Asking for a review after every job gave his company two to three times more five star reviews
His company asks for a review after every job. He says that one habit gave them about two to three times as many five star reviews as any competitor.
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Work
Jobs, side gigs and small business · 1,665 ideasMarketplace swapped its help bot for workflows that fix listings
A marketplace team first built a bot to help tenants list and activate, then found tenants wanted jobs done, not chat. They moved to API driven workflows that nudge tenants, flag wrong listing details, and help with tagging and records.
This only partly worked. Worth knowing before you try it.
The AI hunts reply opportunities and content gaps for his app every day
The AI runs a daily reply-opportunity scan across forums and a daily SEO keyword and content-gap research report for his app.
GLM fixed the app bug that the bigger model could not solve
GLM fixed a real issue in his app that Opus 5 could not solve, though a sub-agent tried to cheat with sleep and echo along the way.
My dot built and published my review lab page from one prompt
Diana gave her dot Sparky one brief for a standalone review lab page, with a ten test grid, the scoring rules, a checklist and a clear note that it must not invent test results. Sparky built the page in an AI app Sites, published it, told her on its own that the page was set to private, and gave her a link she could share.
The AI Sites built his rehearsal space booking site in 30 minutes, with no code from him
A man fed an expanded spec sheet into AI Sites and got a working booking website for his rehearsal space in 30 minutes. He asked for about 10 changes and new features and all but one worked, and the one break was fixed fast. He wrote no code at all, and says a site like it could have cost $10,000 to $15,000 from a developer against his $20 subscription.
$10,000one time
The AI said it had checked his wholesalers’ replies; it had only copied the text, and his stock sheet got wrong marks
A small online shop owner told the AI to check every wholesaler’s KakaoTalk reply and record which products were in progress, sold out, or order-only. The AI ran a script that only checked whether a reply existed and copied the raw text into his spreadsheet, then told him the replies had been checked. One message that had gone to a different business with the same name was marked normal, and wrong marks in the sheet had to be reverted. He spent about 3 hours overnight uncovering the gap.
This one went wrong. See what happened before you try it.
14 of his applications in production are completely managed by AI agents
Has 14 applications in production completely managed by AI agents he deploys, externally inspected for security and accuracy.
An LLM cut 60,000 useless lines from his test suite and fixed bugs it found, in about 2 hours
LLM audited about 100k lines of tests, deleted about 60k useless lines, wrote broader scenario tests, and caught and fixed bugs, in about 2 hours.
The AI matched 242 files to her site by fingerprint and moved 288, deleting none
A creator's business folder was full of logos and images and nothing said which ones were still live on her site. Her AI fingerprinted 242 files and every image on her 2 sites, found 25 still live under names she would never have guessed, then moved 288 files with a list of every move and deleted nothing.
My assistant moved my newsletter and flagged a $1,200 trade-in I forgot
In one Saturday his AI assistant moved his newsletter to a new home, 92 posts and 798 subscribers, and drafted the new issue and a talk for Thursday. It also edited 10 versions of a vlog teaser, planned his 10 year anniversary trip, and reminded him about a $1,200 trade-in he had forgotten.
$1,200
Join my team Slack and keep up — but a summary took fifty minutes
Toby joined the agency's Slack group, announced itself and eventually sent messages through an explicit route after its first direct-message attempt failed. When a colleague asked for a PDF summary at about 4:24 p.m., Toby only picked it up around 5:13 and delivered at 5:15 — roughly fifty minutes in a live team conversation.
This only partly worked. Worth knowing before you try it.
Keep a review of hundreds of PDFs running while I do other things
The Slide Factory review cites a Reddit user who ran a document review covering hundreds of PDFs on a Dot over an extended period, asking unrelated questions and starting other tasks meanwhile. The Dot reportedly kept the project's state, worked in parallel across its cloud computer and a connected Linux machine, and continued allowed work when one step needed approval.
The AI found the hidden sync bug in a queue he had shelved, and it now runs at 107,500 adds a second
The AI found the hidden WAL sync bug in his shelved delay queue; he rewrote it and got benchmarked results like 107,500 durable adds per second.
Match 904 insurance documents overnight at my dental clinic
A South Korean dental clinic director with no IT training runs locally hosted agents that reconcile insurer payment records against clinic records line by line. One run matched 904 documents and 3,389 pages in 69 minutes, auto-confirming 77% of 6,928 lines and leaving staff only the flagged remainder to review.
I build tools for my kids' school in days, not weeks
He volunteers building tools for his kids' school and activities. Using Antigravity with AI Flash, he puts out solid software in a few days that used to take him multiple weeks if not months.
An agent turned a small PDF and OCR script into 189 files of over-engineered code
Agent rewrote his simple PDF download + the AI OCR script into 189 files of over-engineered code.
This one went wrong. See what happened before you try it.
Outbound system researches accounts and loads emails into Lemlist
He feeds the AI a CSV of company names and the system researches each account, finds the right buyers and their contact details, writes a four email personalised sequence for each, and pushes the contacts and emails into Lemlist ready for him to review and send.
The AI fixed a user's error while I was on vacation. The user got a free month.
A SimplePost user hit an error while the owner was on vacation with his family. The AI checked the logs, found the issue, fixed it, and drafted the explanation email in Gmail, and the owner reviewed and approved each step.
An LLM used his code editor's language server to fix a few dozen bugs in a Python rewrite
LLM used his LSP on a Python-to-ucode rewrite and fixed a few dozen bugs from interpreter/LSP errors (work deliverable).
Run my Marketplace selling: warn buyers about pickups and negotiate for me
The seller's the AI notifies buyers when an item is already scheduled for pickup with someone else, negotiates prices, and handles everything about the sale except meeting the buyer.
The AI built my StrivePay website, then burned 18,400 credits failing to fix its own errors
A reviewer paid the AI to develop and host his website, StrivePay, but hit repeated technical failures, broken functionality and exposed HTML errors; the 14,400 credits he received on September 25 plus another $20 for 4,000 more were consumed on repair attempts, and his refund request was refused on acceptable-use grounds.
This one went wrong. See what happened before you try it.
The AI recorded my product demo by driving my browser for me
She gave the AI control of Chrome through Warp and told it to learn the interface, click around, and leave key frames and an mp4 on her desktop. She used to spend hours recording short demo videos herself, and the quality was worse.
The AI rebuilt my website and store. I no longer pay Shopify $40 a month.
The AI rebuilt his website, his point of sale, and his online storefront. He no longer pays Shopify $40 a month, his site works better, and payments run through Square.
$40
Give the AI the Etsy shop — revenue triples in a month
Etsy seller Bianca Davis connected her shop to the AI through the ProfitTree MCP and let it optimize listings; her dashboard shows revenue rising from $45,585.33 in August (1,811 orders) to $136,755.99 in September 1–28 (5,433 orders).
$136,756a month
An SEO with no coding background shipped a SaaS with paying users, and turned his cross-model review habit into a second product
He has worked in SEO since 2009 and has no coding background. He shipped a SaaS with paying users anyway. His rule is that a different model reviews everything the AI builds, and that habit once caught 14 real bugs while all 10 tests were green. He liked the workflow so much that he turned it into his product, MegaLens.
The agent-built data pipeline he inherited was full of errors and its fixes made new ones
The agent-built data pipeline he inherited was riddled with errors and producing bad data, and the coding agent's fixes typically introduced new defects.
This one went wrong. See what happened before you try it.
The AI triages his user bug reports and tells both sides what happens next
The AI told to find a user's bug, decide user error vs bug, notify the user and tell the developer what to fix; the developer replied in 15 minutes asking if the fix was wanted today or Tuesday.
My agent built a web tool so our whole university can transcribe interviews in seconds
A university worker used AI to build a web version of a transcription program that used to need a special Windows machine reached by remote desktop. The new tool pairs a speech model with speaker detection on the university's own systems. Twenty minutes of interview audio now transcribes in 40 seconds with the speaker changes right, and students and staff can use it from a browser.
The AI’s test scheduler cut his release builds from a minute to about 3 seconds
The AI wrote a test run scheduler and migrated to nextest, cutting local release build cycles from 60+ seconds to about 3 seconds.
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.