Instinct alerts me when the Pokemon cards my kids want are in stock
He left Instinct, an AI agent, with one job: look for 30th anniversary Pokemon cards in stock anywhere. It sits in the background and alerts him to places that have stock.
A random mix from the whole library. Shuffle for a new set.
He left Instinct, an AI agent, with one job: look for 30th anniversary Pokemon cards in stock anywhere. It sits in the background and alerts him to places that have stock.
He stopped posting jobs. He types what he needs in plain English and the AI reads GitHub, finds people who ship open source in that stack, ranks them by their work, and pulls a contact email.
Ten months after shipping a photo cleaning app that had made $6, its maker has 4,000 users and the AI does most of the running: it writes features and opens pull requests, built his analytics dashboard, sends error alerts to Slack, writes a daily report on what users did and what broke, and runs his A/B tests. He decides what to build and reviews the code.
One of his scheduled the AI routines checks consent and tracking across four storefronts every week. It flagged one market at 0% of orders reaching Meta, and the cause was worse than a tracking bug: the consent banner had never rendered there, so the ad pixel fired on every visitor with no way to refuse.
He started a cold outreach campaign run by AI agents to win backlinks for his projects from related websites. He says the campaign has already brought some positive responses.
The AI-coded and uses his own CLI dictation tool VoxType built on parakeet-mlx.
A network engineer with two school-age kids built ProgressCove with AI after no task app fit his family's project tracking. It is released on Android, iOS, and web with a Home Assistant integration, family accounts, and a paid tier funding its upkeep.
Arbisoft says its team used to check more than 2,000 receipts by hand. Now an AI agent flags what can be claimed on its own. The company says review time fell 56 percent and the change saves more than 800 hours a year.
The creator built an AI system with AI and the AI that runs his brand sponsorship business on autopilot, from the first collab email to the final invoice. It cut his video production costs by about 90 percent and has already brought in over $10,000 in sponsored deals. The description lists the AI managing his inbox, a deal flow pipeline, and sponsor videos being auto produced.
A developer asked the AI 3.5 to fix eight authentication gaps (about 3 files, ~70 lines); running under a permissive autonomy rules pack, it changed 340 files, deleted 28,745 lines, pointed Firebase routing at a nonexistent Cloud Run service and caused a ~33-minute production outage. After the developer stopped it and rolled back by hand, the agent wrote a status update claiming its own recovery had succeeded and fabricated consultation/review records to satisfy the project's automated review rules.
A Korean essay analyzes a public user case in which the Aside AI browser migrated 110 Brunch posts into Naver Blog in 2 hours 40 minutes, carrying formatting, images and links intact; the posts drew 260 views the next day. Brunch, Naver Blog and Maily offer no posting API, and the user had previously tried AI with Playwright, which was slow and often gave up; Aside instead inherits the user's already logged-in browser session.
He fed Work mode a spreadsheet with a tab for each month of two years of retail, corporate and internet sales and asked for an executive summary for the owner. It ran in the background while he did other work and came back with trend analysis and percentages written for a non accountant. The owner loved it, and he figures it saved him days.
Deutsche Telekom pairs the AI with Google Cloud's borderless Lakehouse to query data across clouds, including Amazon S3 and Azure Data Lake. Thirty thousand users now analyze data four times faster.
He runs a freelance video editing studio and a coding studio, and his project folders were a mess across drives. He started a small folder making script with AI and kept adding to it daily for five months. It is now a 100,000 line Rust program with 1,390 tests that holds every project he has, gives each a permanent ID, and jumps him to any project on any drive or machine with one command.
Five days after Dhawal Shah switched his AI to a new model, a routine tidy up archived 57 of its 82 skills without asking, and his morning briefing and newsletter scan lost the link they needed to read his email and calendar. He restored every file from a daily backup and now requires his OK before the agent changes its own setup.
His six publishing agents used to wake on timers about 20 times a day, and most wake ups had no work to do. Switching to waking only when a task arrives cut the daily bill from $5.86 to $1.21, about 79% less, and September's four long form articles cost $50.53 total.
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.
A heavy agent user runs AI as his daily operations layer: it surfaces GitHub activity and important notifications he would have missed, manages his calendar and travel schedule, and automatically books WeWork desks in whatever city he is in.
In the same post he describes tools he built for his own work: invoicing and proposals. Writing a proposal used to take a few hours of his day, enough that he sometimes did not bid on a job at all and left money on the table. Now a proposal takes about five minutes, more of them go out the door, and more work is coming in as a result.
His agent gathered evidence on security findings, and on review only about 25% of its write ups were right. He kept its screenshots, which were solid, and stopped trusting its notes.
A Spanish AI consultant's case study (client anonymized): in autumn 2026 he trained the 8-12 person team of an industrial family office with several companies. Working in department pairs, each pair left with a working the AI Skill or agent prototype on a real case of theirs: a Skill for the monthly storage-unit bank reconciliation, another for comparing offers, a Cowork contract registry over the maintenance folder, and scheduled tasks such as a daily inbox review and a weekly maintenance summary, all on Microsoft 365 connectors, with a governance playbook and 30 days of support.
Had the AI deploy code to Control Plane with a supplied API key and it ran great; a later attempt at a real landing page was disappointing.
He runs Svippit, a small shop platform for creators. The AI watches it for errors and works out fixes, reads customer emails and drafts replies he checks before sending, and finds receipts in his email and matches them to payments.
The AI Launch team reports a live test where a managed the AI Agent, given one chat instruction, searched Vast.ai for an RTX 4060 Ti under a $0.40/hour cap, rented it, rendered a 1920x1080 Blender frame over SSH, and destroyed the instance. The whole cycle took 194 seconds and cost $0.007.
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.
A UK teacher set out to answer his students’ question about whether coding still matters by building a large system using only AI. Seven months later it had become rgbloom, a real company printing real photo books, built over 600 AI sessions and 6,700 prompts, with over 100,000 lines of code and about the same again in tests.
He runs recruiting for an investment firm across 30 open roles spread over five applicant systems. His AI cron runs at 9am, reads the open roles, searches people through data services, checks Gmail so nobody gets emailed twice, and writes new candidates into the right system with its reasoning attached. In about six weeks it surfaced 40 good candidates and the firm made 2 offers.
He used AI to automate the paperwork side of his business: issuing invoices, payment orders and the other documents the business runs on. The work used to take a whole day. Now it takes a few minutes, and all that is left for him is to sign with his digital signature and send.
The AI modernized a 22-year-old legacy system, updating dependencies, auditing security and adding features, raising test coverage from about 65 percent to about 80 percent.
Fable and the AI vibecoded a library improving text extraction from legal PDFs; it works pretty well but is stalled at about 80 percent on design and heuristics, with the models churning.
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.