Harris @HarrisDecodes

@MarcelVelica These 9 AI workflows are straight fire. Not just writing but full repeatable systems from idea to tracking. This is how you actually save hours every week. Saving this right now

@Tech5353 Great list

100+ AI Tools That Help You Get Hours of Work Done in Minutes ⏱️ 1. Presentation - Gamma AI - Decktopus - Beautiful AI - Slides AI - Designs AI 2. Ideas - Claude - ChatGPT - Bing Chat - Perplexity - Copilot 3. Website - Dora - 10Web - Framer - Unicorn - Style AI 4. Writing - Jasper - HIX AI - Longshot - Textblaze - Jenny AI 5. Meeting - Tldv - Krisp - Otter - Fathom - Noty AI 6. Chatbot - Droxy - Chatbase - Chatsimple - CustomGPT - Mutual Info 7. Automation - Make - Zapier - Xembly - Bardeen - Levity 8. UI/UX - Figma - UiMagic - Uizard - InstantAI - Photoshop 9. Image - Fotor - Leap AI - Midjourney - Stability AI - Microsoft Designer 10. Video - Klap - Opus - Eightify - InVideo - HeyGen 11. Design - Canva - Flair AI - Designify - Clipdrop - Magician Design 12. Prompts - FlowGPT - Alicent AI - PromptBox - Promptbase - Snack Prompt 13. Productivity - Notion - Merlin - Trello - Grammarly - TinyWow 14. Logo Generator - Looka - Brandmark - LogoMakr - Stockimg - Namecheap 15. Marketing - Pencil - Ai-Ads - AdCopy - Simplified - AdCreative 16. Twitter - Typefully - Tweetlify - Tapilo - Hypefury - TweetHunter

@Blum_OG This changes everything. No more turn-based coding hell. Article and video saved, trying the frontend verify trick today

@humzaakhalid Faceless YouTube system with Claude is straight fire. 2026 investment sorted. Saving the whole thing and starting my channel today

@jackcoder0 Chome auto browser will go very high

GEMINI CAN NOW CONTROL YOUR CHROME FOR YOU 🤯 Tell it what you need and it can handle the boring browser work: compare options, fill forms, shop, and help book things. You still approve the important steps. Here is what it can actually do 👇🏽👇🏽

Tokenmaxxing is a trap because the metric everyone's chasing is wrong. Highlight our research! 👇

Aiswarya Sankar @Aiswarya_Sankar

2 days ago

Tokenmaxxing is throwing money down the drain Analyzed 1M+ PRs over 2.4k companies and here are the stats: - 1 in every 4 lines is code churn - Only 21% of code review comments are addressed - at the 90% percentile, 76% of work is reactive bug fixes Full report below 👇

50 29 232 566K 119

@alphabatcher This harness reality check is brutal Context overload + no error feedback kills everything. Saving the full production checklist right now

@Blum_OG These 10 concepts are straight fire Most builders skip the basics and wonder why everything breaks. Tokens to agents explained perfectly. Saving this and learning in order

@jackcoder0 MIT just ended the whole context window game. No more cramming everything in memory, just teach AI to search and read like a human. This is the real fix we needed. Saving the paper right now

MIT just made every AI company's billion dollar bet look embarrassing. They solved AI memory. Not by building a bigger brain. By teaching it how to read. The paper dropped on December 31, 2025. Three MIT CSAIL researchers. One idea so obvious it hurts. And a result that makes five years of context window arms racing look like the wrong war entirely. Here is the problem nobody solved. Every AI model on the planet has a hard ceiling. A context window. The maximum amount of text it can hold in working memory at once. Cross that line and something ugly happens — something researchers have a clinical name for. Context rot. The more you pack into an AI's context, the worse it performs on everything already inside it. Facts blur. Information buried in the middle vanishes. The model does not become more capable as you feed it more. It becomes more confused. You give it your entire codebase and it forgets what it read three files ago. You hand it a 500-page legal document and it loses the clause from page 12 by the time it reaches page 400. So the industry built a workaround. RAG. Retrieval Augmented Generation. Chop the document into chunks. Store them in a database. Retrieve the relevant ones when needed. It was always a compromise dressed up as a solution. The retriever guesses which chunks matter before the AI has read anything. If it guesses wrong — and it does, constantly — the AI never sees the information it needed. The act of chunking destroys every relationship between distant paragraphs. The full picture gets shredded into fragments that the AI then tries to reassemble blindfolded. Two bad options. One broken industry. Three MIT researchers and a deadline of December 31st. Here is what they built. Stop putting the document in the AI's memory at all. That is the entire idea. That is the breakthrough. Store the document as a Python variable outside the AI's context window entirely. Tell the AI the variable exists and how big it is. Then get out of the way. When you ask a question, the AI does not try to remember anything. It behaves like a human expert dropped into a library with a computer. It writes code. It searches the document with regular expressions. It slices to the exact section it needs. It scans the structure. It navigates. It finds precisely what is relevant and pulls only that into its active window. Then it does something that makes this recursive. When the AI finds relevant material, it spawns smaller sub-AI instances to read and analyze those sections in parallel. Each one focused. Each one fast. Each one reporting back. The root AI synthesizes everything and produces an answer. No summarization. No deletion. No information loss. No decay. Every byte of the original document remains intact, accessible, and queryable for as long as you need it. Now here are the numbers. Standard frontier models on the hardest long-context reasoning benchmarks: scores near zero. Complete collapse. GPT-5 on a benchmark requiring it to track complex code history beyond 75,000 tokens — could not solve even 10% of problems. RLMs on the same benchmarks: solved them. Dramatically. Double-digit percentage gains over every alternative approach. Successfully handling inputs up to 10 million tokens — 100 times beyond a model's native context window. Cost per query: comparable to or cheaper than standard massive context calls. Read that again. One hundred times the context. Better answers. Same price. The timeline of the arms race makes this sting harder. GPT-3 in 2020: 4,000 tokens. GPT-4: 32,000. Claude 3: 200,000. Gemini: 1 million. Gemini 2: 2 million. Every generation, every company, billions of dollars spent, all betting on the same assumption. More context equals better performance. MIT just proved that assumption was wrong the entire time. Not slightly wrong. Fundamentally wrong. The entire premise of the last five years of context window research — that the solution to AI memory was a bigger window — was the wrong answer to the wrong question. The right question was never how much can you force an AI to hold in its head. It was whether you could teach an AI to know where to look. A human expert handed a 10,000-page archive does not read all 10,000 pages before answering your question. They navigate. They search. They find the relevant section, read it deeply, and synthesize the answer. RLMs are the first AI architecture that works the same way. The code is open source. On GitHub right now. Free. No license fees. No API costs. Drop it in as a replacement for your existing LLM API calls and your application does not even notice the difference — except that it suddenly works on inputs it used to fail on entirely. Prime Intellect — one of the leading AI research labs in the space — has already called RLMs a major research focus and described what comes next: teaching models to manage their own context through reinforcement learning, enabling agents to solve tasks spanning not hours, but weeks and months. The context window wars are over. MIT won them by walking away from the battlefield. Source: Zhang, Kraska, Khattab · MIT CSAIL · arXiv:2512.24601 Paper: arxiv.org/abs/2512.24601 GitHub: github.com/alexzhang13/rlm

You can earn $1,000–$5,000/ month with a faceless Instagram page But most people never get started because they think they need: ❌ A camera ❌ Thousands of followers ❌ Editing skills ❌ Hours of daily work The truth? AI can now do 80% of the heavy lifting. ChatGPT → Content ideas & scripts Claude → Research & planning ElevenLabs → Human-like voiceovers HeyGen → AI avatars & videos CapCut → Professional editing I've put together a complete guide showing how to: ✅ Find profitable faceless niches ✅ Create content without showing your face ✅ Grow from 0 followers ✅ Automate content creation with AI ✅ Monetize through affiliates, digital products & brand deals Giving this guide FREE to a few people who: Like this post Repost (RT) Comment "FACELESS" Follow me Good luck

Harris @HarrisDecodes

4 days ago

x.com/i/article/2061…

7 98 121 10K 54

@AuroraMar1eL Thought it was gonna flop on vague requests but it read my mind, gave recipes + perfect ingredients, no scrolling ever again. Intent shopping just won. Trying this tonight

i went in fully expecting this to be another ai gimmick. so i tried to trip it up. gave it a vague, lazy, half-formed request on purpose. it did not flinch:

@Marryclaire_AI The worst part was never the actual shopping, it was that endless mental list and the fear of forgetting something. GoPuff just deleted the whole deciding layer. Habits + one tweak = done. This is the future for real

the worst part of a grocery run was never paying. it was everything happening in my head before that. the running list of what i'm out of. what goes with what. the nagging feeling i'm forgetting something, which i always was. that quiet mental tax that hit every single time and that nobody ever names. Go in the @Gopuff just deletes the whole layer. it already knows my habits, the time of day, what i tend to buy. so it builds the cart, i tweak one or two things, and it's on the way. the exhausting part wasn't the shopping. it was the deciding. and the deciding is just gone. you don't realize how heavy it was until something carries it for you. crafted by @Gopuff with SpaceXAI gopuff.onelink.me/xTqd/ephwrq2k

keyboard_arrow_left Previous keyboard_arrow_right Next

@AITechEchoes This is 100% facts. 20 years of search-scroll-forget shopping and GoPuff just burned it all with one sentence. Intent shopping feels like the future already

the way we shop online hasn't changed in 20 years. search, scroll, add to cart, forget half of it. Go just torched the entire thing in one sentence.

@AiTechPerks @gopuff Never going back to scrolling again. Game changer stuff Perks