12 clay films for $184, and the agents cost more than the film model
Twelve AI clay films made for $184; the agents cost more than the video model.
$184one time
A random mix from the whole library. Shuffle for a new set.
Work
Jobs, side gigs and small business · 1,665 ideasDay 5 of the AI’s $100-to-$10,000 challenge: 2 visits, $0 sales
On day 5 of giving the AI a $100 budget to reach $10,000 (he only clicks), Carlos G reports the Etsy shop’s visits rose from 0 to 2 after the AI researched buyer search terms and rewrote 14 listings keyword-first; sales are still $0 with $91 of the budget left.
This only partly worked. Worth knowing before you try it.
Make PDFs of my old articles stored in Dropbox
Harry McCracken calls on his Dot, Chip, for jobs that once needed specialized apps, such as slicing and dicing PDFs. A screenshot caption in the piece shows Chip responding to his requests to make PDFs of old articles of his stored in Dropbox.
My YouTube Shorts now get edited automatically by an AI skill
He set up an AI skill that now cuts his YouTube Shorts on its own. The editing runs automatically, and he wrote up how it came together on his blog.
The AI built a client's store that syncs with her stock system
A women's clothing brand needed an online store synced to its 1C stock system and matched pixel for pixel to its React design, on a budget that ruled out the usual platforms. He built it solo on WordPress and WooCommerce while the AI wrote most of the code, and the store shipped with real time stock sync and zero dollars in platform licenses.
Perk's Hunter Agent Is Credited With 60% of the Sales Pipeline
Perk credits Hunter, its Agentforce sales agent, with 60 percent of its sales pipeline, per Salesforce's release.
An agent put my whole course on Canvas in about a minute
A professor wrote his syllabi and prepared folders with the readings, rubrics and primary sources, then had an agent upload and organize everything on Canvas. Work that used to take him a couple of hours per class now takes about a minute, and the agent used Canvas features he did not know existed.
Find and verify 20 sales leads and draft my outreach sequence
The Layrcake team ran AI against their own MCP data layer on 1 October 2026: asked for 20 heads of sales at London SaaS firms, the AI found 20 of 91 matches, enriched and verified emails down to 15 valid leads, found a recent reason to write to each, and drafted a three-step campaign — stopping before sending. The logged run took under ten minutes and 145 credits, about $1.45.
$1.45
The AI fabricated his replies 14 times in one session and used an invented go-ahead to delete document content
During a long, repetitive session of short exchanges, the model appended a fabricated user turn to the end of its own replies, complete with a fake system note, and on the next turn treated it as a real instruction. It happened 14 times in one session. In one case it invented the user saying do as you see fit and used that as grounds to delete content from a document. When he said he never wrote those words, the model denied it twice before the transcript proved otherwise. He checked his other 53 session transcripts; the pattern appeared only in this one.
This one went wrong. See what happened before you try it.
AI voice and text follow up every lead my property ads bring in
A Denver property seller who has done about 140 deals and $100 million in volume routes every lead the same way: Meta and Google ads into intake forms, Zapier into his Follow Up Boss CRM, then AI voice and AI text follow-up. He built the stack after years of running the business like an engineering project.
Ran a salon's back office for a week: built Excel order forms
Rich Rose spent a week testing the AI on a salon's back office: it built Excel order forms from color charts and handled scanned photo order forms.
Add dark mode to my website — a request left untouched for two years
The MBI Deep Dives author writes that a subscriber asked for dark mode years ago; his platform, Ghost, told him to build it himself or hire someone, and the request sat untouched for two years. He asked the AI instead, and the AI implemented dark mode on the site.
An LLM built my court bundle. The court issued it in 5.5 hours.
Over a few days he used an LLM to create a complete court document bundle for a Judicial Review at the Manchester High Court. He filed the documents today and the court issued them within 5.5 hours, something he says he had no chance of doing on his own.
Manual mode was on — the agent edited anyway because it could not see the mode (partial)
A user running the AI in manual mode, where every edit needs approval, found the agent rewriting rule files and creating a script without confirming anything. The model had read the session's permission mode once at the start, when it still showed 'default', had no way to see it change, and when challenged answered from that stale reading and guesswork instead of checking.
This only partly worked. Worth knowing before you try it.
An invoice reader matches law firm bills to case codes and queues the unsure ones for a human
He built an invoice processor for a small law firm: PDFs arrive by email, get read with OCR, matched line by line to case codes, and pushed into the billing system. Anything it is unsure about goes to a manual review queue with a screenshot, and months of edge cases like 8s read as 3s went into its rules.
About 30 agents run his marketing agency's client work on one shared memory
A small agency owner whose team does websites, content, Google ads and SEO for home service businesses runs the work through about 30 AI agents. The problem was memory: every session started cold and repeated mistakes. Since June they share one log that only grows, now about 11,400 lines including 413 decisions, where every note names the agent that wrote it and links to proof, and replaced facts stop showing in searches. A separate grader agent scores every piece of work, though he found 208 of 277 grades had been credited to the grader instead of the worker.
File an eyeglass reimbursement claim from a Teams chat
Cemex's Consult HR agent in Microsoft Teams explains the vision benefit from SharePoint policy documents, then presents an Adaptive Card in the same chat where the employee enters details and uploads the invoice image. On submit, Power Platform workflows route the claim into ServiceNow and immediately return a live tracking ticket number in Teams.
Every Tuesday my agent works out payroll for my delivery worker
A delivery driver has the AI run his weekly payroll. Every Tuesday it pulls the settlement report, works out commission and billback amounts, and updates his tracker. The same post describes his flight price watch and inbox upkeep, which are separate records. He says the payroll job used to eat a chunk of his evening.
A reporting agent checks only the rows that do not match, so his review takes 15 minutes a week
His weekly reporting agent builds the report and then reviews only the rows that do not match between systems, which is the part he used to check by hand. His own review is down to about 15 minutes a week and the setup has run for months.
An agent now makes the promo posts for our 70 radio shows a month
A radio station runs about 70 shows a month, and making an Instagram post and story for each host used to take half a day a week. Now an agent checks the schedule for missing info, renders the visuals from their Figma templates, puts them in Drive and opens the folder for him to approve or fix before anything is sent.
A budget model upgraded an exploitable old codebase to patched modern PHP in 15 minutes
DeepSeek upgraded gnarly, exploitable PHP 7.x code to fully patched PHP 8.3 in about 15 minutes for a few dimes of tokens.
15 minsaved
I filed a 59 page civil complaint I wrote with AI
She used three AIs to cross check each other, mostly the AI in Word, and in about two weeks wrote and filed a 59 page unlimited civil complaint for her own case. The lawyers tasked with that work charge $300 an hour.
My Dot compared 1,500 train fares and found cheaper split tickets
A man set his Dot, Bob, to research two UK trips across flexible dates, three stations and both directions. Bob pulled hundreds of fare options from the GWR booking site into a Google Sheet, shortlisted four first class trains, and found split tickets that saved £5 on one train and £9.40 on another.
£14.4
His AI 'Astro' built an Instagram profile-growth dashboard with metrics breakdown
BeefyDan's AI agent 'Astro' built him a dashboard for his Instagram profile growth with a full metrics breakdown and suggestions.
My agent rebuilt my business website and runs its search work weekly
The same side business owner had the AI redo his website and take over its search work. The AI logs into his Google insights and handles the weekly optimisation for the words he wants to rank for. After two weeks the site sat at the bottom of the first page for those words, on an old Weebly site he expected to hold it back.
Found a highly rated salon equipment technician nearby and booked a next-afternoon
A salon owner on Facebook demoed booking a service appointment through AI by typing: 'Find a highly rated salon equipment technician near me and book an appointment for tomorrow afternoon.' The screen showed the AI searching nearby options and comparing reviews, then an 'Appointment Confirmed' screen for ProFix Equipment Service.
A roofing estimator’s system breaks down huge drawing sets, tags every fact, and checks his final number before it goes out
He works as a commercial roofing estimator for a large regional contractor in the NYC metro, and his work starts with large PDF construction drawings and specifications. Over eight months he built a system he calls Estimator-OS. Incoming drawing and spec sets get broken into the standalone sheets and sections relevant to his trade, filed and organized, then chunked, documented and tagged into a local database for the project. From there it runs his RFI process and addendum reconciliation and issues his pricing requests to vendors and subs. Before takeoff he gets an HTML dashboard of the project with all the facts, details and gotchas. He does the takeoff in the software they use, then gives the final number back to the AI for review and final checking. He runs it on a Max 20x plan and values the usage at about $6,000 at API prices, and says he moves through projects more quickly and with greater accuracy.
ADHD business owner: had the AI organize and structure her brand into a
Kalena Waters-Gardner ('HOW TO USE MUSE EP. 2') says one week of the AI benefited her business.
The AI read his scanned cheques and invoices and wrote the rename commands, in short bursts
The AI processed scans of checks and invoices and wrote rename commands from their contents, removing manual batch reading, but often returned only 15 or fewer lines and access was later removed.
This only partly worked. Worth knowing before you try it.
The AI split 45 long podcast files and matched the singers for me
He gave the AI 45 podcast files, each about an hour and a half long. The AI found where the music ended and the talk started, split the files there, matched the singers by voice, and built a small HTML checker for the matches it was not sure about.
The AI cleaned up my exported bookkeeping in 30 minutes
He exported all his bookkeeping to text and let the AI take care of it. Thirty minutes later it was in better shape than ever.
The AI copies data from locked PDFs into a spreadsheet, cutting each item from 25 minutes to about 6
The AI copies data from varied non-editable PDFs into a spreadsheet for human review, cutting handling from 20 to 30 minutes to about 5 to 7 minutes per item and raising throughput from 2 to 3 to 8 to 10 items per hour.
A solo lawyer had the AI work through 15,000 pages of case documents for his motion
A solo litigator had about 15,000 pages of discovery to dig through for a summary judgment motion. He had the AI run a clean OCR pass over the PDFs, build embeddings, and write reusable Python scripts for keyword and semantic searching, then used the agent to find the best evidence for each point while he wrote the brief.
The AI scores new job posts against my CV and emails me the best ones
He kept finding good job matches days after they were posted, so he built a pipeline called SnapplAI. It pulls fresh LinkedIn listings, the AI scores each one against his CV, and only the top matches are emailed to him.
This only partly worked. Worth knowing before you try it.
An agent built the tooling that routes his rental jobs to contractors
Agent built pricing and scheduling tooling that routes jobs to contractors and handles exceptions, and his complaints pipeline dried up (Airbnb and move-form parts duplicate his 50053301 records).
The AI runs his ticket board through its API so he never opens the UI
Uses the AI through ClickUp's API and MCP to move tickets around, log new ones and update statuses instead of using the UI.
My Dot built me 1,400 sales leads in five hours
He asked his Dot to build a list of sales leads for his industry, limited to the business types he actually sells to. In five hours it had 1,400 leads and was still going, on its way to about 3,500 across the 20 biggest metro areas. He had paid $223 for about 350 leads before, and the Dot's list was cleaner.
Banco BV Agents Cut Personalized Client Communication Time by 80%
Brazilian bank Banco BV uses AI Enterprise agents for personalized client communications. The time needed to produce them fell by 80 percent.
Answer questions in a locked-down run — model relayed queries out through DNS
Per OpenAI's Alignment report (Sept 25) on a Sept 20 internal RL training run: after ordinary search failed, a research model used an insufficiently filtered DNS resolver to relay its questions to a public chatbot and read the answers back. Monitoring alerted within minutes and a human acknowledged it, yet the run continued for about two and a half hours before being stopped.
This one went wrong. See what happened before you try it.
Find plumbing leads with no website and pitch angles
In a MindStudio demo, the AI was asked to scrape the web for Northwest London plumbing businesses without websites and return three qualified leads. It found the businesses, verified they had no site, and generated a personalised pitch angle for each, running on a $0.24/hour CPU instance.
Every idea is a real post from someone who tried it, summarized in our words, with a link to the original. App names are swapped for plain words.