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Clαrkᵐᵒᵐᵒ⨳
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Clαrkᵐᵒᵐᵒ⨳
@clarkalphas
Options Fαther +10 yeαrs ░ Creαtor of 𝑴𝑶𝑴𝑶𝑿2 trαding system ░ Mentor to 7-8 figure αpprentices ░ Cofounder @tradingalphas join now 𝑭𝑹𝑬𝑬! ⤵️
αpply ApprenticeX Spring 2026 Katılım Eylül 2019
545 Takip Edilen2.8K Takipçiler

Just wrap up a 1-HOUR class on how to catch these plays today. If you missed it
𝐷𝑀 𝑓𝑜𝑟 𝑭𝑹𝑬𝑬 𝑐𝑙𝑎𝑠𝑠
1 $SPY 670C | +371%
2 $SPY 671C | +1308%
3 $SPY 675C | +1667%
#optionstrading #momoX2system

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I built an @openclaw agent that ranks you on Google for $50/month 😱
here’s the system that runs every week on autopilot:
step 1: find your strike zone
→ connects to Google search console + @dataforseo
→ finds keywords where you're positions 5–20. one good article can push to page 1
→ monitors what’s climbing and dropping weekly
→ feeds winners back in. every cycle is smarter than the last
step 2: write content only you could write
→ interviews you first. 8 questions about your brand, voice, and experience
→ follow-up interviews every week. “what are customers asking? what shipped?”
→ content compounds because context compounds
→ google AI overview can’t summarize your real experience
step 3: build backlinks automatically
→ mines competitor backlinks
→ finds sites mentioning you without linking
→ discovers broken links you can replace with yours
→ last week it found 23 unlinked brand mentions across 4 competitor sites
step 4: catch technical problems before rankings drop
→ core web vitals, bad links, redirect chains, missing meta
→ flags before Google
step 5: future‑proof your SEO
→ schema, llms.txt, topical authority mapping
→ the stuff agencies charge $3K+ to audit once
input: your site + your niche
output: an AI that discovers, writes, builds links, and tracks your rankings
the old way: semrush + ahrefs + surfer + seo writers = $5,500/mo
this way: @DataForSEO ($50/mo) + everything else free
5 skills. 14 scripts. gets better every cycle.
open sourcing the whole system.
comment RANK + like + follow
(must follow so I can DM)
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I run a $110K/month agency with 6 AI employees.
They have names. Personalities. Jobs.
One writes content. One monitors infrastructure. One runs campaigns.
Here's the full setup:
Most people use AI like a search engine. I use it like a staff.
The difference: context files that make each AI know its job, its boundaries, and me.
USER.md — Who You Are
Teaches AI everything about you:
→ Name, location, timezone
→ Your business and goals
→ Working patterns and communication style
The AI can't serve you if it doesn't know you.
SOUL.md — Personality & Principles
The AI's operating system:
→ Core truths ("Be resourceful before asking")
→ Communication style and banned phrases
→ Boundaries and business context
This turns a generic assistant into YOUR assistant.
IDENTITY.md — Who the AI Is
Give it an identity:
→ Name (mine is Jarvis)
→ Role (chief of staff, content writer, etc.)
→ Vibe and operating principle
An AI with identity has consistency.
AGENTS.md — The Operating Manual
The longest and most important file:
→ Startup routine (what to read first)
→ Memory system (where to log, what to remember)
→ Safety rules and learned mistakes
MEMORY.md — Long-Term Memory
Persists across sessions:
→ Discovered preferences
→ Business learnings
→ Key decisions made
Without this, you restart from zero every conversation.
TOOLS.md — Integration Notes
Your AI's reference manual:
→ API endpoints and workflows
→ Team contacts
→ What works and what breaks
Skills — Specialized Instructions
Auto-trigger based on keywords:
→ Content generation
→ Sales follow-ups
→ Lead enrichment
→ Customer onboarding
The Agent Squad
I don't have one AI. I have six:
→ Jarvis — Chief of Staff
→ Loki — Content (8am + 3pm daily)
→ Ivan — Infrastructure (20K email accounts)
→ Hades — GTM campaigns
→ Scrapy — Data extraction
→ Trigify — LinkedIn scraping
Each has its own context, memory, and job.
How They Work
8am — Loki writes 5 tweet drafts
9am — Posts to Slack
10am — I approve 2. Done.
No prompting. It runs on a schedule.
Safety
My AI once bought 164 domains without asking. $1,640 gone.
Now I have:
→ Trusted user verification
→ Financial action gates
→ Prompt injection defense
→ Regressions (mistakes become rules)
Proactive Behaviors
The AI doesn't wait:
→ Cron jobs for scheduled tasks
→ Heartbeats for check-ins
This is the difference between a tool and an employee.
The Stack:
→ OpenClaw (open source orchestration)
→ Context files
→ Skills
→ Agent squad
→ Tool integrations
→ Cron + heartbeats
Everyone's sharing AI setup guides.
That's a good start.
This is what happens when you go 10x further.
Not a chatbot. A system that runs while you sleep.
Like + comment "setup" and I'll DM you the full template.

English

@Jacobsklug @openclaw @VadimStrizheus @grok isnt OpenClaw using Opus 4.6 via Claude Max OAuth violating terms of service?
English

This army of @openclaw agents runs an entire company for $400/month. Here's the exact structure to follow.
(bookmark for later)
1/ Core
→ Jarvis (the brain)
→ Model: Opus 4.6 via Claude Max OAuth
→ Routes every task to the right sub agent automatically. YouTube URL comes in, it goes to Clipper. Research report lands, it goes to Scribe. All task routing logic lives in structured MD files the agent reads from.
2/ Research
→ Atlas (deep research analyst)
→ Model: Claude via OAuth
→ APIs: Brave Search, X API, FireCrawl
→ Cron: Every 1 hour
→ Runs deep research across X, Reddit, and the web nonstop. Trained on
MrBeast's virality framework from every podcast he did on YouTube analytics, plus Dan Koe's viral article structure. Outputs research reports and a master virality playbook MD file that the content team pulls from.
3/ Content
→ Scribe (copywriter)
→ Model: GLM 5
→ Cron: Every 3 hours
→ Takes research from Atlas and writes draft posts matched to the founder's voice and style.
→ Trendy (trend scout)
→ Model: GLM 4.7
→ APIs: X API
→ Cron: Every 2 hours
→ Scans X and Reddit for trending topics and viral patterns. Reports findings back so Scribe can write timely content around what's working right now.
4/ Design
→ Image Designer
→ Model: Nano Banana Pro (Google API)
→ Generates images on demand.
→ Video Producer
→ Models: Higgs Field API + Brok Imagine API
→ Creates AI UGC videos and video content.
→ Motion Designer
→ Model: Claude Code (OAuth) + Remotion
→ Produces motion graphics and animated content.
5/ Development
→ Clawed (senior developer)
→ Models: Claude Code (OAuth) + Codex 5.3 (API)
→ Cron: Every night at 11pm
→ Reviews entire codebase, identifies what's missing, and ships pull requests by morning. First feature it ever built was a FAQ section it realized the homepage needed. Spins up multi agents within Claude Code so one reviews, one builds, one handles security in parallel.
→ Sentinel (code reviewer + bug monitor)
→ Model: Separate LLM (acts as second review layer)
→ Cron: Every 2 hours
→ Reviews all pull requests from Clawed before anything gets merged to GitHub. Also monitors production for user reported bugs and errors.
6/ Growth
→ Atlas + Scribe working together
→ Atlas finds Reddit threads where people complain about competitors or ask for clipping tool recommendations. Scribe drafts responses. The founder copies and posts. This workflow alone drove 450+ users to the SaaS with zero ad spend.
7/ Operations
→ Clipper (clipping agent)
→ APIs: Poster API
→ On demand (triggered by Jarvis when a YouTube URL is pasted)
→ Takes YouTube URLs, clips them, adds captions, and auto schedules posts to social channels.
→ Ryder (9 to 5 support)
→ On demand
→ Handles tasks for the founder's day job. Article writing, research, daily work support.
The breakdown: 6 agents run on Claude models.
The rest run on cheaper API credits across GLM, Higgs Field, Brok Imagine, and others.
This is how solo founders are running entire companies now. The team is already built. You just have to set it up.

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