AI Big brain • Degen • Pro gambler
Lost In Space.
Joined January 2023
- Tweets33.2K
- Following940
- Followers3.2K
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DAVE retweeted
whatchu spinning 👀
I’m going with Jack
btw somethings cookin so make sure you’re positioned
vegabet.promo/innopro
DAVE retweeted
This is insane…
I learned this while connecting 7 Grok Bots into one launch workflow.
The biggest mistake? Scheduling every bot to wake up on a timer, even when there’s nothing to do.
Here’s what can go wrong:
→ Constant polling: Seven bots running hourly can generate 1,176 runs per week, with many returning nothing.
→ Approval bottlenecks: Bots handing work off through email can leave you buried in drafts waiting for approval.
→ Dangerous test runs: A test may execute real actions instead of simply simulating them.
→ Shared X limits: One bot can consume the team’s available read budget before the others get their turn.
→ Launch-hour overload: A sudden burst of signups can push your workflow past its execution limits.
And the waste adds up quickly.
A single bot running every five minutes can trigger 2,016 runs per week, even if nothing meaningful happens.
My launch team handles its workflow in roughly 60 runs.
Here are 5 changes worth making:
1. Replace constant polling with triggers.
Keep one scheduled routine for essential checks. Let the other bots activate when there’s actual work to do.
2. Use a shared ledger.
Have bots record completed tasks and handoffs in one shared file instead of creating endless email drafts.
3. Set clear execution limits.
Give every bot its own X-read budget and a hard stop when it reaches the limit.
4. Separate testing from execution.
Use a genuine simulation mode where available, and require approval before any real action during testing.
5. Put spending behind a strict approval gate.
Assign financial actions to one bot, enforce a $40 limit, and require your explicit approval for every purchase.
The goal isn’t to make seven bots run more often.
It’s to make them work together without wasting resources, hitting limits, or taking actions you never approved.
Fewer unnecessary runs. Better coordination. More control.
Save this before building your next Grok Bot workflow.
Full guide to the 7-bot launch setup below ↓
DAVE retweeted
STOP SCROLLING.
This guy just built a full $25,000 agency website with AI and n8n, and he didn’t write a single line of code.
The site looks expensive.
The real play is what happens after someone fills the form.
Here’s the workflow:
→ Interview Claude about the business and generate CLAUDE.md
→ Tell it to build the site with real photos, big serif headlines, and a 5 step quote form
→ Push the project to GitHub
→ Set up n8n and connect it to Claude
→ Tell Claude to build the lead workflow in plain English
→ Save every request, score it, and write a custom reply
→ Email the owner and the customer automatically
→ Add follow ups and error alerts
→ Put the site live on Vercel and expose the webhook with a Cloudflare tunnel
→ Run a security audit and fix what it finds
A lead comes in.
Claude reads it, scores it, and sends a real reply in under a minute.
The website is the shop window.
n8n is the office that never sleeps.
Bookmark this.
DAVE retweeted
$3k in under 2 months. 7 income streams. one ai agent team. the whole playbook…
no team. no ads.
here's the exact plan:
- find leads:
an ai agent scans x daily for ai x crypto projects and creators who just launched, raised, or are posting nonstop, that's the customer list
- send emails:
the agent drafts a personal email for each lead:
- what i noticed
- what i'd make them
- one clear offer
i review, i hit send
10 a day
- ai video bookings:
custom 10–15s ai clips at $150 - $250/per month. one viral sample becomes the portfolio, dms turn into bookings
- brand deals:
a media kit plus pitches to the ai tools i already use
target: 3 - 5 sponsored posts at $300 - $500
- digital product:
package the workflow into a $19 - $29 kit
target: 30 - 40 sales
- newsletter:
a weekly ai x crypto brief
goal: one sponsor slot per issue by month 2
- affiliates
link the tools i actually use, small, but it stacks
the math i'm aiming for:
- brand deals: ~$1.5k
- ai videos + services: ~$600 - $1k
- kit: ~$600 - $900
- newsletter + affiliates: ~$200 - $400
target: $3k+ in under 2 months
the agents do the grind
i do the deciding
i'll share real numbers as they come in
follow along and bookmark this if you're building the same thing
DAVE retweeted
THIS IS F**KING INSANE
I just tried a browser that lets you run dozens of accounts without them getting linked or banned 🤯
It's called Octo Browser, an anti-detect browser that gives every account its own fingerprint, cookies, and proxy.
Here's what you can do with it:
→ Spin up profiles fast with Templates
→ Create Android device fingerprints
→ Bulk-create profiles when you scale
→ Buy residential and mobile proxies in-app, with UDP support
→ Set a separate password per profile
→ Manage teams with permissions, tags, folders, and tasks
→ Automate with Selenium, Puppeteer, Playwright
The best part? You can customise your plan and add profiles or team members as you grow, so you only pay for what you need.
If you manage client accounts, run ads, or work in a team, this could save you hours of setup.
If you manage multiple accounts, Octo is worth a look. Templates, per-profile passwords, and UDP proxy support are the features that set it apart for me.
Save this for later
Check it out:
octobrowser.net/
use promo code HURRICANE for 4 days of free access + a 30% discount.
🤝 Paid partnership
This guy breaks down how to make $30K on YouTube without showing your face once.
The exact method he's using in 2026, explained step by step.
If you've been thinking about YouTube automation, you need to see this.
DAVE retweeted
I TOLD MY GROK BOT ONE THING:
“PROTECT MY CAPITAL FIRST.”
It turned a $250 paper-trading account into $2,310.
The setup? An open-source GitHub repo that turns Grok into a Hyperliquid perps trader.
Here’s how it works:
1. Clone the repo.
2. Add your API key.
3. Set leverage and risk limits.
4. Choose which trading pairs it can access.
5. Test everything on paper before risking real money.
Then let the agents do their jobs.
The reported results after 5 trades:
→ ETH: +$140
→ BTC: +$265
→ SOL: −$71
→ HYPE: +$402
→ DOGE: +$1,324
$250 → $2,310 on paper.
But the real alpha isn't just Grok picking trades.
It's the risk management system behind it.
One agent sizes every position, sets the stop-loss before entry, and can veto the other six agents.
Grok can spot an opportunity all it wants.
If the risk agent says no, the trade doesn't happen.
And here's the part most people would leave out:
DOGE generated 64% of the total profit.
Without that trade, the account would have ended around $986.
That's why one profitable run doesn't prove a bot is consistently profitable.
I'll keep sharing the runs, including the losses.
Bookmark this if you're building AI trading agents.
One question: What's the FIRST rule you'd give your trading bot?
DAVE retweeted
THEY JUST RELEASED AN AI HACKER THAT AUTOMATICALLY TESTS YOUR APP FOR VULNERABILITIES.
And it already has over 48,000 GitHub stars.
It’s called Shannon, an open-source AI penetration testing tool.
Instead of just listing potential security flaws, it attempts to exploit vulnerabilities and verifies whether they can actually be exploited.
Here’s what makes it interesting:
→ Attempts real exploits instead of simply guessing where vulnerabilities might exist
→ Avoids reporting flaws it can’t successfully exploit
→ Integrates with GitHub Actions and GitLab CI for automated security testing
→ Generates professional PDF reports for your team or clients
→ Exports findings in SARIF format so they can appear in compatible development tools
Traditional tests check whether your application works.
Shannon goes further and tests whether an attacker could break in.
You can integrate it into your development workflow and run security tests as part of your release process.
It’s open source and supports compatible AI models.
If you’re building software, doing security research, or working in cybersecurity, this is worth checking out.
REPO IN THE FIRST COMMENT.
DAVE retweeted
5 ai agents that replace a whole content team
1/ scout
replaces: hours of scrolling for alpha
finds early ai and ai x crypto projects before they blow up
you wake up to leads, not a feed
2/ analyst
replaces: the research rabbit hole
digs into team, product and traction on whatever scout finds
you get the facts, not the hype
3/ writer
replaces: staring at a blank draft
writes posts in my voice with the source attached
you just hit post
4/ creative
replaces: the designer you can't afford yet
makes the visuals and clips for each post
5/ growth
replaces: refreshing your analytics
tracks how every post performs
that's my all agent team on grok bot
follow + repost if you want the setup
DAVE retweeted
steal this prompt for your grok bot
paste it in and get a week of posts ideas:
- check the top 10 ai accounts on x from the last 7 days
- pick the 7 posts with the most engagement that have a video or image.
for each one
- write a post in my style, link the source, and flag any number i should double check
it does the scrolling so you don’t have to anymore
bookmark this
DAVE retweeted
This is f**king crazy.
Imagine being able to test an entire robotic factory in your browser before deploying anything on a real production line.
Claude Opus 5.5 makes it possible with a simulation powered by real physics.
At 780 cartons per hour, every system check passes.
Increase the speed to 1,680 cartons per hour, and things start breaking down.
Within 4 seconds, the robot's grip slips and a carton crashes to the floor, all happening live in the simulation.
You can build it, push it to its limits, identify failures, and fix them before they happen in the real world.
This is what happens when AI meets real-world engineering.
DAVE retweeted
I GAVE MY GROK BOT ONE PROMPT AND WENT TO SLEEP.
By morning, it had built a 6-agent trading system for pump.fun.
No code written by me. Just one prompt.
Here’s how the system works:
→ Scout: Monitors every fresh token launch
→ Filter: Rejects tokens that fail even one safety check
→ Analyst: Scores survivors. Anything below 0.6 gets rejected
→ Executor: Never risks more than 10% of the portfolio per trade
→ Risk: Sets an −8% stop-loss before entry and trails winners after +15%
→ Logger: Records the reason behind every decision
But the most interesting part?
It spent hours saying NO.
Out of 11,400 token pairs:
→ 11,306 rejected
→ 94 scored
→ 41 trades executed
Here’s what got them rejected:
• 3,212 — Mint authority not revoked
• 2,584 — Liquidity not locked
• 2,147 — Top 10 holders owned over 25%
• 1,738 — Less than $40K in hourly volume
• 1,021 — Developer wallet linked to past rugs
• 604 — Bundled at launch
Three trades stood out:
PUMPKIN looked perfect. Rejected because mint authority wasn't revoked.
ZAPPY hit its predefined stop-loss at −$2.09.
TUFFY caught an early move on the Pump.fun bonding curve and returned a reported +$1,140.
The simulated results:
41 trades. 29 winners. 12 losers.
Worst loss: −$5.25.
Reported account progression:
$300 → $1,065 → $2,056 → $3,313 → $4,217.
One important detail: this was a simulated run, not verified live trading performance. The next test is whether the system can survive real execution, slippage, and changing market conditions.
The exact prompt is in the first reply ↓
Bookmark this if you're experimenting with AI trading agents.
Would you trust 6 AI agents to trade while you sleep?
In just 8 minutes, this guy breaks down how to consistently go viral on YouTube Shorts in 2026.
It's one of the clearest explanations of how the algorithm actually works that I’ve come across.
If you're serious about growing on YouTube, this is worth saving.
Bookmark it. You'll thank yourself later.
nitter.cf/He1s_Sammy/status/2109…
DAVE retweeted
i always assumed decentralized compute meant a painful setup
then i watched @linq_ai's new demo 👇
connecting to a 𝗱𝗲𝗰𝗲𝗻𝘁𝗿𝗮𝗹𝗶𝘇𝗲𝗱 𝗩𝗠 now feels exactly like any cloud VM
and with LinqGuard monitoring provider activity, workload behavior stays verifiable
decentralized only wins when it feels 𝗷𝘂𝘀𝘁 𝗮𝘀 𝗲𝗮𝘀𝘆 as the cloud
🤝 Paid partnership
DAVE retweeted
This is the direction trading needed to go.
Instead of fighting the market alone and getting wrecked by liquidations or rugs, you’re competing skill-vs-skill for a fixed pot.
Highest PnL% wins. Liquidation = knockout.
@FatCatArena is turning trading into an actual sport.
The days of traders losing money to liquidations & rugs are almost over. The new Era of Trading is getting closer. Dial in and prepare for a better way to trade and earn income. #competitivetrading #FatCarArena
@FatCatArena
DAVE retweeted
THIS IS F**KING GOLD
GROK + TAVILY + CLAUDE CODE. THIS IS A POWERFUL COMBINATION.
GrokSearch is an open-source MCP server that gives Claude Code access to Grok-powered web search, webpage extraction, and website mapping.
Here’s what makes it interesting:
→ AI-powered search: Let Claude search the web for current information instead of relying entirely on its training data.
→ Read entire webpages: Use Tavily to extract webpage content and retrieve information from the actual source.
→ Automatic fallback: If Tavily extraction fails, Firecrawl can step in to retrieve the page.
→ Map websites: Discover URLs across a website to help your AI explore its structure.
→ Search specific platforms: Focus searches on platforms like X, GitHub, and Reddit.
→ Switch models: Change the Grok model used for searches without rebuilding your workflow.
→ Automatic time context: Time-sensitive queries get local time context to improve search relevance.
It also provides tools for retrieving sources, diagnosing configuration issues, and planning complex searches.
The idea is simple:
Give your coding agent better access to external information so it can verify details instead of blindly trusting what it already knows.
GitHub: github.com/GuDaStudio/GrokSe…
