A security company's agent built a full browser exploit chain in 6 days
XBOW's agent built a Chrome full-chain exploit affecting a billion users in six days.
A random mix from the whole library. Shuffle for a new set.
XBOW's agent built a Chrome full-chain exploit affecting a billion users in six days.
He runs a B2B cold outreach agency at $58,500 a month in recurring revenue. The agents he actually uses are plain: one reads each prospect's website and writes an opener about their business, one sorts replies into truly interested versus politely brushing off, and one sends a personal reply only when a human cannot get to it first.
A Spanish AI consultant's case study (client anonymized): in autumn 2026 he trained the 8-12 person team of an industrial family office with several companies. Working in department pairs, each pair left with a working the AI Skill or agent prototype on a real case of theirs: a Skill for the monthly storage-unit bank reconciliation, another for comparing offers, a Cowork contract registry over the maintenance folder, and scheduled tasks such as a daily inbox review and a weekly maintenance summary, all on Microsoft 365 connectors, with a governance playbook and 30 days of support.
He talks loudly on video calls and his partner, who works across the hall, hears him. In 15 minutes of back and forth, the AI built him an app set to his own voice level and his keyboard volume, and it sits on top of Zoom.
He set up an AI skill that scans job sites for him. He says the jobs it brings back are much more relevant than what he was finding on his own.
Hands an LLM a loose BNF-ish grammar and gets a recursive-descent parser in five minutes instead of 2 to 3 hours by hand.
During an ML security competition, he gave his research and code to the AI on a GPU VPS and told it to improve the score, then went back to his own research. The team only found out the AI had submitted new results when their score jumped, and it jumped again a few moments later.
His business scans every invoice into a Google Drive folder. The AI reconciles them there: checking they were billed correctly, that credits for returned goods actually arrived, and that there is no slippage. He says it is far faster than reconciling by hand.
A small-business owner runs a small AI team sharing one Google Drive knowledge base, with a chief-of-staff bot that preps his mornings from his calendar. In one week the bots built and tested his AI Assessment client flow end to end (fit call, payment, booking, intake), rewrote his Todoist tasks as next physical actions, searched X for him, and built a customer slide deck from templates, saving about two hours.
During a migration, a written plan in the session said nothing in the legacy repo gets touched. The plan was re-shown in full mid-session. When the user later asked for a follow-up change, the AI searched the folder it had been working in most recently, which was that repo, found a file that looked right, and edited it there. The user caught it, and the edit was reverted and redone in the correct repo.
Duggan says he replaced a $480/mo Upwork video editor with an AI pipeline: The AI scripts the video, ElevenLabs provides the voice, and Remotion/HyperFrames handles the animation. He says the reel itself was produced this way.
His Gmail Promotions tab held 7,102 promo emails built up over years of online shopping. He asked the AI to clear them. It asked him to confirm before doing anything destructive, moved all 7,102 to Trash in one go, then ran a follow-up check to verify zero promos were left outside Trash. The whole job took about a minute of his time, and trashed mail stays recoverable for 30 days.
His general contracting firm built an AI program that searches for signals, warms up emails and sends personal outreach to find work. It worked so well they had to turn it off twice: a $120,000 bid for a four season room was accepted, painter responses came back within seven minutes, and they now have subcontractors across the state after struggling to find 30 before.
To mark the start of the semester, he asked the AI to build a macOS widget. It counts down how many weeks are left until the last class, and how many of those weeks are real teaching weeks.
Asked to compare the AI and the AI with citations in a saved Google Doc, Spark produced the table and doc but contradicted its own pricing figures and cited an electronics retailer's blog for software pricing. Challenged, it fixed the USD prices but the India rupee figures stayed unverifiable.
A builder used AI in Google AI Studio and DeepSeek to build a 19 project .NET system over about 4 and a half hours. It turned an 820 MB corpus into a 153 MB SQLite catalog with 0 foreign key errors.
A solo operator in Texas runs DeedSpring, where people get paid $13 to $75 for small real world deeds like leaving art in public or helping a stranger. His agent Vesper runs the desk: recruiting, acknowledgments, checking photo evidence against the posted rules, and payouts through escrow. Six deeds have been paid so far across five countries, and every receipt sits on a public ledger.
Frontier model reviewed his KiCad project, queried the AI vision for datasheet data, ran ngspice sims; $1-2 tokens saved $70-80 of bugged PCBs.
A solo founder runs PromptBase on a small AI team living on a Linux server: a support bot answers customer email from his Gmail, an engineer bot writes code, a security bot watches Cloudflare and server logs - and the bots have fixed a customer bug together without him, while he managed them from a phone on a five-hour hike in Wales.
The AI wrote a Windows batch helper as a UTF-8 file with LF line endings. On this Japanese locale machine the last byte of a Japanese full stop swallowed a line break, a variable stayed empty, and a delete meant for one file deleted every file in the project folder, 1,068 files in one second. 123 files could not be recovered.
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.