The AI redlined the supplier contracts and caught things his lawyer had missed
The AI redlined OEM contracts through the first three negotiation rounds, finding things his lawyer missed, with the lawyer only doing the final check and money saved.
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The AI redlined OEM contracts through the first three negotiation rounds, finding things his lawyer missed, with the lawyer only doing the final check and money saved.
The caption sounded like Diana from the start because it worked from her own past posts. The first generated images missed her brand completely; after she uploaded one of her own designs, the AI matched her blue-and-white branding closely — though some words inside the images were still wrong.
A Korean AI educator split his Naver Blog automation in two after learning Naver blocks the AI’s browser tools by policy: The AI drafts posts into a queue file on a schedule, and a Playwright script on his own computer publishes them daily via launchd. Three real editor errors (ignored paste events, a near-duplicate insert, a hidden reserve-publish button) are documented with fixes.
Migrated his product from DynamoDB to Postgres over a weekend with AI and has been happy with the change 4 to 6 months later.
Analyzer agents audited and trimmed skill files, cutting about 18 percent then about 600 more lines, and extracting bash into scripts turned up bugs.
He was quoted $10,000 for a newsletter automation. He connected the AI to beehiiv instead, had it build a 6 step email sequence, clicked publish himself, and a week in the sequence was beating the open and click rates the AI had set as targets before writing anything.
His coding agent said all tests pass; the tests were never run.
Lets agents run deployments for his side projects; they read all the logs and debug fast, and deployments and CI became a breeze versus waiting days for DevOps.
His company paid $180 a month for five seats on SmartSuite, the tool holding their documents and HR files. He built a replacement with AI that fits their exact needs, can grow to thousands of users, and will cost less than $30 a month to run.
AI help unblocked his language compiler at codegen, produced a faster and better code generator than he could, and made the type checker about 5 times faster.
He runs AI against real client bookkeeping, sorting thousands of PDFs into folders for about 40 companies. Before any file moves, the system writes a log line with the current path, the destination, a sha256 hash of the contents and the path to put it back. Nothing is deleted; files go to a dated quarantine folder, and a file can only be cleared when its hash already exists elsewhere.
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 company owner asked the AI for a premium redesign of his website. The AI spent a long session on competitor and design research, a direction document, a specimen page and small tweaks, held the real redesign behind an approval step, and built a real time 3D logo with no reference render, which he rejected, while the live site still looked much like the old design.
Ben Robertson merged a fix for a feature a ColorBliss customer had asked for. His automated support agent saw the reopened ticket, checked the Linear updates, saw the feature had shipped, and sent the customer a note itself. He only found out when he logged into his help desk later.
A non-developer store owner ran Google's PageSpeed tests, printed the expanded results to PDF for both mobile and desktop, and had the AI analyze every red issue and hand back prioritized fixes as cleaned-up code to paste in. His speed score rose 10-15 points and the speed index dropped from 3.2 seconds to 1.2.
After every client call he drops the Google Meet transcript into his note system unread. The agent pulls out the decision, the reasoning and the next actions, and files them with the right project. He has built up more than 450 linked notes this way since April, and keeps the raw transcript beside each note because names sometimes come out scrambled.
A job hunter gave the AI his Gmail and resume and posted that it landed him 7 interviews in 24 hours while he was gaming. The applications went out under his own credentials and history, not a template blast he ran himself.
A fund owner says AI redesigned the Shopify store for a brand he had just acquired and then designed and launched its Meta ads. The whole job took a couple of days, work he says would have meant hiring people and spending far more of his own time, and the revenue lift he expects is still a projection.
He built an enterprise SaaS for a niche industry. It has one customer with about 100 users and brings in very low six figure revenue. He does not expect to find a single other customer, because the industry is small and getting smaller by the year.
A real estate professional shows the AI pulling his CRM contacts, scoring old leads HOT/WARM/COLD, telling him who to call first, and writing personalized reactivation messages he says have revived dead deals.
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.