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.
A random mix from the whole library. Shuffle for a new set.
Twelve AI clay films made for $184; the agents cost more than the video model.
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.
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.
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.
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 credits Hunter, its Agentforce sales agent, with 60 percent of its sales pipeline, per Salesforce's release.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.