Agentic workflow ingests files from a complicated program, parses and loads them to a database, spawns agents that reconcile hundreds to thousands of items in flight and reach out to people for clarification, catching mistakes in real time, replacing a 500 dollar per hour service.
A monthly client report that used to take most of a morning now takes less than half that. One the AI skill and one read only MCP server pull from Phoenix, Sentry and the product database to make it.
Concur's AI booked a man's flight but read his European passport wrong and put his birth date down as the 1st of the 18th month. The flight ended up booked with the wrong birth date.
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A self-published author says the AI, his personal agent, made every cover, flipbook and promo for his 7 books that are now live. The post carries his AI referral code, so he and readers who sign up both get tokens.
A creator shows the system now running his Threads presence: a folder holds his rules, plan and log; the AI reads his real posts to learn his voice, plans 15 days, drafts every caption from a source post, checks each against his rules and schedules one post a day in Metricool. A weekly Monday check keeps Metricool and the folder in sync, and the video's test mode puts two real posts live within minutes.
In 'Using the AI for Business' Ep. 1, the AI researched Etsy's best-selling Wix website templates using real sales numbers, identified the winning niche and delivery method, and planned a resellable template product line for Jackie (the build itself is Part 2).
He told his AI dots assistant, Teto, to earn the $200 a month he pays for it by selling things before his November 6 renewal date. Teto made a pack of animal reaction images and got it listed in his Ko-fi shop for $2, but by October 24 the shop still showed zero orders.
This only partly worked. Worth knowing before you try it.
A teacher asked the AI to make a presentation from her pacing calendar. She exported it as a PDF and uploaded it to Wayground, where it became a lesson with interactive questions and extra practice problems she can add.
A perpetual the AI thread in his llama.cpp checkout periodically sweeps PRs and research, rebuilds llama.cpp, benchmarks, finalizes upgrades and verifies which model and variant to run, sometimes committing its own optimizations.
He is job hunting in tech, aiming at startups and big tech. He gave the AI a list of up to 100 target companies, target roles, and his filters: salary range, posted in the last month, locations, industries to avoid, and sub rules like roles that do not need past experience in that exact title. Twice a week the AI sweeps the list and brings back matches. He reviews each role, tells it which were bad and why, or that he applied, and it sharpens the filters for the next run. He says the matches are strong and far quicker than scrolling LinkedIn Jobs. It cannot submit applications, and no interview has landed yet in the post.
In someone's weekly 'what my AI got wrong' log, the AI let the content queue run completely empty, so a scheduled morning post was missed — and it never warned the creator the queue was running low. The fix was a standing alert at four remaining posts; the same log notes the AI opened a follow-up email with an all-caps 'I'M SORRY', a phrase the creator never uses, until corrected once and the rule written down.
This only partly worked. Worth knowing before you try it.
An Instagram business operator uses AI as a sidekick: reading insights (reach, audience hours, why a reel flopped), publishing posts/reels/stories with drafted captions, competitive intelligence on rival accounts, scanning comments for discount-code/restock/shipping questions to hand over as warm leads, plus a scheduled daily report on what people say in the niche's comments.
At RL Electric, Maricruz prepares proposals and used to count every symbol by hand with PDF markup tools across dozens of plan sheets per bid, where one missed symbol could throw off the price. Quotr.ai's AI now recognizes and counts the symbols directly on the electrical plans; she verifies and adjusts the counts, and the hours that went to symbol-by-symbol tracking now go to bid strategy.
Creator Pratibha cancelled ManyChat ($29/mo) and plugged the AI into her Instagram instead. The AI drafts every comment reply and DM in her voice, she reads and taps approve, and it sends — clearing in under two minutes a batch that used to take her an hour every morning.
A user asked the AI to build a multi-agent outreach pipeline. The code it generated retried failed calls forever, re-billing the most expensive call in the system on every run. The spending guard it wrote only slowed spending down instead of stopping it, and the daily ceiling it picked reset every day, so the charges accumulated to roughly $50 of unintended OpenAI usage before he noticed.
$50at stake
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Creator Alex Finn recounts on a podcast episode that he gave an AI access to his business inbox and told it to answer and negotiate with legitimate companies. Within about four hours it had researched market rates and closed its first sponsorship deal, worth $10,000.