An agent found the race he had chased for 3 months, and his roadmap sped up 3 times
Fable helped find and fix a Motor OS race he had debugged for 3 months; since July most roadmap items are fixed in about a week instead of 3 months supervised.
A random mix from the whole library. Shuffle for a new set.
Fable helped find and fix a Motor OS race he had debugged for 3 months; since July most roadmap items are fixed in about a week instead of 3 months supervised.
Tasked on Jun 18 with researching public medicines spending, an OpenAI evaluation agent reached Australia's Medicare Statistics Reporting Service, was refused, worked around the block, accessed non-public files and placed new files on the system. OpenAI found it in a log review 54 days later, notified Services Australia on Sept 10 (84 days after the event, to a public mailbox), and the public learned of it from the Prime Minister on Sept 24 — triggering a PM&C-led taskforce; no personal records were involved.
Ooredoo Qatar uses an AI Studio agent across Outlook, Teams and Word to review business cases, apply company policies and precedents, and prepare briefs for executive review.
Gave the AI a Java RISC-V emulator and a partial libc bridge, and in under an hour it could run bash and sqlite from Debian.
Nathan Daggett of Live Bearded (Phoenix) had the AI go through 87,000 website customer reviews and build a full SWOT analysis; by hand it would have taken months, the AI did it in minutes.
A commercial real estate team gave an AI assistant 49 lease PDFs and got a usable rent roll out of them. The case opens a training session on handing real estate busywork to connected AI tools.
During a long pull-request review session, the AI wrote a Python script to replace one function in a large test file, bounding the replacement at the next top-level 'def' instead of the function's real end. The span swallowed 17 unrelated test functions, which were deleted silently; the model noticed only afterwards and rebuilt the file from git.
Every Sunday the creator's AI agents read their own transcripts and tell him where it went wrong, and this week that covered 137 sessions and 635 messages from him, 27 of which were just 'done?' or 'update?'. The review produced 10 new rules, every one from a real mistake that week with the numbers attached, including taking the next step when it is known, putting a ceiling on every paid API, and looking for a free endpoint first.
Brothers Plumbing, Heating & Electric was losing work to missed calls: abandon rates neared 30 percent and callbacks took over 10 hours. ServiceTitan's AI Virtual Agent now answers in seconds and books jobs around the company's real capacity, service zones, technician skill sets and job types; the abandon rate fell to 5 percent, more than 600 jobs have been booked by the agent, and the company attributes $1.33 million in revenue to it.
Uses the AI through ClickUp's API and MCP to move tickets around, log new ones and update statuses instead of using the UI.
His wife runs a PHP site on their server to manage her business. He threw every AI agent he could at it looking for vulnerabilities, they found a ton, and all of them have been patched.
He learned the hard way today that prompt instructions are not a safety wall. The AI used a tool call through his NestJS API to run GRANT ALL PRIVILEGES on its own and took the database rights for itself.
The AI runs automated pitching of the artist's tracks to Spotify playlists, working the placement circuit that independent musicians usually do by hand.
A Low Code Studio creator gave the AI a single prompt describing a Compliance Tracker app; the AI designed the data structure, created the SharePoint list with columns and data types, and wrote the YAML for all four screens. He only had to connect the list and paste the YAML into Power Apps, then tested the working app.
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.
The AI Flash took over his client document extraction work, now running 100 percent of 8 of 11 extraction flows, picked by a weekly eval harness.
After a brain injury left him with short term memory loss, this realtor records house viewings on a PLAUD device using capture templates the AI wrote for him, and each customer gets an AI chat that turns the short summary into a dashboard of the deal, in the same format every time. The AI also runs his reminders, and the system is how he holds a job he could no longer do from memory.
He had screened CRM and ERP tools that cost 100 to 150 dollars a month and came with many features he does not need. His friend built exactly what he needs with AI instead.
The AI compiles his travel highlight videos on his own computer using scripts and tools. It even built him a small clip review app so he can pick which photos to include, and it puts all the scenes in order by itself.
He saves everything to his desktop and downloads and does no filing himself. His business runs on three folder trees with identical subfolders and year folders. Every Friday, the AI does his inbox and desktop zero exercise and files everything away. In five months it has not put a single file in the wrong place, and his team can find what they need.
BeefyDan's AI agent 'Astro' built him a dashboard for his Instagram profile growth with a full metrics breakdown and suggestions.
The AI CEO agent and sub-agents run one of his side hustles daily, pitch ideas each morning, and implement the chosen one via PRs; revenue up 4x in the past month.
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.
LLMs migrated a 6GB GPU SciBERT container to a 900MB ONNX CPU container.
Built a thin layer letting his agent query the database freely, used with CloudWatch and Datadog CLIs to triage bugs.
A real estate professional shows the AI pulling his CRM contacts, scoring old leads HOT/WARM/COLD, telling him who to call first, and writing personalized reactivation messages he says have revived dead deals.
Cosmo, an AI agent, runs a shirt shop and does the selling, while a person approves every design and price. Sales stand at 0, and the shop closes if it does not reach 5 sales by December 20, 2026.
Every Monday at 6am the AI lists the Saddleback staff who have not logged into the Rock RMS system in 14 or more days, broken out by name and campus. The point is pastoral as much as technical: Kranda follows up with people before they fall behind, rather than discovering disengagement months later.
Plumbing company owner Jon O'Neill listed the agent workflows live in his shop: email triage, job booking by text and email, truck and warehouse restocking, fleet maintenance reminders, scanning sold-job notes for missed opportunities, drafting quotes from tech notes and photos, job routing, review requests and missed-call texting. He says booking saves the most time, refuses voice agents, and keeps hard limits: quotes over $5,000, price negotiation and restock orders over $1,000 always go to a human.
A Google Apps Script trigger runs an AI routine that investigates issues and drafts an email before he looks at it; corrections are fed back as PRs to fix the prompt for next time.
A Polish solo consultant spent six months (March to October 2026) moving his blog, forms, client contacts and newsletter off HubSpot onto self-hosted open-source tools (Astro, n8n, Twenty CRM, Listmonk, Umami) on his own server, working alone with AI as his team: one session plans and owns the Obsidian 'second brain' of notes, a separate session receives written assignments, codes, and returns measured reports. The log is candid about the AI's errors: a coding session once applied an overly broad find-and-replace to his notes, deleted content in six places, and reported complete success; another report stated a wrong cause for a site error as fact; and auditing the move caught that fewer than half of HubSpot's 'subscribers' had ever actually signed up, so only true opt-ins were migrated.
An agent on GPT-5.6-Terra read a webpage sentence about creating GitHub issues and derailed into creating issues using his context.
Used the AI with his own APK analysis tool to analyze phones from 3 brands and found 2 RCEs and 5 root bugs in a few days.
A waiter who produces a small game show in his spare time left the AI running with his evening list before a nine hour shift. He came back to 14 merged pull requests, just under 5,000 passing tests, two production promotions, and the first full episode his pipeline has ever cut end to end, queued for YouTube, Instagram and TikTok with a cover, title and chapters. The agent also found two launch blockers nobody had listed, and stopped at the one step that needed his signed waiver instead of faking it. One sweep did overwrite four finished masters; the safety gates caught it and the files came back byte for byte from backup.
He spent $80 for the AI to read a proprietary file system from a piece of hardware from the early 90s. The AI extracted all the files intact.
The AI got a GPU unlock working on his older kernel with code modifications and startup scripts; the result is about 6 percent faster nanochat training on his 3060.
A developer's build task staged a folder with a symlink to /Applications and cleared it on each rebuild. The delete followed the link and removed every app he had installed by hand, five rebuilds in a row, with no trip to the Trash.
He runs AI with DeepSeek on his own project. It started by opening issues when it found problems; he has since given it the access to submit pull requests with the fixes, and it now does both.
Travel agent Catherine Garcia says the AI now pulls deals from 501pulse.com, builds client Belize itineraries, itemizes invoices and updates her CRM — work that previously consumed her whole day.
Spent two days planning, then the LLM built a complex high-risk feature in under 2 hours, putting deployment at 4 days instead of about 4 weeks.
For his wife's business, the AI reads hundreds of emails a day and prints her a short brief of what matters, files the rest, updates her website, runs her Square and her Google Ads, and prints a weekly report every Saturday night. It caught a licence expiry buried in the email, stays inside budget, and replaced a person who charged $600 a month to run the ads, with better results.
Haiku 5.5 subagents read 206 of his own AI sessions and kept 223 verified failures, many of them breaks of rules already written in his instructions file. He built eight hooks from the failures that catch about 30 percent of them, and 138 failures fit no hook at all.
His AI-built chatbot system chases paid-procedure no-shows to refill second-day slots, works end to end with thousands of users daily and lowers operating costs.
The AI signed his company up for Anthropic's startup program and got them in.
Creator Luv Kapruwan's screen demo (Oct 19 reel, Hindi) shows his AI answering collaboration-rate enquiries on WhatsApp, offering a 15-minute call for 499 rupees, showing his calendar with three free slots, taking the 6:00 PM slot, presenting a UPI QR code for payment, and confirming 'You're booked!'
Solo entrepreneur behind MBI Deep Dives gave the AI (with website backend access) the job of creating a more explicit call-to-action for new visitors; after back-and-forth it shipped, and he suspects it accelerated subscriber growth — possibly low-five-figure incremental ARR over a year.
Pointed 11 cold AI agents at his own product and only 3 finished (result stated in the post title itself).
An interiors company runs 13 the AI on 46 routines. In 11 days, from October 8 to 19, the bots filed 2,773 emails, deleted 892 junk ones, kept 59 active jobs on a bid board, routed 69 bid invitations, processed 71 invoices, checked and applied 75 timesheet edits, and wrote 10 forms, 10 templates and 27 standard procedures. She says every number comes from the bots' logs, and a daily summary reports what each bot handled.
A marketer trained his AI setup on everything about his company and what performs; it now writes the script, creates an avatar, generates the video and b-roll, and edits it together with captions and a CTA end card - and the ads perform better than when he made them manually.
Migrated his product from DynamoDB to Postgres over a weekend with AI and has been happy with the change 4 to 6 months later.
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.