GROK BOT + OPUS 5.5 CAN BE YOUR FULL-TIME ANALYST FOR UNDER $1 A TASK.
NO SALARY. NO SICK DAYS. IT CHECKS ITS OWN WORK.
the difference between AI that guesses and AI you can trust with real work:
bad: One prompt, one answer, hope
good: Plan, act, check, fix, repeat
give it 12 checks for what "correct" means. It loops until all 12 pass, then stops on its own.
3 rules:
1. A clear checklist
2. Permission to fix its own mistakes
3. A stop rule: all pass, a lap limit or a budget
I break down one AI system like this every week. stay tuned and pass it on to a business owner who needs it.
would you trust an AI analyst with your numbers?
GROK + OPUS 5.5 = 18,000 PARTICLES SHOWING WHY YOUR AI BILL IS 87% TOO HIGH
whether you run grok, opus 5.5 or any other big model, you're probably paying full price for the same prompt again and again.
this board shows where the money goes:
fire = tokens the model reads fresh, at full price
ice = tokens reused from cache, at about 10% of the price
gold = what you keep
same 18,600-token request, example pricing:
→ no cache: $0.0558
→ cached: $0.0072
three rules decide which side you're on:
1. same stuff first: instructions, tools and docs at the top
2. new stuff last: only the new message at the bottom
3. don't edit the start: one changed line at the top makes everything after it full price again
and caches go cold. leave one idle for a few minutes and you pay to write it again.
i break down AI cost tricks like this in plain english. if someone on your team pays the API bill, show them this.
did you know your AI could reuse most of your prompt for a tenth of the price?
GROK + OPUS 5.5 = 18,000 PARTICLES SHOWING WHY YOUR AI BILL IS 87% TOO HIGH
whether you run grok, opus 5.5 or any other big model, you're probably paying full price for the same prompt again and again.
this board shows where the money goes:
fire = tokens the model reads fresh, at full price
ice = tokens reused from cache, at about 10% of the price
gold = what you keep
same 18,600-token request, example pricing:
→ no cache: $0.0558
→ cached: $0.0072
three rules decide which side you're on:
1. same stuff first: instructions, tools and docs at the top
2. new stuff last: only the new message at the bottom
3. don't edit the start: one changed line at the top makes everything after it full price again
and caches go cold. leave one idle for a few minutes and you pay to write it again.
i break down AI cost tricks like this in plain english. if someone on your team pays the API bill, show them this.
did you know your AI could reuse most of your prompt for a tenth of the price?
OPUS 5.5 + GROK BOT = 48,000 S&P 500 HEADLINES CHECKED. 6,688 WERE FAKE
NONE GOT THROUGH.
how the swarm works:
→ 300 agents take in every market headline: wire stories, posts, screenshots, forum rumours.
→ opus 5.5 reads each one and pulls out the claim: which company, what happened, what number.
→ the Grok bot checks that claim against the company's own sources, like the press release, exchange notice or earnings call. Each check takes about 100 ms.
→ if nothing official backs it up, it's flagged as fake, with the reason: no source, company denies, wrong number, old story or parody account.
→ real news is sorted into the 11 S&P 500 sectors: tech, banks, health, energy and the rest.
when a rumour storm hit, fakes jumped 3×, and every headline was still checked before it counted.
a fake "CEO steps down" post can move a stock in minutes. Here it doesn't get the chance.
if you know someone who trades on headlines, send this their way.
have you ever traded on a headline that turned out to be fake?
tekario retweeted
I GAVE GROK BOT $200 AND BANNED EVERY COIN EXCEPT BITCOIN. IT TURNED IT INTO $1,400 IN 7 DAYS
everyone said my last runs were just DOGE luck. So I took DOGE away.
no memecoins. No lottery trade. No "one lucky pump."
One coin. The most watched chart on earth. The one everyone says is too efficient to beat.
6 trades. Longs and shorts. Same coin every time.
I test AI trading repos and I post the parts that make them look bad. This week I tried to take away their best excuse.
the repo: HyperGrok. One Grok brain, 7 agents, Hyperliquid perps. Free and open source.
setup, 10 minutes:
1 Clone the repo
2 Add your Grok API key
3 Wallet: $200
4 Allowed coins: BTC. That's it.
5 Paper mode on
the week, all BTC:
Long +$90
Short +$160
Long −$40
Short +$230
Long +$310
Long +$450
$200 → $1,400. Zero DOGE.
the honest part: the last long made 38% of it. Without that one, the wallet ends at $950. Smaller than the DOGE weeks, but no single trade carried it.
if you've got a friend who still says "it was just luck," send them this one.
what should I ban next?
OPUS 5.5 + GROK BOT = 48,000 S&P 500 HEADLINES CHECKED. 6,688 WERE FAKE
NONE GOT THROUGH.
how the swarm works:
→ 300 agents take in every market headline: wire stories, posts, screenshots, forum rumours.
→ opus 5.5 reads each one and pulls out the claim: which company, what happened, what number.
→ the Grok bot checks that claim against the company's own sources, like the press release, exchange notice or earnings call. Each check takes about 100 ms.
→ if nothing official backs it up, it's flagged as fake, with the reason: no source, company denies, wrong number, old story or parody account.
→ real news is sorted into the 11 S&P 500 sectors: tech, banks, health, energy and the rest.
when a rumour storm hit, fakes jumped 3×, and every headline was still checked before it counted.
a fake "CEO steps down" post can move a stock in minutes. Here it doesn't get the chance.
if you know someone who trades on headlines, send this their way.
have you ever traded on a headline that turned out to be fake?
OPUS 5.5 + GROK BOT = 300 AGENTS HUNTING HIDDEN CONNECTIONS IN THE S&P 500
500 annual reports and every link checked against the page it came from
Apple, Nvidia, JPMorgan, Exxon. Each one publishes a 100+ page annual report every year. Who supplies them, who sits on their boards, who owns what: it's all in there, and almost nobody reads it.
so here's the swarm I'd point at it:
→ 300 agents split the S&P 500 across its 11 sectors: tech, healthcare, banks, energy, industrials and the rest
→ Opus 5.5 reads each company's annual report and pulls out suppliers, major customers, board members and major shareholders
→ It then proposes links between companies: supplier, shared board member, investor, subsidiary
→ A cheap Grok bot checks every link against the exact page it came from in about 100 ms
→ Wrong links get cut. Only links with a page number behind them stay on the map.
the real prize is the links between sectors. A chipmaker and a bank that share a board member. An energy giant that quietly supplies half of industrials.
those ties don't show up on any stock screener, and they're exactly what you'd want to know before you invest.
it's weeks of analyst work, done by a swarm that checks itself.
I'm building more boards like this. If you're into agent setups, you'll see the next one here first. And show this to the friend who picks stocks from headlines.
which S&P 500 company would you want to see the hidden ties of?
OPUS 5.5 + GROK BOT = A REVERSE ENGINEERING MACHINE THAT FACT-CHECKS ITSELF. 300 AGENTS. 51,320 CLAIMS. 0 ERRORS LEFT
how it works (the board shows the architecture):
→ 300 agents run in parallel, each taking one company apart from its filings
→ Opus 5.5 does the heavy lifting: it pulls out revenue, HQ, CEO and founding year
→ A cheap Grok bot checks every claim against the source page, in about 100 ms each
→ If a claim fails, it's thrown out and redone. No "looks right." Only "the source says so."
→ 3 passes over 100 profiles: 212 errors, then 37, then 0
the lesson: don't let one model grade its own homework.
expensive model for the work. Dirt-cheap model for checking. Loop until clean.
every dot on the ribbon is one claim. the white sparks are the ones that got caught.
I'm breaking down more agent setups like this one, so stick around if that's your thing. And show it to the friend who still trusts single-shot AI answers.
would you trust a cheap model to check an expensive one?
OPUS 5.5 + GROK BOT = A REVERSE ENGINEERING MACHINE THAT FACT-CHECKS ITSELF. 300 AGENTS. 51,320 CLAIMS. 0 ERRORS LEFT
how it works (the board shows the architecture):
→ 300 agents run in parallel, each taking one company apart from its filings
→ Opus 5.5 does the heavy lifting: it pulls out revenue, HQ, CEO and founding year
→ A cheap Grok bot checks every claim against the source page, in about 100 ms each
→ If a claim fails, it's thrown out and redone. No "looks right." Only "the source says so."
→ 3 passes over 100 profiles: 212 errors, then 37, then 0
the lesson: don't let one model grade its own homework.
expensive model for the work. Dirt-cheap model for checking. Loop until clean.
every dot on the ribbon is one claim. the white sparks are the ones that got caught.
I'm breaking down more agent setups like this one, so stick around if that's your thing. And show it to the friend who still trusts single-shot AI answers.
would you trust a cheap model to check an expensive one?
Claude Code found a hacker’s device on my home Wi-Fi…
I have 9 devices. Phone, laptop, TV, a couple of smart plugs. I asked Claude Code to list everything connected to my router. It found 11
One was the old smart plug I forgot about in the hallway. Fine
The other one had no name. Its hardware ID didn't match any manufacturer, which usually means one thing: a laptop hiding its real address
It was hacker’s laptop. Connected to my Wi-Fi every evening for 5 months.
Changed the Wi-Fi password. Everything dropped off. Only my devices came back
Someone on your network can see what else is on it, use your IP for whatever they want, and poke at every camera and smart device you own
The full step-by-step is below, takes 2 minutes. Save it so you don't lose it
after I read through Anthropic official guide on Reverse Engineering i gave my local LLM one app and one instruction: “replicate this"
then i logged everything.
- 00:00 drop in the binary. no source, no docs, nothing
- 00:06 50+ functions renamed. it reads like real code now
- 00:18 it finds the encryption routine buried deep inside
- 00:35 full login flow mapped, step by step
- 01:00 spec md done. enough to rebuild the app from zero
one hour. one laptop. zero cloud.
3 rules that made it actually work (keep this):
→ make the model quote the exact address for every claim
→ check anything important by actually running the code
→ keep one notes file it rereads every step
that's it. those 3 rules turn a guessing chatbot into a real reversing partner.
a year ago this was a week of work for a skilled human. now it's a coffee break.
i'm pushing this further every week: bigger apps, harder targets. stay tuned and watch where it breaks.
show this to the friend who still opens ida and suffers alone.
question for you: what's the first app you'd point it at?
tekario retweeted
I TOLD GROK BOT ONE RULE AND IT TURNED $100 INTO $1,000 IN 6 DAYS
the rule: "Stop at $1,000."
the tool: one free, open-source GitHub repo. Grok figured out the rest on its own.
and the moment the wallet hit $1,000, it did something I've never seen a human trader do. It stopped.
closed everything. Went flat. Sent me one line: "Target hit. Waiting for a new one."
I test AI trading repos so you can see what actually works before you put a dollar in. This is the first one that understood the word "enough."
the repo: HyperGrok. One Grok brain, 7 agents, Hyperliquid perps.
setup, 10 minutes:
1. Clone the repo
2. Add your Grok API key
3. Wallet: $100
4. The rule: stop at $1,000
the 6 days:
ETH long: +$55
BTC short: +$120
SOL long: −$30
HYPE long: +$210
DOGE long: +$545
$100 → $1,000. Exactly 10x. Then silence.
the honest part: DOGE made 61% of it. Without that trade, the target is still $545 away. Paper run.
next week I give it a harder rule. If you want to see whether it survives it, you know where to find me.
what rule would you give it?
after I read through Anthropic official guide on Reverse Engineering i gave my local LLM one app and one instruction: “replicate this"
then i logged everything.
- 00:00 drop in the binary. no source, no docs, nothing
- 00:06 50+ functions renamed. it reads like real code now
- 00:18 it finds the encryption routine buried deep inside
- 00:35 full login flow mapped, step by step
- 01:00 spec md done. enough to rebuild the app from zero
one hour. one laptop. zero cloud.
3 rules that made it actually work (keep this):
→ make the model quote the exact address for every claim
→ check anything important by actually running the code
→ keep one notes file it rereads every step
that's it. those 3 rules turn a guessing chatbot into a real reversing partner.
a year ago this was a week of work for a skilled human. now it's a coffee break.
i'm pushing this further every week: bigger apps, harder targets. stay tuned and watch where it breaks.
show this to the friend who still opens ida and suffers alone.
question for you: what's the first app you'd point it at?
FREE HECKING GOLD FOR ANY AI USER:
best 20 GitHub repos to make your own Reverse Engineering Crew to replicate any app you want
i wired these into opus 5.5 and it stopped being a chatbot.
it became a reversing crew:
[01] decompiler bridges: the agent drives the decompiler itself
- LaurieWired/GhidraMCP
- mrexodia/ida-pro-mcp
- fosdickio/binary_ninja_mcp
- radareorg/radare2-mcp
- cyberkaida/reverse-engineering-assistant
[02] ai copilots: explain, rename, comment inside your tool
- JusticeRage/Gepetto
- atredispartners/aidapal
- mahaloz/DAILA
- radareorg/r2ai
[03] runtime & mobile: debug and hook live processes
- AgentSmithers/x64dbgMCPServer
- signal-slot/mcp-gdb
- dnakov/frida-mcp
- zinja-coder/jadx-ai-mcp
- zinja-coder/apktool-mcp-server
[04] diff, decompile & fuzz: find what changed and prove the bug
- clearbluejar/ghidriff
- albertan017/LLM4Decompile
- google/oss-fuzz-gen
[05] benchmarks: check what the agent can really do
- andyzorigin/cybench
- NYU-LLM-CTF/NYU_CTF_Bench
- zhuyansen/awesome-ai-reverse-engineering
the flow: prompt -> mcp -> decompile -> debug -> patch -> verify
what i learned wiring this up:
- a smarter model doesn't win, the loop does.
- an agent that can only read pseudocode guesses.
- an agent that can also set a breakpoint, hook a function and diff two builds checks its own guesses.
that one change is what turns "AI explains code" into "AI does the reversing".
start with GhidraMCP + mcp-gdb. those two alone change how you work.
keep this for the next time a binary makes you want to quit.
i'm breaking down one of these setups end to end soon, so you'll want to be around for that.
and if you have a friend still reversing by hand at 2am, show them this.
be honest: would you trust an AI agent to patch a binary you ship?
FREE HECKING GOLD FOR ANY AI USER:
best 20 GitHub repos to make your own Reverse Engineering Crew to replicate any app you want
i wired these into opus 5.5 and it stopped being a chatbot.
it became a reversing crew:
[01] decompiler bridges: the agent drives the decompiler itself
- LaurieWired/GhidraMCP
- mrexodia/ida-pro-mcp
- fosdickio/binary_ninja_mcp
- radareorg/radare2-mcp
- cyberkaida/reverse-engineering-assistant
[02] ai copilots: explain, rename, comment inside your tool
- JusticeRage/Gepetto
- atredispartners/aidapal
- mahaloz/DAILA
- radareorg/r2ai
[03] runtime & mobile: debug and hook live processes
- AgentSmithers/x64dbgMCPServer
- signal-slot/mcp-gdb
- dnakov/frida-mcp
- zinja-coder/jadx-ai-mcp
- zinja-coder/apktool-mcp-server
[04] diff, decompile & fuzz: find what changed and prove the bug
- clearbluejar/ghidriff
- albertan017/LLM4Decompile
- google/oss-fuzz-gen
[05] benchmarks: check what the agent can really do
- andyzorigin/cybench
- NYU-LLM-CTF/NYU_CTF_Bench
- zhuyansen/awesome-ai-reverse-engineering
the flow: prompt -> mcp -> decompile -> debug -> patch -> verify
what i learned wiring this up:
- a smarter model doesn't win, the loop does.
- an agent that can only read pseudocode guesses.
- an agent that can also set a breakpoint, hook a function and diff two builds checks its own guesses.
that one change is what turns "AI explains code" into "AI does the reversing".
start with GhidraMCP + mcp-gdb. those two alone change how you work.
keep this for the next time a binary makes you want to quit.
i'm breaking down one of these setups end to end soon, so you'll want to be around for that.
and if you have a friend still reversing by hand at 2am, show them this.
be honest: would you trust an AI agent to patch a binary you ship?
a Chinese schoolkid with $5 can now outbuild your whole f*cking AI agent stack. here's the exact setup
step 1 → point Claude Code at DeepSeek's Anthropic endpoint and set EVERY model name to deepseek-flash. skip one and "opus" quietly goes to V4 Pro
step 2 → send every small call to Jev. "which file?" "retry or stop?" "ship it?" $0.042 per 1M tokens, output free
step 3 → one long session per project. cached input is $0.003 per 1M, so rereading your repo is basically free
step 4 → 2 tries per fix, then park it. heavy runs wait for off-peak, half the price
step 5 → the expensive model reads only the final diff. nothing else
Flash-1017 is about $0.20 per DeepSWE task on DeepSeek's own chart. Opus 5 is around $10. that's 50 Flash tasks for one
no team. no funding. just rules
one catch: the chart compares Opus 5, not 5.5. and Flash is cheaper, not faster
so who's still paying the $10 version for every step?
tekario retweeted
I GAVE MY GROK BOT $500 AND ONE ALPHA GITHUB REPO
7 days later it turned it into $4,870.
no charts. no signals group. no paid course. no staying up at 3am watching candles.
just Grok, 7 AI agents and a free open-source repo doing the work while I lived my life.
I test AI trading repos every week so you don't have to burn your own money finding out which ones are real. This is the first one that made me stop scrolling.
the repo is called HyperGrok. one Grok brain runs 7 agents that scan, research, read X sentiment, build a thesis, check risk, execute and review, all on Hyperliquid perps.
setup took 12 minutes:
1. Clone the repo
2. Add your Grok API key
3. Max leverage 20x, max risk per trade 10%
4. Paper mode on
5. Walk away
the trades:
BTC short: +$420
ETH long: +$310
SOL long: −$180
HYPE long: +$1,140
DOGE long: +$2,680
$500 → $4,870. that's 9.7x in a week.
the honest part: one DOGE trade did 61% of the work. Take it out and it's $2,190, still 4.4x.
if you know someone still paying for signals groups, send them this. It'll save them more than a subscription.
would you let Grok trade your $500, or keep doing it yourself?
THIS IS ACTUAL F*CKING TREASURE FOR ANY DEV
Anthropic built one of the best tricks for Claude Code into the product itself.
Almost nobody uses it. It's called opusplan. The idea: stop paying Opus 5.5 to type.
Opus becomes the architect. It plans, reasons, and makes the hard calls.
Then Sonnet 5.5 picks up the plan and does the actual coding.
Same feature, two ways:
Opus solo:
→ 47 min
→ burned budget on boilerplate, imports, renaming variables
→ hit the usage limit before tests were done
Opus plans, Sonnet builds:
→ 21 min
→ ~3x cheaper
→ cleaner diff, because the plan was locked before a single line was written
Here's why this works:
1/ Intelligence matters most at the START.
Choosing the architecture, spotting edge cases, deciding what NOT to build: that's where Opus earns its price.
2/ Typing is not thinking.
80% of a coding session is mechanical: writing tests, wiring components, fixing imports. Sonnet does this just as well, faster and cheaper.
3/ A locked plan kills drift.
When the model plans and codes at the same time, it improvises halfway through. When the plan is written first, execution stays on rails.
4/ You review 1 plan, not 2,000 lines.
Your job shifts from babysitting code to approving decisions. That's the real 10x.
How to set it up (60 seconds):
→ In Claude Code, type: /model opusplan
→ Press Shift+Tab to enter Plan Mode
→ Describe the feature. Opus writes the plan.
→ Read it. Push back. Make it fight for every decision.
→ Approve it, and Claude Code automatically switches to Sonnet for execution.
Pro tips nobody tells you:
- Ask Opus for a "files to touch" list in the plan. Sonnet follows it like a checklist.
- Add "list the risks and edge cases" to your planning prompt. That's where Opus shines.
- Stuck mid-build? Jump back into Plan Mode and let Opus re-think, instead of letting Sonnet guess.
- Put your conventions in CLAUDE md so both models play by the same rules.
keep this. Your next feature will thank you.
show for the dev on your team who's still burning Opus credits on imports.
stay tuned for one Claude Code trick that actually saves time, every day.
Be honest: do you still run Opus for everything?
this is getting f*cking dangerous...
opus 5.5 + the 20 best github repos = a full reverse engineering studio:
[01] analysis core
- NationalSecurityAgency/ghidra
- radareorg/radare2
- rizinorg/rizin
- rizinorg/cutter
[02] ai + mcp
- LaurieWhited/GhidraMCP
- mrexodia/ida-pro-mcp
[03] debug
- x64dbg/x64dbg
- pwndbg/pwndbg
[04] binary & low-level
- WerWolv/ImHex
- angr/angr
- capstone-engine/capstone
- unicorn-engine/unicorn
- horsicq/Detect-It-Easy
[05] firmware
- ReFirmLabs/binwalk
[06] mobile & apps
- frida/frida
- skylot/jadx
- iBotPeaches/Apktool
[07] .net
- icsharpcode/ILSpy
- dnSpyEx/dnSpy
[08] network
- mitmproxy/mitmproxy
how it runs: binary -> analyze -> SPEC.md -> rebuild -> oracle -> retry
the real unlock isn't any single tool.
it's the MCP bridges (GhidraMCP, ida-pro-mcp).
they let an agent drive a decompiler the way a senior reverser would:
rename, retype, cross-reference, repeat.
what used to take a week of staring at assembly now takes an afternoon.
point it at any binary and watch it explain itself.
keep this before your next CTF or malware sample, you'll want it.
i post stacks like this every week. stick around if that's your thing.
and show it to the one friend who still reads hex by hand.
if any closed-source app can now be explained and rebuilt in a day...
is "closed source" still a thing?
this is getting f*cking dangerous...
opus 5.5 + the 20 best github repos = a full reverse engineering studio:
[01] analysis core
- NationalSecurityAgency/ghidra
- radareorg/radare2
- rizinorg/rizin
- rizinorg/cutter
[02] ai + mcp
- LaurieWhited/GhidraMCP
- mrexodia/ida-pro-mcp
[03] debug
- x64dbg/x64dbg
- pwndbg/pwndbg
[04] binary & low-level
- WerWolv/ImHex
- angr/angr
- capstone-engine/capstone
- unicorn-engine/unicorn
- horsicq/Detect-It-Easy
[05] firmware
- ReFirmLabs/binwalk
[06] mobile & apps
- frida/frida
- skylot/jadx
- iBotPeaches/Apktool
[07] .net
- icsharpcode/ILSpy
- dnSpyEx/dnSpy
[08] network
- mitmproxy/mitmproxy
how it runs: binary -> analyze -> SPEC.md -> rebuild -> oracle -> retry
the real unlock isn't any single tool.
it's the MCP bridges (GhidraMCP, ida-pro-mcp).
they let an agent drive a decompiler the way a senior reverser would:
rename, retype, cross-reference, repeat.
what used to take a week of staring at assembly now takes an afternoon.
point it at any binary and watch it explain itself.
keep this before your next CTF or malware sample, you'll want it.
i post stacks like this every week. stick around if that's your thing.
and show it to the one friend who still reads hex by hand.
if any closed-source app can now be explained and rebuilt in a day...
is "closed source" still a thing?











