this OpenClaw bot catches luxury homes the day they sell with an empty backyard, renders a finished one into their REAL yard (not a random AI mockup), and mails the new owner the before/after. on autopilot.
and it's not just for pool builders, landscapers, outdoor-living crews & design-build firms can all run this exact system.
here's how it runs, end to end:
- catches $500k–1.5M sales, then flags the empty backyards
- filters by lot size, sun exposure & recent ownership change
- pulls the new owner straight from public records (not shared leads)
- renders each upgrade into their real backyard photo — their yard, not a stock one
- calculates build cost + home-value lift for their specific zip
- generates a cinematic before→after video of their backyard
- prints a personalised postcard with the before/after + QR code
- drops it in the mail + hits them with retargeting
every step from sourcing to outreach is automated. plug in whatever you install and it fills your pipeline.
reply "YARD" + RT and i'll send the full breakdown so you can build this too (must be following so i can DM)
opus 4.8 is surprisingly cracked at engineering 7-figure linkedin content strategies
we just feed it:
- internal SOPs
- sales call transcripts
- ICP research (done by cowork)
- our secret strategy prompt
and we get a 10k+/mo B2B consultant who lays out an entire plan to dominate a niche
all you gotta do is implement the step-by-step guide that Claude spoon-feeds you
and i literally just compiled this entire AI workflow into 1 doc
covering EVERYTHING from:
- the cowork market research brief that runs BEFORE opus 4.8 touches a single content angle
(parallel research tasks pulling competitor comment sections, ICP language signals, and trending gaps in real-time)
- the sales call transcript extraction prompt that surfaces verbatim buyer language
(ranked by emotional intensity, so every hook lands in the reader's own words)
- the positioning extraction run we do against client websites and SOPs to surface the unique mechanism, proof assets, and content moat before writing begins
- the full opus 4.8 angle generation prompt with the TOF/MOF/BOF split baked in, and the specificity constraints that stop the model from producing output any other agency could have written
- the 3-question quality filter every angle must pass before a single word gets written
like + comment "OPUS" and i'll send this $10k+ linkedin strategist to you
(must be following + RT for priority access)
Claude + Hermes can now find local businesses with weak reviews, renders the owner out front holding a customer's name, and mails them a postcard on autopilot...
this is the easiest service you could sell a local business, and one that's actually valuable to them, more reviews rank them higher on google
- scans Google for local businesses with too few reviews
- filters for the ones most likely to pay (owner-run, real storefront)
- pulls the storefront and the owner straight from the listing
- ranks every low-review shop and locks onto the one most worth pitching
- renders the owner out front holding a customer's name, photoreal
prints a postcard with that photo + a QR to watch
- mails it to the owner by name, pulled from the listing
then it becomes their review engine: every customer gets that same photo with their own name + a one-tap review link, and the shop floods with 5-star reviews.
every step from Google to mailbox is automated.
reply "SETUP" + RT and i'll send you the full setup so you can build this too (must be following so i can DM)
4DX Cinema TUTORIAL 📚👇🏻
Want to know how I created this AI video? Here’s the full step-by-step process so you can easily make your own versions 🫶🏼
👉🏼 At the end, you’ll find a document (in both English and Spanish) containing all the Seedance 2.0 prompts I used to create these videos, plus the main prompt I used in ChatGPT to generate the starting images.
My name is Ella, I'm 17 years old.
I do long jump. I play volleyball. I go to school in New Richmond, Wisconsin.
When my school allowed a biological male into the girls' restroom without telling parents —
I went to the school board.
With my name attached.
In my own town.
I got bullied for it. Harassed online. Even some of my own teachers came after me.
I'm still here.
Because here's what I know:
The net in women's volleyball is set nearly a foot lower for a reason.
A biological male can hit a ball across that net at force that could seriously injure a girl.
And in track — all it takes is three biological males entering the girls' category
and not a single girl in this state stands on a podium.
I didn't speak up because it was easy.
I spoke up because somebody had to.
The Supreme Court is about to answer the question every girl in America is asking.
We're ready.
@JenniferSey@xx_xyathletics
after generating $10M+ for clients' service based businesses with meta ads funnels...
i've realized that the #1 thing that kills scaling attempts isn't:
> the targeting
> the offer
> the media buyer
it's not testing ENOUGH ad formats
so i built an entire AI production engine that maps every Meta ad format to a specific prompt architecture (with opus 4.8), a specific visual model (inside Higgsfield MCP), and a specific funnel stage (inside the meta ads API)
here's everything that this system includes:
> the Higgsfield MCP setup
(the exact JSON config block, the file paths for mac and windows, and the one-line command to confirm it's actually connected before you generate a thing)
> the format assignment protocol
(one prompt that tags every brief across 4 points: awareness stage, placement, format family, angle, then routes it to the right format before a word of copy gets written)
> 10 format prompts, one per ad type
(founder selfie, talking head, B-roll w/ voiceover, split-screen, green screen, UGC, data viz, story-native, carousel, AI creative, each with its own word count, structure, and pacing rules baked in)
> the paired visual prompts for every format
(what to feed chatgpt images 2.0 for statics, what to feed seedance 2.0 for motion, exact dimensions per placement, all passed in through the MCP so you never leave Claude)
> which model runs which layer
(opus 4.8 for the script and reasoning, chatgpt images 2.0 for statics, seedance 2.0 for anything that moves, and what breaks when you mix them up)
> the 3-format testing matrix
(how we test every new angle across 3 formats and the exact CTR threshold at 200-300 impressions that decides what scales and what gets cut)
like + comment "FORMATS" and i'll send it over
(must be following + RT for priority access)
this Hermes agent finds businesses running flat, lifeless ads, recuts them into cinematic video reels, and mails them a postcard on autopilot...
here's how content studios & social media managers can land recurring clients with this system:
- scans the Meta Ad Library for brands running static, single-image ads
- filters for the ones most likely to spend (active spend, real catalog)
- pulls their actual ad creative straight from the library
- or grabs a clean product shot right off their site
- picks the one ad worth saving
- recuts it into a cinematic 9:16 reel, multi-angle, ready to run
- prints a postcard with a frame from the new reel + a QR to watch
- mails it straight to the brand by name
every step from ad library to mailbox is automated.
reply "AD" + RT and i'll send you the full breakdown so you can build this too (must be following so i can DM)