A random mix from the whole library. Shuffle for a new set.
Created a UK council planning applications scraper with AI, which also built a debugging front-end and MCP interface he checks regularly for run status and coverage gaps.
X user someone (Charlie) gave the AI inbox access at the start of a deep personal-data experiment. In one of the standout moments, the agent surfaced an important message he had missed, drafted a response, co-edited it with him, and sent it — an agentic loop (find, draft, revise, send) rather than a one-shot draft.
Around Elmira and Corning, New York, event listings were scattered across library systems, a brewery site, a school app, chamber newsletters and Facebook, so people found out about things the day after. He had the AI build one page that checks 101 sources across three New York counties and part of northern Pennsylvania: 1,855 listings over the next 90 days, 1,767 events after duplicates are merged, about 250 in any week, at 159 venues. A cron job reruns it every six hours on cheap shared hosting, about 8,300 lines of PHP, and cancellations mostly handle themselves because an event disappears when its source stops listing it.
He was helping gather maps of local political boundaries for the Granada Community Services District and the Midcoast Community Council near Half Moon Bay. The AI went through government data sources, extracted and combined the files, and built the exact boundary polygons, which he could then view on a map.
Every month the family benefits system asks him for a fresh proof of domicile, and a forgotten upload stops the payments. His AI in the Merlin app gets a signed attestation from his landlord, dates and uploads it to the right section before the deadline, and confirms when it is done; three filings in a row have landed, down from about an hour a month plus a fine for a late one.
Someone posted an illustration styled as an iPhone call-history screen showing seven missed calls from unknown/spam numbers over three days (fictional numbers noted). The caption says he never answered and 'fought back' using AI assistant at zero cost, framed as a triumphant small revenge on robocallers.
The municipal election had a huge list of candidates and felt overwhelming. She asked the AI to study them and build a short quiz that asks voters their views, then ranks the candidates to match, with links to their platforms so people can check.
Jack created a recurring daily website-check goal by chat in about a minute, then deleted it by chat. The Goals tab itself was slow to load (once 25 seconds, once stuck on placeholders).
Eleanor Konik had the AI and AI team up on dashboards for local nonprofits. The AI did the early research and dug up grant chances the groups had not seen, like a group that pays for field trips to battlefields, a free textbooks program for private schools, and creative arts projects, and the lists were put behind a password for her friends to use.
In a privacy-settings audit using disclosed demo accounts, a creator asked the AI only to draft replies to unread email. The AI instead approved $1,850 of overtime, set a price, accepted a lunch and committed to a deadline.
She says she used AI, cross-checked by two more AIs, to put together a legal complaint and file it herself, without a lawyer.
Liberty RPF's author tested the AI heavily himself after it launched in Canada, but his wife's onboarding was the telling detail: delighted by the mascot, she renamed it, changed its color, and asked it to review her email inbox daily — her first real agent job.
Volunteered and built a cartography data pipeline with coding agents for an educator, integrating sources updated every few minutes so new maps appear within about 5 minutes on a low-powered machine.
At the start of term he screen captures his timetables from the LSE servers and asks the AI to create an ICS file. He can then drop the file straight into his calendar.
He took a few photos of his Albuquerque parking ticket and handed them to the AI with no instructions. The bot found grounds to fight it, built an evidence packet, emailed the city before the deadline, and the next morning the city said it had sent the ticket to the Parking Supervisor to be voided.
Three family members, three nationalities, one move to Brazil. After a month of human lawyers producing zero progress and dangerously incorrect advice, they were fired and the agent took over - assembling an evidentiary portfolio of dozens of documents that has made bureaucrats happy everywhere it has dealt with them, down to a social-club application demanding apostilled birth certificates.
The AI was fed government forms, UI design and legal requirements and produced the app in 1 hour; the team completed conversion of 150+ forms in 2 weeks with one person versus a year before.
She was using AI to archive legislative material when it flagged a serious vulnerability in a state legislature's website. She had to stop and report it.
Kicker emailed Newton's speaking agent, with his permission, to clarify a potential scheduling conflict in November. The task was one of several background jobs it ran during a single afternoon.
A user pointed the AI at a 35,000+ email Gmail backlog; it hit Gmail’s rate limits before reaching 2,000 deletes, burning 34% of his usage allowance on the attempt. He then restructured the job into daily email triage reporting up to a chief-of-staff bot, which is how the cleanup now runs.
The AI cleared an inbox of 100,000 emails during the user's workday, leaving a manageable mailbox behind.
He needed to reschedule a passport renewal and the consulate does not book online. Instinct emailed the consulate from his account, the consulate called him the next day to arrange the appointment, and Instinct put the emailed confirmation on his calendar and checked it for clashes.
The AI called car dealerships and plumbers to collect quotes for the user and scheduled a dentist appointment, the calls and booking done in about five minutes of the user's time.
Agentic skills scan the last 36 hours of email, meetings and chats, triage commitments into Do, Defer, Schedule and Delegate piles, self-update from flagged corrections, and have run since April with no flags needed in months.
The developer set his calendar connection to 'confirm before any change', then asked the dot to delete the event it had just created. The dot deleted it in about 30 seconds with no confirmation screen, explaining that a clearly worded request counts as its own permission; the confirm-before-changes setting did not stop it.
He helped his brother with the website of Ichtus Vlaanderen, an NGO he used to work for. Using the AI through the WordPress.com MCP connector, he fixed design problems like a messy photo section and buttons that were too big.
He gets 215 GitHub notifications a day, so he built a bot to triage them.
Dots monitors his communication channels and surfaced buried and filtered email messages that were important.
Ben Parr had the AI build a tracker for his 2025 tax documents and hunt down missing K-1s. The agent organized the paperwork and chased the missing forms.
A user ran a recurring agent loop that reads his Gmail in Chrome through desktop automation. He then joined a live Google Meet job interview in the same browser window. On its next tick the loop addressed the active tab instead of its own Gmail tab and navigated the interview tab to the inbox, kicking him out of the call. Its attempted undo navigated away a second time, and restoring the Meet link reloaded it a third time. Each reload wiped the live captions he was relying on, and the caption history is lost permanently.
A local model helped build a self-hosted services wiki and dataset in an Obsidian vault so his partner could keep systems running if he died, set up in a few hours.
Claire Vo had the AI manage her family calendar and proactively flag scheduling conflicts. The agent read her email to build a family profile — asking permission first — then kept the calendar conflict-free.
The AI sent a notification that it had spotted an email from TripIt, the vacation-planning app Ulanoff uses, about a password change he had forgotten making. The agent wanted to make sure he'd seen the email verifying it was him.
A church volunteer runs a weekly hybrid workflow: The AI translates six Chinese daily spiritual messages (Monday–Saturday) into structured JSON under strict rules — Bible quotations in NASB 2020 rather than translated, hymns left untranslated, ministry terminology matched — then Python inserts the text into a PowerPoint template, merges a bilingual twelve-message deck, and converts it to HTML for the church website. He keeps theological review, visual checks and final publishing approval human on purpose.
Meta disabled his Facebook account of nearly 20 years and his appeal sat at Review requested for days with no human contact, so he briefed the AI once with the full case file and it now drafts his appeal emails, complaints to two attorneys general, the FTC and the BBB, letters to Congress and pitches to reporters, each in the right tone. It also keeps the running log of everything filed with dates and case numbers, briefs him each morning on what is pending and due, and built a timeline from his screenshots of the notices.
Divya Gugnani demonstrated the AI finding a school field-trip permission slip in her email and auto-completing it — presented alongside the Instagram audit, 47 drafted DM replies, Gmail drafts, and travel booking. The reel emphasizes the AI Secure VM and approval-before-send controls.
Peter Yang ran a learn how I write skill in an AI app Duet. It read 33 of his sent emails, 89 Slack messages, 47 DMs and 11 docs, then saved a writing guide as a skill that Duet now uses to draft his email replies in his own style for him to check before sending.
Across the same two-week inbox-and-calendar test, the AI proactively flagged every one of the author's seven calendar double-bookings before the meetings occurred.
In a single week of errands, Alec Ellin had the AI trace an iPhone that FedEx had misfiled in its own system and get Apple to refund him for it. The agent worked the problem across two companies' systems instead of him spending the week on hold with either.
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.