rewind

🚨 Claude Code costs $200/month. GitHub Copilot costs $19/month. Jack Dorsey's company built a free alternative. 35,000 GitHub stars. It's called Goose. An open source AI agent built by Block that goes beyond code suggestions. It installs, executes, edits, and tests. With any LLM you choose. Not autocomplete. Not suggestions. A full autonomous agent that takes actions on your computer. No vendor lock-in. No monthly subscription. Bring your own model. Here's what Goose does: → Works with ANY LLM. Claude, GPT, Gemini, Llama, DeepSeek, Ollama. Your choice. → Reads and understands your entire codebase → Writes, edits, and refactors code across multiple files → Runs shell commands and installs dependencies → Executes and debugs your code automatically → Extensible through MCP. Connect it to any external tool. → Desktop app, CLI, and web interface. Pick your workflow. → Written in Rust. Fast. Lightweight. No bloat. Here's the wildest part: Block is a $40 billion company. They built Cash App, Square, and TIDAL. They use Goose internally. Then they open sourced the entire thing. This isn't a side project from a random developer. This is production-grade tooling from a company that processes billions in payments. Built for their own engineers. Given to everyone. Claude Code: $200/month. Locked to Claude. GitHub Copilot: $19/month. Locked to GitHub. Cursor: $20/month. Locked to their editor. Goose: Free. Any LLM. Any editor. Any workflow. Forever. 35.3K GitHub stars. 3.3K forks. 4,078 commits. Built by Block. 100% Open Source. Apache 2.0 License.

POV: Life after I stopped spending $649 a month

POV: you now know more than 99% of Claude Code users

Life after mastering claude cowork:

Started building my first mobile app MVP from scratch coding skills = ~0, background is in marketing and content creation, so this is something new in ~7 hours i managed to: -> set up the app structure -> build the onboarding flow -> implement the core functionality -> connect backend and database -> fix around 10-20 bugs stack i'm using: Claude for structuring and thinking things through + Cursor for implementation when Claude hits usage limits, i switch to ChatGPT to fix simple bugs, also planning to improve the design with Framer spent around ~5 hours coming up with the idea, validating it, and talking to people who'd actually be interested i get that a full version of the app will take about a week, the world's not gonna be the same after that with my background in content on X, i can see this is the best time to pivot my career into building feels like we're in the prime era for solo builders who can create pretty much anything they imagine last year i generated ~50M+ high-quality impressions for my clients on X, time to do it for myself and my own products inspired by my friend @DeRonin_ who also started building his own products and already launched a beta for his fitness app it's never too late to start

🚨 the product was never the speaker > low price drives distribution > distribution drives data collection > data improves models > better models increase ad value > ad value funds more devices > the loop compounds hardware is the funnel, must-read👇

@realsigridjin @Fried_rice GOOD BRO!

@Fried_rice i backed the source up on my github github.com/instructkr/cla…

Claude code source code has been leaked via a map file in their npm registry! Code: …a8527898604c1bbb12468b1581d95e.r2.dev/src.zip

@Fried_rice x.com/rewind02/statu… LOL

🚨The same company that spent $8B building "the most safety-focused lab on earth"...

@Fried_rice @grok What are the consequences of this? And why did this happen?

@sharbel Wow, it'll be interesting to see all this

The fastest growing GitHub repos this month: 1. affaan-m/everything-claude-code (+65.1K stars) Skills, memory, security for Claude Code, Codex, Cursor 2. obra/superpowers (+61.3K stars) Agentic skills framework. Plug-and-play tools for AI agents. 3. 666ghj/MiroFish (+41.9K stars) Swarm intelligence engine that predicts anything 4. ruvnet/RuView (+37.1K stars) WiFi signals → real-time human pose detection. No cameras. 5. bytedance/deer-flow (+32.5K stars) ByteDance's open-source SuperAgent. Researches, codes, creates. 6. koala73/worldmonitor (+29.1K stars) Real-time global intelligence dashboard 7. shareAI-lab/learn-claude-code (+24.9K stars) Build a Claude Code clone from scratch. Bash is all you need. 8. shanraisshan/claude-code-best-practice (+19.9K stars) The best practices repo for building with Claude Code 9. moeru-ai/airi (+19.0K stars) Self-hosted AI companion with real-time voice chat 10. NousResearch/hermes-agent (+17.0K stars) The agent that grows with you The theme this month: agent harnesses took over GitHub. Bookmark this. April's list will look completely different.

@shannholmberg yeah

POV: you tested Helena, the "autonomous AI marketer" and generated a whole month of marketing slop in a minute

🚨One of the best videos i’ve seen recently, a must-watch for everyone:

@alphabatcher with full focus, the earning potential can be unreal

How to scale AI UGC system in 6 months ​ if you treat it like a full-time operation from day one ​ the scale you can reach in 6 months is genuinely insane ​ here's exactly what that looks like month by month 👇 ​ Month 1 - build one system that actually works ​ before you scale anything you need one thing that works ​ what you're doing full-time this month: ​ - pick one niche with a clear monetizable product (fitness app, finance app, productivity app) - create your first AI persona in Arcads using Nano Banana - build your first 3-5 video formats and test all of them - post 3-5x per day on one account - study every video's performance obsessively - find the one hook format that consistently gets views ​ what you have by end of month 1: ​ - 1 account, 60-100 videos posted - 1-2 hook formats that clearly outperform everything else - a repeatable production process: hook → script → render → edit → post - first data on which content drives app downloads vs just views ​ the most important thing this month: do not scale until you have a format that works ​ scaling a broken system just gives you more broken content ​ Month 2 - systematize everything before you duplicate ​ now you make the first account run ​ what changes this month: ​ - build a hook library: 50-100 proven angles organized by awareness level - create script templates for each hook category - set up AI agent to generate new hook variations automatically - production time per video drops from 2 hours to 20-30 minutes - connect Arcads via API so renders trigger automatically from scripts - set up auto-posting via scheduling tool ​ what you have by end of month 2: ​ - 1 account posting 5x per day fully systematized - AI pipeline generating hooks and scripts without you - production requires 2-3 hours of review per day instead of active creation - 150-200 total videos posted - clear conversion data: which hooks turn views into downloads boring but everything that comes next depends on it ​ Month 3 - clone the system across 3 niches ​ now you duplicate the template ​ same process, new persona, new niche, new product ​ what you're doing this month: ​ - launch 2 new accounts in different niches using the same production system - each account gets its own AI persona built in Arcads - same hook library structure, different angle for each niche - AI agent now runs scripts for all 3 accounts simultaneously - take the best performing organic videos from account 1 and put them behind paid ads ​ what you have by end of month 3: ​ - 3 active accounts each posting 3-5x per day - combined monthly output: 270-450 videos - AI pipeline handles 80% of content creation automatically - paid ads running on validated organic creatives from account 1 - combined organic views: 1-3M per month - ROAS on paid: 2-3x ​ your job this month shifts from creator to operator ​ you're reviewing output, killing what doesn't work, doubling down on what does ​ Month 4 - the machine runs without you ​ this is where full automation kicks in ​ what the pipeline looks like at this point: ​ - AI agent (Open Claw or custom n8n workflow) monitors top performing videos - generates 50+ new hook angles per week based on what's working - writes full scripts structured for each awareness level - pushes scripts to Arcads API automatically - renders come back, you do a 1-hour review session daily - approved videos go to scheduler, post automatically across all accounts - paid ads manager pulls winning organics and scales them ​ what you have by end of month 4: ​ - 5 active accounts across 5 niches - combined output: 450-750 videos per month - 2-3 apps generating revenue simultaneously - time investment: 3-4 hours per day of oversight not creation - combined organic reach: 3-8M views per month - paid ads running on 10-15 validated creatives per account ​ total stack cost at this point: $500-800/month ​ what a human team producing this volume would cost: $20,000-40,000/month ​ Month 5 - add products, not just accounts ​ the distribution machine exists now ​ so you point it at more revenue streams ​ what changes: ​ - existing accounts start cross-promoting 2-3 products - launch a second app in the niche that's performing best - accounts in the same niche start cross-promoting each other - best performing AI persona gets licensed to an external brand for a campaign - start collecting winning creatives into a paid ads library ​ what you have by end of month 5: ​ - 6-8 active accounts - 3-4 apps generating revenue - organic reach: 5-12M views per month - paid ads scaling the best performing products - first licensing deal for one of your AI personas - system runs on 2-3 hours of daily oversight ​ Month 6 - this is what full scale looks like ​ the numbers if you executed the system full-time: ​ content output: ​ - 8-10 active AI influencer accounts - each posting 3-5x per day - combined monthly output: 800-1500 videos - combined organic reach: 8-20M views per month ​ the automated pipeline: ​ - Arcads - persona creation and video rendering - Nano Banana - hyperrealistic character generation - Character Swap - maps AI persona onto real motion footage - AI agent - hook generation, scripting, API triggers - Arcads API - automated render pipeline - scheduling tool - auto-posting across all accounts - paid ads manager - scaling organic winners ​ revenue streams running simultaneously: ​ - app sales from organic traffic - paid ads with 3-4x ROAS on validated creatives - brand deals and persona licensing - potentially: selling the system itself to other operators ​ total stack cost: $500-800/month ​ the real difference between month 1 and month 6: ​ month 1: you spend 8 hours making 3 videos ​ month 6: your system produces 50 videos while you spend 3 hours reviewing and optimizing ​ CONCLUSION: ​ this technology is now accessible to everyone. ​ there are countless ways to monetize it: ​ - Sponsored videos - Revenue-share collaborations - Ambassador programs - Selling content packages to projects - Platform monetization ​ the potential in 6 months: $4k-$30k in 12 months this space will be 10x more crowded and 10x harder to stand out in ​ the best time to start building the system was 6 months ago ​ the second best time is today

how to set up autoresearch with claude code 🧵

@IndianTechGuide @grok Who is “Agent Smith”?

🚨 Google employees are increasingly relying on an internal AI agent called "Agent Smith" to handle tasks like coding, even without using a laptop.

@NoLimitGains @grok How will all this change?

🚨 Per the Washington Post: The US military is preparing boots on the ground in Iran, a 2-month operation. Everything changes from here.

@EvanLuthra engagement science accelerating

🚨WHAT META JUST DROPPED IS MORE DANGEROUS THAN ANYTHING OPENAI HAS EVER BUILT!!!!! while everyone was losing their mind over Claude Mythos.. Meta dropped something that nobody noticed.. they built an AI called TRIBE v2.. it's basically a digital copy of your brain.. you show it a video, a sound, a sentence.. and it already knows how your brain is going to react.. 70,000 different parts of your brain.. blood flow, oxygen, everything.. they trained it on 1,000 hours of brain scans from 700 real people lying inside MRI machines.. it doesn't read your thoughts.. it does something worse.. it knows what's going to make you feel something before you even feel it.. think about that for a second.. if an AI already knows which image, which sound, which word is going to hit your dopamine.. you don't need to read someone's mind.. you just build the perfect trap.. and meta didn't even keep it locked up.. they open-sourced it.. gave the code, the weights, everything to the entire world.. this is the same company that got caught making instagram destroy teenage girls.. the same company whose own research said their algorithm pushes rage because rage keeps you scrolling.. that company now has a working copy of how your brain responds to everything you see and hear.. they don't have to guess what keeps you glued to the screen anymore.. they can rehearse it on a copy of your brain before you ever see it.. the product was never the app.. the product was always you.. now they have the blueprint.

@Hesamation compute is the new leverage

startups are spending more than $1000/day on claude code and codex. ai is now another pay-to-win game that favors the well-funded. and that gap will only widen when these companies decide to bump up their prices.