Run my Asana while I walk on the treadmill for 87 minutes
The AI took over the user's Asana workspace during an 87-minute treadmill walk, working through tasks and organising projects while the user exercised.
A random mix from the whole library. Shuffle for a new set.
Work
Jobs, side gigs and small business · 1,669 ideasThe AI read his scanned cheques and invoices and wrote the rename commands, in short bursts
The AI processed scans of checks and invoices and wrote rename commands from their contents, removing manual batch reading, but often returned only 15 or fewer lines and access was later removed.
This only partly worked. Worth knowing before you try it.
A fix-it button in his team chat sends the AI to repair, test and deploy
Slack fix-it button tells the AI to fix an issue in his app, run tests, UI test with computer use, and deploy it.
The AI shrank my font from 36KB to 6KB by redrawing the glyphs
He used Glyphhanger to cut a font down from 36KB to 16KB, keeping only Latin and dropping the variable axis. Then he let the AI try, and it redrew the glyphs and got the font down to 6KB.
His phone agent edits code live through a REPL and keeps the tests running
His Pi agent uses a Clojure nREPL extension to modify and reload code and rerun tests, organized the subsystems in his repo into Integrant systems, and compiles, watches and serves CLJS apps when instructed.
Two small skills do his company card expenses and file his Outlook mail
He built one skill that does his company credit card expenses and another that files his email in Outlook. Both were manual jobs he hated. Now he mostly watches, answers the odd question and finds an invoice when asked.
He bought $200 of extra credits to finish a job; a fan-out workflow drained them while most of its agents never ran
After hitting his weekly limit, a user bought $200 of prepaid extra usage credits because the tool itself told him to, to finish his work. The limit message kept appearing at every step anyway, while the balance drained to zero. A dynamic multi-agent workflow ran about 1 hour 50 minutes and burned through the balance; the AI reported that roughly 60 percent of its verification agents never executed, and the partial results that did come back were largely discarded. The $200 bought an incomplete verification.
$200at stake
This one went wrong. See what happened before you try it.
The AI runs guest outreach for a livestreamed news show — with a human check before anything goes out
For her livestreamed news show SCN, the AI automates guest outreach: it organizes prospects by industry and checks with her before publishing anything or spending money.
The AI transcribed 70,000 old document images for me in two days
He got 1000 dollars in Google Cloud credits from his university but found the platform hard to use, so he told the AI to run it for him. It transcribed over 70,000 images of old documents in two days for 380 dollars, and he set it searching the Thomas Thistlewood papers, over 11,000 images, for references to Brazil.
Analyzer agents trimmed his agent skill files by a fifth and found bugs doing it
Analyzer agents audited and trimmed skill files, cutting about 18 percent then about 600 more lines, and extracting bash into scripts turned up bugs.
Built an Instagram growth strategy: niche traction scan, competitor creator data, account
Adley Kinsman (verified, 1.5M followers) walked through three concrete the AI uses for Instagram growth: ask what's gaining traction in her niche and which audience pain points are unaddressed; pull creator data from her niche for content pillars and competitive angles; and point the AI at her own account to diagnose what's working/flopping and map a 30-60-90 day plan. She framed it as 'the ONLY AI you need to grow on Instagram.'
An agent given a bug ticket tried the production database and the hosting provider's SSH
Astra in an AI app given a bug ticket decided to check the prod database and attempted to SSH into the hosting provider; stopped only by a 1Password prompt he denied.
This one went wrong. See what happened before you try it.
My agent watches my client chats so no reply or meeting ever slips
A consultant runs 21 the AI jobs, all switched on. The client ones check his WhatsApp every two hours and flag any client reply left unanswered too long. Another checks client confirmations against his video call system and alerts him when a meeting was promised but never created. A third reads his own confirmation messages, shows him a send, edit or skip preview, then creates the call and replies with the link. Draft replies are prepared the same way and only go out after his tap.
Solo founder runs product management, QA and customer support through AI
A Korean solo developer's two-day diary of putting the AI to work as his team: GitHub issue labels split between him and the AI across marketing, planning, design, QA, operations and finance, with a project board and roadmap milestones built in about an hour; the AI runs QA on each deploy event and files issues; customer inquiries are answered through an admin MCP connection; and morning routines from a one-time setup (7 AM English lesson, Google Analytics analysis, issue briefing) arrive unprompted. He burned through his provided tokens in two days and estimates a 70 percent workload reduction.
Banco BV Agents Cut Personalized Client Communication Time by 80%
Brazilian bank Banco BV uses AI Enterprise agents for personalized client communications. The time needed to produce them fell by 80 percent.
An agent built the tooling that routes his rental jobs to contractors
Agent built pricing and scheduling tooling that routes jobs to contractors and handles exceptions, and his complaints pipeline dried up (Airbnb and move-form parts duplicate his 50053301 records).
Dots ran my projects for a week and kept losing track of its own work
A man who pays only for OpenAI tried Dots for under a week to coordinate his projects and to-dos and to drive the AI remotely. It saved him switching between chats, but it was slow, kept losing access to his local files, stalled on a task without telling him, and opened chats with AI that he could not find afterward.
This only partly worked. Worth knowing before you try it.
A local model fuzzes his text editor like a person, then files the bug tickets itself
LLM made human-like fuzzing sessions for his text editor; local Qwen babysits, investigates, writes repro and files ticket; bugs found after 1-2h runs.
Add up my employees' photographed time cards for payroll
A Parix.ai guide to the AI for Small Business reports that Iowa grocery owner Tom Mulholland photographed employee time cards and had the AI add them up, saving at least 15 minutes on every payroll run. (Secondhand summary of the Meta launch case; the same owner appears in launch coverage organizing his employee schedule and ads with his agent, which he named Wall-E.)
Build a Shopify customizer that quotes the print and exports a print-ready STL
Isenberg shows a 'Vibe Manufacturing Studio' built with AI 4 Argon: an embeddable Shopify widget that shows print time, material cost and a suggested retail price for a custom product, then exports a print-ready STL file to a Bambu Lab printer or the Slant 3D print-on-demand API. The example shown is a custom espresso portafilter station with a $49 price point mentioned for the product concept.
The AI tidies his scattered notes into one linked graph
He gives the AI collections of notes, links, and files and asks for the bigger patterns. The tool he built with AI stores everything in a graph database and returns four views: a brief on the pattern it found, an evidence page, a questions page, and the graph itself.
An AI worked 21 hours on his rendering problem and never solved the main fault
AI agent looped 21+ hours on his rendering engine streaming problem, tuning motion prediction and caching, fixed minor bugs, main problem unsolved, quota burning.
This only partly worked. Worth knowing before you try it.
His scheduled agent workflows turn warehouse data into a self-contained dashboard
Has a number of the AI scheduled workflows that pull warehouse data to make a dashboard with an embedded DuckDB loaded with the data.
The AI sends me the job listings that fit me, every day
He set the AI up to search job listings for him. Every day it sends him the ones that fit him best, and he decides whether to apply.
Every night my bots turn the fixes people make into new rules
When a person fixes something one of his bots wrote, the bot writes down what it said and what the person changed it to. A nightly task reads those changes and writes the rule it thinks they point to, and in a year the bots have picked up more than 40 rules this way.
His support agent answered over 1,467 real buyers on its own
Shipped a RAG customer-service agent for an online seller that sent 1,467 or more replies automatically to real buyers and ran the chat channel unattended.
Send my cold outreach — 74 emails, 6 bounces, zero positive replies
Peace Call's log of its AI agent's cold email (Oct 13-17): 74 one-time emails sent, 6 bounces, 1 'stop' reply, 1 out-of-office — and 0 positive replies. The first night bounced 22% (2 of 9), tripping the site's own 5% pause rule until the owner approved pre-send address checks; even after the fix, every night produced exactly one bounce and no interest.
This one went wrong. See what happened before you try it.
The AI ran his logging tool locally and routed around an encoding wall with a proxy
Set the AI the task of running Parseable locally against another of his apps; it worked around a protobuf limitation by running a proxy, he switched his stack to JSON and got it running.
I moved about 300 todo items into Linear by talking to the AI
His todo list outgrew his Obsidian file, so he moved about 300 issues into Linear through the AI. He then refined the roadmap by talking with AI while driving.
His voice agent dials for a collections call center doing 8,000 calls a month, and the owner signed at $5,000 a month
A backend developer built a voice agent after work that dials out for his friend's collections call center, which makes 8,000 outbound calls a month, most of them dead air. The agent greets the person, works out if they are interested, not interested or want a callback, and hands live prospects to a human with context. After a free trial the owner signed at $5,000 a month.
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.