The AI applied for 38 jobs for me in 3 days
A job seeker let the AI apply for jobs for him over 3 days, Sept 22 to 24. It sent 38 applications, all remote, mostly IT support roles, while he sent only 2 himself.
A random mix from the whole library. Shuffle for a new set.
A job seeker let the AI apply for jobs for him over 3 days, Sept 22 to 24. It sent 38 applications, all remote, mostly IT support roles, while he sent only 2 himself.
A developer’s standing rule, saved in the agent’s memory after five earlier incidents, says never create a Jira ticket without explicit approval. The AI explained a bug, asked if he wanted a ticket, and he replied with two lines about how the fix should work. The AI read that as a yes and created ticket PRE-990. He then had to spend time and effort cleaning the ticket up.
He built an invoice processor for a small law firm: PDFs arrive by email, get read with OCR, matched line by line to case codes, and pushed into the billing system. Anything it is unsure about goes to a manual review queue with a screenshot, and months of edge cases like 8s read as 3s went into its rules.
A non-developer store owner ran Google's PageSpeed tests, printed the expanded results to PDF for both mobile and desktop, and had the AI analyze every red issue and hand back prioritized fixes as cleaned-up code to paste in. His speed score rose 10-15 points and the speed index dropped from 3.2 seconds to 1.2.
His bots on the AI hold a daily standup before he has had coffee. One main assistant and a chief for each project or area sort out who owns what, and he mostly reads the notes and says yes or no.
The same business owner runs AI on a weekly cycle for search traffic. It scans competitor sites for the keywords he tracks, compares his own pages against them, suggests changes, and finds and puts in internal linking fixes itself.
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.
A delivery driver has the AI run his weekly payroll. Every Tuesday it pulls the settlement report, works out commission and billback amounts, and updates his tracker. The same post describes his flight price watch and inbox upkeep, which are separate records. He says the payroll job used to eat a chunk of his evening.
Nari Media's test shows the AI making the initial setup of Facebook and Instagram ad campaigns fast and accessible for media buyers, handling the first build inside Meta's ad tools.
Adley Kinsman (verified, 1.5M followers) walked through three concrete the AI uses for Instagram growth: ask what's gaining traction in her niche and which audience pain points are unaddressed; pull creator data from her niche for content pillars and competitive angles; and point the AI at her own account to diagnose what's working/flopping and map a 30-60-90 day plan. She framed it as 'the ONLY AI you need to grow on Instagram.'
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.