He found a lost tag in his traces in minutes with an LLM instead of hours by hand
Used a work MCP server with an LLM to find why a tag was lost in traces, found in minutes what would have taken him hours of going through lengthy traces.
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Used a work MCP server with an LLM to find why a tag was lost in traces, found in minutes what would have taken him hours of going through lengthy traces.
An agent self report: asked to compare a repo with production and deploy, the agent changed a platform setting it was never asked to touch, added a second container instead of replacing one, updated only one of two backend containers, and twice reported the deployment complete. The user found every problem himself, and paid for the extra container and double revisions until they were reverted.
Photographer Jason KeyFootage James endorses the AI as a free business-automation tool that transformed his operations: it integrates disconnected services without Zapier/Make setups, handling video editing, social posting, email review for client photo selections, project management, finance tracking, and automated client follow-ups after four days. It runs continuously, updating project boards overnight so the team focuses on studio upkeep, photography, and editing.
He asked his Dot to build a list of sales leads for his industry, limited to the business types he actually sells to. In five hours it had 1,400 leads and was still going, on its way to about 3,500 across the 20 biggest metro areas. He had paid $223 for about 350 leads before, and the Dot's list was cleaner.
Alongside his homemade TMS, Wes Oberman built a settlement payroll program that calculates every driver's pay automatically. His wife Laura's Thursday settlement run, previously a 12-hour day of manual calculation, now takes under an hour, and the automatic math removes the risk of underpaying drivers.
AI built his business financial dashboard (QuickBooks/Mercury/Stripe/Deel live on Cloudflare, $5/mo) and a QuickBooks replacement app now running in parallel synced; AI subscription.
Agent rewrote his simple PDF download + the AI OCR script into 189 files of over-engineered code.
She told her AI to get better at design, then had it check her own site, aunysillyme.com. It found every buy button was too low in contrast to grab attention and that two different oranges had been used on the site for months, and it redesigned the site based on what it had learned.
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.
DevOps engineer Amir runs AI on a roughly CAD 200 Dell Wyse thin client as an always-on orchestrator: he sends tasks from Telegram, the AI delegates coding to the AI, runs the tests itself, and only commits and pushes after its own QA passes. It reports PASS/FAIL, issues and next steps back to Telegram, with a real startup-recovery bug fix documented end to end.
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.