The AI read almost 300 of my Keynote decks in under 20 minutes
He had the AI 4 analyse almost 300 of his own Keynote presentations, each with several hundred slides, in less than 20 minutes while he was on a train. He then posted what it found.
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Work
Jobs, side gigs and small business · 1,665 ideasFollow up every AI receptionist call so no customer hears silence
In Tye Gordon's Lauderhill businesses, the agent roster includes Hope, whose whole lane is the gap after the AI receptionist takes a call: Hope follows up on those calls and sends the customer update texts and thank-you emails, each one approved by Tye first. The design point is that an answered call is not a finished job — somebody still has to close the loop with the customer, and that somebody is an agent working from the call record.
Settlement program cuts a bookkeeper's 12-hour Thursday to under one hour
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.
11 hourssaved
A one-file Excel audit became a 137-agent workflow against his standing no-multi-agent rule, half his weekly allowance gone in an hour
A user asked for a single audit of one Excel deliverable. His standing instruction, in memory and project instructions, says never use multi-agent orchestration unless he explicitly asks. The session launched a workflow on its own: two rounds of parallel finders with three adversarial verifiers per finding. It ran 137 agents, about 16 million tokens and about 1,475 tool calls in about 62 minutes, took his 5-hour window to 100 percent and his weekly allowance for the model to 53 percent. There was no estimate, cap, or confirmation. He stopped it manually.
This one went wrong. See what happened before you try it.
The AI and the AI rebuilt my 20 year old teaching site
His free French teaching site Ralentir travaux, used by millions of visitors, had been more or less abandoned because its old code ran to thousands of pages. Over about six months the AI and the AI cleaned, fixed and modernised the code and added new tools, and the rebuilt site relaunched for its 20th anniversary.
Clean my giant inbox by sender — trash only, never delete, undo everything
Dheeraj Sharma built an AI cleanup agent for decade-old Gmail inboxes like a reader's 130,000-message one, then ran it on his own 7,610-message mailbox in four gated stages: census, editable plan, dry run, apply. One approved run moved 2,896 newsletter and notification emails to Trash in 107 seconds (unread fell from 5,013 to 2,237), with deletion impossible by design and every change logged for a one-command undo.
Run my brand's support inbox, including warranty replacements
The owner of an acquired consumer brand had the AI build an app that pulls Facebook and Instagram comments and messages plus email into one place and drafts replies with the actions attached - for a warranty claim it collects the damage photo and order number, creates the replacement order, and sends the confirmation; his edits teach it the playbook.
Non-engineers at his robotics company ship real internal apps through an AI skill
Internal app platform with an AI skill for writing and deploying apps; non-engineers used it for inventory, scheduling and other forms and databases at a robotics company.
Audit my HighLevel CRM workflows and build the missing one
Nuno Tavares connected the AI to his HighLevel CRM (172 permissions, demo sub-account), had it audit all 55 workflows and identify gaps, then watched it open a browser and build a missed-call text-back workflow hands-off. The build landed as a draft: missed-call trigger, tag and wait step.
This only partly worked. Worth knowing before you try it.
Run my coding tasks overnight and report pass or fail
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.