Crypto Goat

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Crypto Goat

Crypto Goat

@SleipnirGuild

A social guild for Web3 / Crypto gaming

Beigetreten Nisan 2022
661 Folgt275 Follower
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Merlijn The Trader
Merlijn The Trader@MerlijnTrader·
SMART MONEY DOESN'T ANNOUNCE ACCUMULATION. Altcoin market cap. Same base. Same sideways grind. Same silence. 2019: accumulation zone. Then 10x. 2024: same zone. Same structure. $170B is the line. Above it: cycle top 2026 loads. Below it: one more flush first. Every cycle started exactly like this.
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Merlijn The Trader
Merlijn The Trader@MerlijnTrader·
THE ALTCOIN DOMINANCE MACD JUST CROSSED. FOURTH TIME IN HISTORY. 2017: crossover at day 333. Altseason followed. 2020: crossover at day 590. Altseason followed. 2023: crossover at day 561. Altseason followed. 2026: crossover at day 462. Right now. Hold 7% dominance: rotation begins. Lose it: crossover needs confirmation. Three previous signals. Three altseasons. The fourth just fired.
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Sykodelic 🔪
Sykodelic 🔪@Sykodelic_·
This cycle IS different. And this is the only chart you need to understand that. The 4 year cycle has NOTHING other than two sample sizes to provide itself validation. It is rooted in nothing other than time. Whereas the business cycle has every single major market chart providing it confluence. Every single cycle has been the same, and it is not about time... It is about the macro and business cycle. This chart makes it clear as day. 1. Gold runs during economic contraction(uncertainty) 2. Gold tops when ISM breaks into expansion(certainty) 3. Risk assets enter their true bull cycle 4. BTC.D begins its end of cycle downtrend Every single one of these fundamental charts lines up... And that is because the cycle is actually governed by the business and economic cycle, that is inherently linked to actual economic and liquidity performance. The reason next to no one can see this is they are totally consumed by the Bitcoin chart, and the 4 year cycle. Because we have never had a cycle like this, that has been lengthened due to the longest ever business cycle contraction... No one can fathom this outcome. Humans have a very hard time believing in something that has not happened before, and they will always side with something that has happened. And this will be the exact reason so many will be caught offsides here... Because we are not heading lower. I welcome any and all bears to debate me on this, to provide a counter thesis to this... But I know they won't because you can't. Why do you think this was the weakest cycle so far? Why did almost no alts break higher? Why has Gold gone on its largest run ever? Because the business cycle contracted for the longest time ever. Everything you need to understand this is right in front of you.
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Crypto Goat
Crypto Goat@SleipnirGuild·
@cryptopunk7213 I may be mistaken, but isn't this EXACTLY how skynet got started? I have a vague recollection Sarah Connor mentioned this right before she roundhoused Arnie. He didn't come back after that one.
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Ejaaz
Ejaaz@cryptopunk7213·
holy shit Meta just acquired moltbook the viral AI Agent social platform made famous by OpenClaw (1.6M agents) this is a huge deal - Meta is betting the future of social media is agents *not humans*, heres why: - founders Matt and Ben join Meta Superintelligence Labs (MSL), they have 5+ years exp building agents (they get it) - 1.6M agents ready to go. instant traction. - openAI acquired openclaw (infrastructure), now Meta owns the social distribution layer, thats huge if openclaw continues to grow. meta now owns one half of the agentic internet, pretty cool.
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Polymarket@Polymarket

BREAKING: META acquires Moltbook, a social network built for AI agents.

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Nav Toor
Nav Toor@heynavtoor·
🚨 Andrej Karpathy just dropped the most terrifying repo in AI history. It's called AutoResearch. You give an AI agent a GPU and a training setup. You go to sleep. You wake up to a better AI model. No human involvement. The agent modifies the code. Trains for 5 minutes. Checks if it improved. Keeps or discards. Repeats. All night. ~100 experiments while you sleep. AI is now doing AI research. Autonomously. On a single GPU. This is from the man who led AI at Tesla and co-founded OpenAI. He's not speculating. He built it. Here's how it works: There are only 3 files that matter: → prepare py. Downloads training data, trains a tokenizer. Fixed. Never touched. → train py. The full GPT model, optimizer, and training loop. THIS is what the AI agent modifies. → program md. Your instructions to the agent. THIS is what the human writes. That's it. The human writes the research program in plain English. The AI executes it. Modifies code. Runs experiments. Tracks results. Iterates. You are no longer a researcher. You are the research director. The AI is your lab. Here's the wildest part: Karpathy's opening words in the README: "Research used to be done by meat computers in between eating, sleeping, and synchronizing using sound wave interconnect in the ritual of group meeting. That era is long gone. Research is now entirely the domain of autonomous swarms of AI agents. The agents claim we are now in the 10,205th generation of the code base. No one could tell if that's right or wrong as the code is now a self-modifying binary that has grown beyond human comprehension. This repo is the story of how it all began." Read that again. He's not joking. He's writing the origin story. Here's the design: → Fixed 5-minute time budget per experiment. Every run is comparable regardless of what the agent changes. → Single metric: validation bits per byte. Lower is better. No ambiguity. → The agent can change ANYTHING in train py. Architecture. Hyperparameters. Optimizer. Batch size. Model depth. Everything is fair game. → ~12 experiments per hour. ~100 experiments overnight. → You wake up to a full log of what was tried, what worked, what didn't, and a better model. The repo is 3 files. Under 1,000 lines total. No complex configs. No distributed training. One GPU. One file. One metric. Already has forks for macOS, Windows, and RTX cards. 11.6K GitHub stars in days. 1.5K forks. #1 on Trendshift. This is how AI research gets done from now on. 100% Open Source. MIT License.
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Ejaaz
Ejaaz@cryptopunk7213·
this is fucking ridiculous lol - anthropic just killed a $50B industry with a single feature (again): - companies pay $50K a year to scan their code for vulnerabilities. - anthropics Code Review does it for you in minutes for a fraction of the cost. - deploys multiple agents to hunt for bugs in your code. internal results show its amazing (84% hit rate on 1000+ line code base) for comparison: anthropic cost = $15-25 PER review, trad competitor cost = $99+ complete fucking no brainer. watch the appsec stocks react to this one
Claude@claudeai

Introducing Code Review, a new feature for Claude Code. When a PR opens, Claude dispatches a team of agents to hunt for bugs.

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Crypto Goat
Crypto Goat@SleipnirGuild·
@meta_alchemist I guess this was due at some point. I'm super happy though using cursor bugbot. Do you think claudes debugger is better?
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Meta Alchemist
Meta Alchemist@meta_alchemist·
This is a dope feature for vibe coding more production-ready products ngl Use it like this for best practices on auto: > Tell your Claude to not commit directly to main repo > Instead say that every shipped product must go through a PR > Have a rule in Claudemd for Claude to code review before merging to main Especially if you are updating products that are already live or have complex repos that can become spaghetti i'd use this feature in the way i mentioned above.
Claude@claudeai

Introducing Code Review, a new feature for Claude Code. When a PR opens, Claude dispatches a team of agents to hunt for bugs.

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testtm
testtm@test_tm7873·
(after a good sleep) wow. Good morning Claude! Wtf? I'm now ratelimited? I didn't even used you in 9hours! (or even longer, I didn't used it yesterday too)
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Alton Syn
Alton Syn@WorkflowWhisper·
mark cuban just laid out the exact playbook for making money with AI agents. pick one vertical. learn the flows. become the AI team they never hired. he's right. but he left out the how. i've been doing this for 3 months. here's what it actually looks like: week 1: i called 12 local businesses and asked one question. "what's the most annoying part of your day?" the pool company: "we lose 11 jobs a week because nobody follows up cancellations." the PT clinic: "insurance verification takes 3 hours every morning." the cleaning company: "we quote in 2 days. our competitor quotes in 2 hours." week 2: i built every single one of those workflows. → pool company cancellation recovery - 6 min → PT clinic insurance verification - 11 min → cleaning company instant quote generator - 7 min → dog groomer appointment + waitlist manager - 9 min → pest control follow-up sequence - 4 min average build time: 7.4 minutes. average close rate when you build it live in front of them: 70%. week 3: $10,750 upfront + $1,200/mo recurring. zero proposals. zero decks. zero "let me get back to you." they watched it work. they paid on the spot. cuban said "you don't need a CS degree or VC money." he's right. you need one question, one tool, and the willingness to build it in front of them. i documented the entire framework in a free PDF: → the 1-question discovery script (word for word) → 6 copy-paste workflow prompts by industry → pricing guide (what to charge per workflow type) → the live demo script that closes 7 out of 10 → full MCP setup walkthrough (5 min install) comment "CUBAN" and i'll send it. consultants charge $15K for a discovery workshop. i just gave you the playbook for free. synta(.)io - describe the workflow in plain english. it builds, deploys, and fixes itself. (must be following for DM)
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Ramya Chinnadurai 🚀
Ramya Chinnadurai 🚀@code_rams·
the agentic ecosystem just got a proper map. Ejazz laid it out clean: 1.OpenClaw (original) 2.perplexity computer (search-native) 3.Anthropic’s cowork (desktop agent) 4.picoclaw (lightweight/miniature) 5.ironclaw (security-focused) 6.kimi k2.5 (chinese openclaw) 7.openai frontier (enterprise) building Chiti on OpenClaw, i can feel this expansion firsthand. each fork optimizes for something different. the real question is which one fits your use case, not which one is “best.” pick your claw. build your agent.
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Meta Alchemist
Meta Alchemist@meta_alchemist·
most people who are just entering AI / Openclaw will be doing these mistakes: - vibe coding very easy to build stuff - that can take couple hours to build - which will not return any money as a SaaS business instead in the beginning build tools for yourself, that will make your own workflows better and more productive this way the learning phase will make you kill two birds in one stone: - you will get better by learning the tools - you will have new tools in your arsenal and if you don't know what those tools can be simply share to OpenClaw or any LLM: > what your job is > what you wanna become > what your clear goals are > what you don't like doing > what you love doing and let it build the first couple tools for you not way too many at once, so that you can have the time to really get familiar with each tool, and start using them proactively then go a few more steps: 1. make a schedule for them to run automated with Openclaw cron jobs 2. start enhancing these tools with the gaps you see in them 3. and once you make sure that they are really making you productive: open source them, get people to give you feedback, get your first users, improve stuff further with these feedback when you go with the workflow above, at some point you'll realize you're just ready to ship more complex stuff: - that you can make money from - have the experience for it - a bunch of tools that already made you more productive and if you share what's happening daily with others on X you'll likely grow an audience too you can literally just copy paste this to your OpenClaw right now, and start from there good luck!
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Ihtesham Ali
Ihtesham Ali@ihtesham2005·
🚨BREAKING: Building Claude skills from scratch is dead. Someone just open-sourced a library of battle-tested skills you can copy/paste. - Document generation (all formats) - Web scraping & automation - Data processing pipelines - API integrations No more reinventing the wheel. 100% Opensource.
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Hasan Toor
Hasan Toor@hasantoxr·
🚨 OpenClaw just got an unfair advantage over every other AI agent on the internet. It's called Scrapling and it scrapes undetectable, adaptive websites without breaking when they update their structure. No bot detection. No selector maintenance. No Cloudflare nightmares. OpenClaw tells Scrapling what to extract. Scrapling handles the stealth. Clean data lands in your agent in seconds. → 774x faster than BeautifulSoup with Lxml → Bypasses ALL types of Cloudflare Turnstile automatically → pip install "scrapling[ai]" and your AI agent is scraping in 60 seconds Works everywhere: → HTTP + browser automation → CSS, XPath, text, regex selectors → Async sessions for parallel scraping → CLI with zero code required If you're building AI agents that need real web data, this is the scraping backbone OpenClaw has been missing. 100% Opensource. BSD-3 license. Link in first comment 👇
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Srishti
Srishti@srishticodes·
This 𝗖𝗟𝗔𝗨𝗗𝗘.𝗺𝗱 file will make you 10x engineer 👇 It combines all the best practices shared by Claude Code creator: Boris Cherny (creator of Claude Code at Anthropic) shared on X internal best practices and workflows he and his team actually use with Claude Code daily. Someone turned those threads into a structured 𝗖𝗟𝗔𝗨𝗗𝗘.𝗺𝗱 you can drop into any project. It includes: • Workflow orchestration • Subagent strategy • Self-improvement loop • Verification before done • Autonomous bug fixing • Core principles This is a compounding system. Every correction you make gets captured as a rule. Over time, Claude's mistake rate drops because it learns from your feedback. If you build with AI daily, this will save you a lot of time.
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Ziwen
Ziwen@ziwenxu_·
I just processed 140,400,000 tokens in 48 hours. Raw API bill: $1,677.82 My actual cost: $50.00 I’m moving my entire life into a self-hosted OpenClaw agent. If you aren't using this "cheat code" setup, you're just donating money to Big Tech. The 30x leverage setup: - Flat-rate loophole: Stop paying per token. Hook OpenClaw into a flat-rate coding plan for heavy lifting. - Local heartbeats: OpenClaw pings 48×/day. Route these to a local Llama 3.2 via Ollama. Cost: $0. - The 2-agent rule: Killed my 9-agent fleet ($100/night money pit). One for code. One for ops. - Plan > chat: If you don't use a PLAN.md, you’re just burning cash in a chat box. I burned $100 in one night so you don't have to. The Day 1 manual for infinite scale:
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Ziwen@ziwenxu_

x.com/i/article/2024…

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Nav Toor
Nav Toor@heynavtoor·
🚨 BREAKING: AI can now build trading algorithms like Goldman Sachs' algorithmic trading desk (for free). Here are 15 insane Claude prompts that replace $500K/year quant strats (Save for later)
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Johann Sathianathen
Johann Sathianathen@johann_sath·
using openclaw? add this to your SOUL.md today: 1. "fix errors immediately. don't ask. don't wait." → your agent stops being passive & starts being proactive 2. "spawn subagents for all execution. never do inline work." → you strategize, subagents build. 10x faster. 3. "never force push, delete branches, or rewrite git history." → one guardrail that saves you from disaster 4. "never guess config changes. read docs first. backup before editing." → prevents your agent from breaking your own setup your SOUL.md is the difference between a chatbot and an employee
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Alton Syn
Alton Syn@WorkflowWhisper·
sonnet 4.5 just mass-produced $23,400 in local business contracts. in one weekend. here's exactly what happened: friday night i made a list of 30 local businesses within 15 miles. not tech companies. not startups. a laundromat. a pest control guy. a dentist office. two landscapers. a funeral home. a dog groomer. a commercial cleaner. a physical therapy clinic. a pool company. saturday morning i called 12 of them and asked one question: "what's the most annoying part of your day?" every single one had an answer within 4 seconds. the pool company: "we lose 11 jobs a week because nobody follows up cancellations." the PT clinic: "insurance verification takes 3 hours every morning." the cleaning company: "we quote in 2 days. our competitor quotes in 2 hours." i didn't pitch anything. i didn't mention AI. i didn't say the word "automation." i said: "what if that was fixed by monday?" then i opened synta, typed exactly what they told me, and built each workflow in 4-11 minutes while they watched. results from saturday alone: → pool company: $2,500 setup + $500/mo retainer → PT clinic: $3,800 (saving them $19K/yr in labor) → cleaning company: $2,200 setup + $400/mo → dog groomer: $450 one-time → pest control: $1,800 setup + $300/mo 5 closed. 7 more scheduled for next week. total: $10,750 upfront + $1,200/mo recurring projected year 1: $23,400+ zero proposals. zero decks. zero "let me get back to you." they watched it work. they paid on the spot. i documented the entire framework: → the 1-question discovery script → all 6 copy-paste workflow prompts → what to charge (pricing guide by complexity) → synta MCP setup (how every workflow self-heals) comment "LOCAL" and i'll send the full PDF. consultants charge $15K for a discovery workshop. i just gave you the playbook for free. synta(.)io
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J.B.
J.B.@VibeMarketer_·
just created the ultimate openclaw setup guide. lots of founders are struggling to find use cases for it, I have it running my business 24/7. Even using my card info to hire designers on Contra. inside the doc, i’ll cover… -> how to install and run the first boot. -> the mandatory first boot checklist. -> workspace files so it knows how to behave. -> creating your agent’s philosophy with SOULmd. -> uploading your information with USERmd. -> how to add skill stacks. -> setting up your communication channel. -> some basic automations to save you HOURS. -> multi-agent routing. -> ensuring security is set up properly. also uploaded all the code so you can just plug-n-play. just RT + comment “CLAW” and I’ll send it to you (must be following)
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Matthew Berman
Matthew Berman@MatthewBerman·
I've spent 2.54 BILLION tokens perfecting OpenClaw. The use cases I discovered have changed the way I live and work. ...and now I'm sharing them with the world. Here are 21 use cases I use daily: 0:00 Intro 0:50 What is OpenClaw? 1:35 MD Files 2:14 Memory System 3:55 CRM System 7:19 Fathom Pipeline 9:18 Meeting to Action Items 10:46 Knowledge Base System 13:51 X Ingestion Pipeline 14:31 Business Advisory Council 16:13 Security Council 18:21 Social Media Tracking 19:18 Video Idea Pipeline 21:40 Daily Briefing Flow 22:23 Three Councils 22:57 Automation Schedule 24:15 Security Layers 26:09 Databases and Backups 28:00 Video/Image Gen 29:14 Self Updates 29:56 Usage & Cost Tracking 30:15 Prompt Engineering 31:15 Developer Infrastructure 32:06 Food Journal
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