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Work

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

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.

Turn construction plans into a priced remodel estimate in about 10 minutes

A contractor coach shows his working takeoff system: he uploads construction plans into AI, which reads every sheet, note and finish item against his existing JobTread cost group of rates, markups and formulas, cites the sheet behind each quantity, and produces a bathroom remodel estimate of about $44,000 at a 46% margin in roughly 10 minutes. The conversation is saved as a reusable skill, with guardrails to show numbers before writing and stop on contradictions.

WorkPartly worked

Fix Meta Ads targeting lookups that the AI’s MCP cannot do

A poster in the showcase hub built two the AI skills that fetch real Facebook targeting IDs for the Meta Ads MCP, which cannot fetch them itself. End-to-end testing caught the first version silently dropping 25 of 135 valid targeting options, including the highest-intent behavior.

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

Every 30 minutes it picks the top open issue in my repo and leaves a draft pull request by morning

A builder runs AI as a night shift for his side project. Every 30 minutes, around the clock, it checks the project repo for open issues, picks the most important one, spins up a coding agent in an isolated worktree, and always ends the same way: one draft pull request waiting for his review, one task at a time. He wakes to a progress report at 8 am and reviews code before he is fully awake. The same post describes hourly inbox ranking and Monday briefings; only the repo case is recorded here because the rest is a generic digest shape.

His server agent reads Google Ads at 6 AM and tells him which campaigns burn money

Polish marketing freelancer Damian Nowaczek runs AI agents on his own server: every day at 06:00 one pulls data from his Google Ads accounts, compares performance and sends a report with conclusions to the company chat, so he never opens ad dashboards to spot a campaign burning budget. A second agent scans new public tenders daily and picks the marketing-related ones.

The AI edited my whole video from one raw clip

He dropped his raw clip into AI and it did the edit: it cut the stutters, pauses, and ums, and added zooms, sound effects, captions, and animations. He says the finished edit was the AI’s work, not his.

WorkWent wrong

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.

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.

Run a marketing operation on 8 scheduled the AI tasks — and test the cloud move before it is forced

Charles Summers runs his demand-generation work on the AI: 8 scheduled tasks that drive HubSpot, Search Console, Gmail and LinkedIn through Chrome, backed by 578 local sessions and about 220 memory notes. Ahead of Anthropic's October 6 cloud switch he audited every task, backed up 7.9 GB of sessions, and ran a 14-point cloud readiness test — 13 passed, including a live HubSpot API call, and the one 'failure' was Cowork asking before deleting a file, as designed.

WorkWent wrong

The AI sent 13 emails to a public mailing list when the job needed 3

A developer let the AI submit a two patch series to an open source project's public mailing list, a job that takes 3 emails. The AI sent 13, retrying with different formats under his name after the first copies came out garbled, even though the project's rule to always use git send-email was already in front of it. The extra 10 could not be taken back.

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

I built my client a live dashboard in a day with AI

He built a client performance dashboard in a day with AI, pulling four APIs into one live page for a natural stone company that takes enquiries online but gets paid weeks later, offline. He labelled the big number enquiry value, not revenue, and changed the page the same day after the client saw it.

His agent keeps its own handover notebook; he just says 'remember that' after each mistake

The operator of a small Japanese company has used AI daily for three months across quote tooling, documents, internal pages and accounting help, and never edits a file himself: after every failure he tells the agent in chat to remember the lesson, and the agent writes it into its own handover note and memory (now 250+ memory entries and a note past 1,000 lines). The scars are specific: work built under the wrong account, duplicate tool instances breaking half the controls, and aggregated data lost to a 30-day chat retention setting.

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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.