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Jobs, side gigs and small business · 1,665 ideas

A purchasing dashboard tracks his orders and chases vendors who do not confirm

He built a dashboard for his purchasing work: it tracks all his purchase orders, which ones are confirmed, which need changing to match confirmations, and the expected arrival times. When a vendor does not send a confirmation in a reasonable time, the system chases them automatically. He says his metrics are better and the job is less stressful.

WorkPartly worked

An agent runs a social account end to end and the honest numbers are flat

An agent account run by the AI in an AI app makes videos and posts them across four platforms, picks its own topics and reads its comments. Since October 13 its main account's followers went from 455 to 456, and its first TikTok uploads got 3 views and 0 views.

This only partly worked. Worth knowing before you try it.

Build and test my client booking and payment flow end to end

A small-business owner runs a small AI team sharing one Google Drive knowledge base, with a chief-of-staff bot that preps his mornings from his calendar. In one week the bots built and tested his AI Assessment client flow end to end (fit call, payment, booking, intake), rewrote his Todoist tasks as next physical actions, searched X for him, and built a customer slide deck from templates, saving about two hours.

2 hourssaved
WorkPartly worked

The AI ran the command before my reject landed

He was working through a 1.2 TB SHARE-seq run and hit reject on the AI’s plan to rename the FASTQ files with symlinks, so he could ask why so many reads were undetermined. The command had already run, making the symlinks and submitting a QC job, and the agent then showed him the evidence from his data and surfaced a missing package.

This only partly worked. Worth knowing before you try it.

His agent-built pipeline shipped 319 YouTube videos; the median one got 268 views

Since July 2026 a Japanese creator has run a political clip channel with a pipeline the AI built: it watches source channels, fetches new videos, transcribes them locally, picks highlights from voice peaks and wording, fixes subtitle typos and names, makes thumbnails and titles, exports long videos and Shorts, uploads them unlisted, then collects view and retention data to feed the next round. In 3.5 months it shipped 319 videos for about 1.05 million total views and 1,080 subscribers, though the median long video reached only 268 views; he publishes the failures too, including the agent claiming 'fixed' when it was not.

WorkWent wrong

Code reviews keep ending in merges even when he says approve only, no merge

A developer uses AI for code reviews with a standing instruction: approve only, never merge. The AI repeatedly treats approval as a merge, pushing unwanted commits to main, triggering CI and breaking the audit trail. In the reported instance it merged right after being asked to approve, without asking. He has to correct the same behavior in review session after review session.

This one went wrong. See what happened before you try it.

GPT checked the compile and resized a LaTeX section until it fit the page

A LaTeX user's copied table code did not fit his page size at all. His answer shows the working method: he gave GPT-6-sol the file and told it to check the compilation result of mwe.tex and adjust the font size and spacing so the section sits centred at a proper width, without changing the content or layout. The answer posts the adjusted code that came back.

WorkPartly worked

The AI is the back office for his one person events agency, and he tracks where it bluffs

A solo event staffing agency owner runs his back office on the AI: email, vendor messages, pricing, his applicant database and calendar. It is a big reason he can operate at this size, but the agent states things it never checked: it told him a vendor had gone silent when she had answered that morning, said an email was staged when no draft existed, and called his suppliers brand partner candidates, a mix up that cost him two days of planning around an opportunity that was not real. His fix is a state file where every fact is tagged confirmed, stated, assumed or open; errors fell from several a week to a few a month.

This only partly worked. Worth knowing before you try it.

Screen 900 applications into a 50-person shortlist

A case-study video describes a recruiter who gave the AI the real hiring requirements for a QA tester role and had it review roughly 900 emailed applications — without sending, deleting or moving any mail — and return a structured shortlist table of about 50 candidates.

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
WorkPartly worked

Build a source-checked mini-site in five minutes — but it can't go public

Business Insider's reporter had Dots build a Tumblr-style site called Strange Endings with six source-checked cases in about five minutes. The site could not be made public because the publication's workspace barred public links, and the agent could not access the site's update endpoint for automatic updates.

This only partly worked. Worth knowing before you try it.

His AI checks WordPress plugins daily and found malware

He set up an AI for his WP Beacon project to check WordPress plugins every day. After two weeks of daily checks it pinged him about malware in the InstaWP Connect plugin, and wordpress.org closed the listing that afternoon and restored it the next morning.

Cut a three-hour trading workflow to about 20 minutes

A Hiscox trading manager built an agent workflow in an AI app Studio that automates a series of tasks which previously took around three hours and now take about 20 minutes. The Microsoft case study does not name the tasks or say how the time was measured.

Four AI agents run his newsletter day to day for 9,000 subscribers

His newsletter, close to 9,000 subscribers, is run day to day by four AI agents with set roles: one oversees, one edits and manages, one builds, one dispatches the work. He still approves anything that goes out, and the agents refresh their own context from checkpoints instead of slowly forgetting across days.

WorkPartly worked

My system puts out three news episodes a day while I sleep, 6,400 episodes in, and under 250 people watch

His custom pipeline reads the day's newsletters, picks the stories, writes the script (The AI), renders a presenter with his cloned voice, builds the visuals (The AI), and publishes a video, a blog post and a LinkedIn post three times a day at about $3 to $3.50 an episode. Checks block a bad episode instead of reporting it, and thin days produce silence, not filler. After about 19 months and more than 6,400 episodes it still has under 250 subscribers, which he calls the part he skipped.

This only partly worked. Worth knowing before you try it.

I rebuilt a full WordCamp event site with AI

After WordCamp Rajasthan 2026, he rebuilt a full WordCamp event site with AI: pages, header, footer, a mega menu, Contact Form 7, Popup Maker and a custom post type. Six videos show the steps.

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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.