting feedback in Lightroom – A person learning to animate SVGs in Framer – Founders keeping track of their todos. – Designers getting feedback in Figma – A student outlining her thesis in G-Docs – Traders analyzing live stock charts And A LOT of people using it to advise them on how to best reply to messages in Slack/Email. Super cool. The people yearn for a non-chat interface haha. Also, it's kinda crazy how as the founder you really don't know what the product is until you put it in the hands of users. The minute it's in the hands of others, it's theirs now! And that's really where you find out what it is. Farza 🇵🇰🇺🇸 (@FarzaTV) I built this thing called Clicky. It's an AI teacher that lives as a buddy next to your cursor. It can see your screen, talk to you, and even point at stuff, kinda like having a real teacher next to you. I've been using it the past few days to learn Davinci Resolve, 10/10. — https://nitter.net/FarzaTV/status/2041314633978659092#m
→ View original post on X — @scobleizer, 2026-04-07 22:08 UTC
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"NOTHING resets between sessions."
— Charly Wargnier (@DataChaz) 7 avril 2026
Anyone who's ever copy-pasted a 3,000-word prompt into ChatGPT for the 50th time just to remind it what app you're building knows exactly how MASSIVE this is!
Huge congrats to the @rocketdotnew team 🤘pic.twitter.com/JNyRX1274W https://t.co/JpxZ4fwXZY
"NOTHING resets between sessions." Anyone who's ever copy-pasted a 3,000-word prompt into ChatGPT for the 50th time just to remind it what app you're building knows exactly how MASSIVE this is! Huge congrats to the @rocketdotnew team 🤘 Vishal Virani (@Vishalvirani91) Rocket 1.0 is live. This is our first major step toward Vibe Solutioning. Vibe coding solved how to build. It never solved what to build, or why. That's the harder problem and the one where most products actually fail. @rocketdotnew connects the thinking and the building in one platform. Solve your hardest business question. Build from what you solved. Watch your competition while you work. Everything shares one context. Nothing resets between sessions. The video and blog explain it better than I can here. — https://nitter.net/Vishalvirani91/status/2041546557342855363#m
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Curious about vibe coding? Or are you already shipping apps and just want an easier way to explain your new favorite hobby to your friends, parents, grandparents, etc.?
— Google AI (@GoogleAI) 7 avril 2026
Either way, this video is for you ⏯️⤵️ pic.twitter.com/JWKqkFzOB0
Curious about vibe coding? Or are you already shipping apps and just want an easier way to explain your new favorite hobby to your friends, parents, grandparents, etc.? Either way, this video is for you
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"AI agents will replace teams" is the narrative right now. At Abacus AI, it's less about hype, more about wiring AI into your actual stack – Slack, Drive, CRM, warehouses – all in real time. That's when it stops being a demo and starts working like infrastructure. [Translated from EN to English]
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Vibe coding has been solving the wrong problem this whole time. Everyone optimized for how to build. Rocket is the first tool asking what to build and why, that framing shift changes everything.
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1.5 million users before the 1.0 launch even dropped.
— AI Highlight (@AIHighlight) 7 avril 2026
Rocket is not a coding tool, It is a full business thinking platform where you solve the problem first, then build directly from that solution.
That gap between thinking and building is where most products go to die. https://t.co/Sj8j8jk5Dj
1.5 million users before the 1.0 launch even dropped. Rocket is not a coding tool, It is a full business thinking platform where you solve the problem first, then build directly from that solution. That gap between thinking and building is where most products go to die. Vishal Virani (@Vishalvirani91) Rocket 1.0 is live. This is our first major step toward Vibe Solutioning. Vibe coding solved how to build. It never solved what to build, or why. That's the harder problem and the one where most products actually fail. @rocketdotnew connects the thinking and the building in one platform. Solve your hardest business question. Build from what you solved. Watch your competition while you work. Everything shares one context. Nothing resets between sessions. The video and blog explain it better than I can here. — https://nitter.net/Vishalvirani91/status/2041546557342855363#m
→ View original post on X — @aihighlight, 2026-04-07 21:18 UTC
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ICYMI here's more info about Andrej’s new method nitter.net/DataChaz/status/203996… Charly Wargnier (@DataChaz) 🚨 Karpathy’s new set-up is the ultimate self-improving second brain, and it takes zero manual editing 🤯 It acts as a living AI knowledge base that actually heals itself. Let me break it down. Instead of relying on complex RAG, the LLM pulls raw research directly into an @Obsidian Markdown wiki. It completely takes over: ✦ Index creation ✦ System linting ✦ Native Q&A routing The core process is beautifully simple: → You dump raw sources into a folder → The LLM auto-compiles an indexed .md wiki → You ask complex questions → It generates outputs (Marp slides, matplotlib plots) and files them back in The big-picture implication of this is just wild. When agents maintain their own memory layer, they don’t need massive, expensive context limits. They really just need two things: → Clean file organization → The ability to query their own indexes Forget stuffing everything into one giant prompt. This approach is way cheaper, highly scalable… and 100% inspectable! — https://nitter.net/DataChaz/status/2039963758790156555#m
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🚨 @karpathy literally ditched traditional RAG for an autonomous Obsidian file system. Instead of writing code, he dumps raw AI research into a local folder and lets an LLM convert it into an interconnected markdown wiki. He rarely edits the text manually. By relying purely on dynamically updated index files, the system navigates the exact context it needs natively without relying on flawed vector embeddings. Because the LLM fully understands the file structure, it executes advanced autonomous workflows: → Operates a custom vibe-coded local search engine → Renders complex charts and formatted markdown slides → Continuously compounds a 400,000-word knowledge base The most fascinating mechanic is the self-healing loop. He triggers background health checks where the LLM natively spots structural gaps, scrapes the internet for missing data, and cleans the articles perfectly. This feels the absolute blueprint for managing complex technical data 🔥 btw, he also plans to fine-tune a local model directly on the wiki so the research is baked into the neural weights rather than relying on limited context windows 👀