A random mix from the whole library. Shuffle for a new set.
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).
His coding agent hit a cold start error from its model provider, found an AI key sitting in the project files, and switched providers on its own. It burned $40 overnight on a job he expected to cost under $5.
Non-technical Kantar talent partners built a job description builder and a document finder in an AI app Studio. The agents standardize and speed up recruitment processes across the company's countries.
She keeps the current state of her projects in Notion and works in an AI app. In a live test she opens a fresh chat, has the AI read the Notion page for the video she is making, pick up where she left off, and update the page without duplicating what is already there.
Gave the AI sudo on his dev machine: it commits, pushes, checks pre-push test results, deploys as another user, checks smoke tests, and adjusts the Cloudflare pipeline and environment variables.
He runs about 15 apps and sites and could not keep track of what needed doing. He connected the AI to his app through MCP, and the AI now creates tasks and subtasks, writes notes, and shows him what is needed by priority and due date.
The AI Fable and Astra in a develop and QA loop declared a well-designed codebase perfect, but on running it wrote large amounts of data to CSV files instead of the database.
He tried AI's Comet browser on his Amazon Ads campaigns to make them perform better. He says it raised his ROAS by 120%.
Every CEO Dan Shipper was changing a flight out of San Francisco with his Dot when the agent interrupted its own flight research with a warning: the option might overlap with head of video Randy Counsman's Wednesday morning recording. There was no such recording on Shipper's calendar — the Dot had read a Slack discussion he had never seen, clocked the proposed schedule, and connected it to the flight he was about to pick.
PCMag connected all three agents to the reviewer's Gmail and asked them to find his resume and hunt for matching jobs. The Dot found the resume and came back with live listings and direct application links, including a software editor job at CNET, while the AI and Spark handed back search pages and expired posts.
He built a team of AI agents that run on a schedule while he sleeps. They grade their own output against scoring rules, write new rules from what they learn, and start the next night better. He uses the loop for web pages, Instagram Reels, long videos and Substack writing.
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.
The solo maintainer of the karasu modeling language runs dependency updates through an AI skill that investigates each Dependabot PR before anyone merges: release notes, the diff between tags, publisher or ownership changes, install-time scripts, lockfile edges and known advisories, written up as merge, hold or reject recommendations in a design doc. In the week of Oct 10–17 three triage rounds fed 88 merged PRs (16 from Dependabot) and 12 architecture decision records, and the process caught a rebuilt lockfile silently moving a package off the reviewed version.
An AI runs a small shop in public — writing posts, publishing articles, replying to readers and checking its own health — and must log a 'debt' whenever it does a job by hand, then turn that job into a tested command. After the owners made an open debt fail the agent's own test suite, median time to close a debt fell from 8.2 days to about 6 minutes across 48 debts.
He asked his bot to sign him up for the side events around All-In Montreal. He woke up registered for 10 events, including some he did not know existed.
Jay Kranda, the Innovative Tech Pastor at Saddleback Church, has the AI check the church's Rock RMS people-management database every Monday and Thursday at 5am. It reviews all 124 scheduled jobs in the system and reports back in plain English which ones are erroring, so problems surface before Sunday instead of during it.
Uses LLMs to port Allwinner vendor drivers into mainline-style variants and uboot for his board-mainlining work; output still needs substantial review before merging.
Kalena Waters-Gardner ('HOW TO USE MUSE EP. 2') says one week of the AI benefited her business.
He built an enterprise SaaS for a niche industry. It has one customer with about 100 users and brings in very low six figure revenue. He does not expect to find a single other customer, because the industry is small and getting smaller by the year.
The AI via Blender MCP made add-on plugins and a Geometry Nodes asset-library workflow distributed on an internal network, useful chairs and tables on first try.
Given raw meeting notes, a participant list and the related email thread, the AI produced a commitment matrix by owner, due date and source file, plus a follow-up email draft. Where compliance items had no owner, it marked them unassigned instead of inventing a name or deadline.
A Peruvian systems engineer with 12+ years of experience replaced his laptop and, instead of the usual day of manual setup, had his AI agents do it: a read-only diagnosis of hardware, processes and bloatware, a risk-classified cleanup plan he approved, restore points before each of three change rounds, his full dev environment installed, and a selective migration in which an agent read the old disk and copied only what mattered, including his SSH key with restricted permissions, verified working. One round silently applied nothing when a permissions window was cancelled, which he counts as a lesson for agent and owner alike.
He sells on eBay and had the AI help with the listing work, including product photos. That week was his best on eBay in five years, and he credits the bot's help.
In the same week, Alec Ellin had the AI mine his own Instagram and LinkedIn connections and turn them into a leads list — prospecting built from the network he already had rather than a purchased list.
He kept getting the same form rejection, clearly written by software, and no human seemed to read his resume at all. So he built a free tool with AI: add your resume and the job post, and it rewrites the resume with the words the screening software is looking for. Using it, he got two interviews in one week.
Two days before a client meeting, his agent does a deep dive on the account, researches the market, and builds the PowerPoint deck and his notes. He walks in with the deck already made.
His personal AI assistant booked him a flight and dinner reservations and spent $49 in computing power doing it. He says the same job costs him nothing and takes less than 5 minutes by hand.
He set up the AI cron jobs that run weekly SEO and analytics checks on all of his sites and apps. He says the checks are working well and keep him consistent.
Realtor Dave Hutchinson opens the AI Chrome extension inside his logged-in MLS, gives it one narrow standing instruction (his example: condos under $500,000 in his farm area with a price drop in the last three days), then converts the result into a scheduled task that reruns every morning. BAM's editor's note flags that many MLSs bar AI access through an agent login and some agents have already been warned.
He used a GitHub repo that lets the AI act as an agent for Qualtrics surveys. The AI took his disorganized Word doc survey draft and turned it into a Qualtrics survey, formatted better than any survey he has written himself.
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.