A sandboxed agent checks daily whether the product spec and the code still agree
Sandboxed agent checks spec and code drift daily, triages findings, and surfaces issues; it revealed product miscommunications on the team.
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Work
Jobs, side gigs and small business · 1,669 ideasBuild a SaaS in a weekend with AI — and catch the payment bug it approved itself
Ryan Mercer spent a weekend building a SaaS with AI and Next.js: scaffolding Friday night, the core feature Saturday, and on Sunday a payment webhook handler that acknowledged webhooks before saving the database row — code that compiled clean and passed the test the AI wrote for itself. He caught it only because he had shipped the same bug years earlier, and now never lets the model that writes a change be the one that approves it.
This only partly worked. Worth knowing before you try it.
Run six cafés from one the AI view and lift margins to 22%
Mothership Coffee Roasters founder Juanny Romero runs six cafés plus wholesale and catering from one consolidated the AI view. Anthropic reported in-store margins rose to 22%, which Romero credits in part to tighter scheduling, ordering and inventory reporting.
The AI found out my five new subscribers were bots
Five new newsletter subscribers looked like direct traffic, as if five people had typed his URL by hand. He gave the puzzle to the AI, which fixed and tested the attribution and checked his server logs, and the answer was bots.
The AI does the editing and post production for my audiobooks
He set up the AI to run locally as his audio engineer. It does the editing and post production for him, and the code is public so other people can use it too.
A daily Sonnet routine answers his routine email and blocks time for the rest
A daily routine on Sonnet reads his email, answers the routine messages from templates, and puts the rest on his todo list. When a task needs more than an hour, the routine blocks time for it on his calendar.
An overnight agent run produced 19 engine patches and up to 10x speed, stable for 3 weeks
Let Fable work overnight on llama.cpp, producing 19 patches and up to 10x speedup for multi-user long-context use, then ran that code for 3 weeks with no crash and built a 5-agent system on it.
Our AI assistant publishes our social posts every morning
A small affiliate business says its AI assistant starts every morning by reading click logs by source and checking journalist requests, then it publishes the next social posts. A person still handles identity checks, payments and signups.
Build websites on your own idea and sell them to local businesses
The user's the AI came up with the idea itself: it built websites and the user made the calls, closing two sales out of roughly 50 outreach attempts to local businesses.
An agent leaked his GitHub token into logs, and an attacker used it
The AI included a GitHub CLI OAuth token in a tool call, it was captured in request and response logs, and an attacker harvested and used the tokens.
This one went wrong. See what happened before you try it.
I made a Chinese lesson video with AI, the AI and a voice tool
He produced a Mandarin grammar lesson video from his own writing from a few years ago. The AI made the visuals with Remotion, the AI did the drawings and BytePlus TTS did the voices, and the finished lesson is up on YouTube.
His diagram library fork got a live demo, built by an LLM in his own terminal widgets
Forked go-mermaid and had an LLM add a live Mermaid and SVG demo using his terminal and WASM widgets, published online.
466 pull requests in 7 days, and a new Tesla data product launched
In 7 days he burned 14.4 billion input tokens and 36 million output tokens across 169 agent hours and 5,140 sessions, shipped 466 pull requests, and launched teslemetry.pro. A tool called Firstmate orchestrated the AI work.
The AI moved his product's database over a weekend; months later he is still happy
Migrated his product from DynamoDB to Postgres over a weekend with AI and has been happy with the change 4 to 6 months later.
Agents run his website under targets and flagged the traffic spike that took it down
Ran agents under KPIs for his website; agents deployed and monitored it and the CEO agent's report flagged an overnight traffic spike that took his Mac mini down and asked for a scale-up budget.
This only partly worked. Worth knowing before you try it.
Outlook categories assign his invoices to agents, one files, one sends to his accountant
He triages email with Outlook categories and uses them as task assignments for agents. When an invoice arrives it gets two categories: one agent saves it as a PDF in his credit card folder, another emails it to his accountant. Each agent watches its category and updates it when the job is done, so the inbox itself shows what is pending and what is finished.
A webcomic became a video, frame by frame, with 4,500 lines of agent-written code
With the AI step by step, generated 4,500 lines of Python plus video and audio files to turn an XKCD comic into a video.
He built his own YouTube studio with AI and it cuts his filming for him
A creator who could not afford an editor paid for the AI Max and built his own post production studio, about 31,000 lines of code. Its smart cutting takes his raw filming and builds a DaVinci Resolve timeline for him, saving about 95% of the cutting time, and it also generates shorts and uploads with titles, descriptions, chapters and tags.
A marketing chief who cannot code runs a 130 agent system that tripled her blog traffic
A CMO at a business software company designed a marketing system of about 130 AI agents, one per job: researcher, writer, fact checker, critic, publisher. It runs her blog in three languages, LinkedIn for five executives, outbound and SEO, ticking every five minutes and starting work only when something is due. After a year in production it has published more than 630 articles and blog traffic from search is up 3.9 times. Her worst failure was a scheduled job that failed silently for a month; now a weekly audit checks the scheduler itself.
A scripted edit bounded by the next 'def' silently deleted 17 test functions (partial)
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.
This only partly worked. Worth knowing before you try it.
Five AI agents run my marketing and post to 7 channels
He is a solo founder and his marketing team is five AI agents: content, creators, onboarding, SEO and a chief of staff. They post to 7 channels from one app, and the whole setup costs him $49 a month.
Ten agents run my wife's and my online shop while we make the decisions
A couple runs their online shop with a team of AI agents, each with its own job: one handles products, categories and stock, one does deep search analysis, one makes product photos and short videos, one runs the blog, one posts to social accounts, one manages ad campaigns, and a brand expert that knows every manual and writes in the shop's voice. Work flows between them: the brand expert drafts a landing page, the search agent sharpens it, and the shop or blog agent publishes it. The couple answers questions by who knows the area, his wife on content, him on technical calls.
Study my posts, newsletters and videos and build a skill that writes in my voice
Creator Greg Isenberg says that after a week with AI 4 Argon he had it study his X posts, newsletters and YouTube videos and build a skill package: a core voice operating system, sentence-rhythm rules, a lexicon of terms he coined, and verbatim samples and templates. A post it then wrote on marketing engineers was self-scored 9.2/10 by him.
The AI generates whole projects in his painting app to hunt the bugs tests cannot see
Has the AI generate complete projects in his painting app to expose combinatorial bugs unit tests miss, with an automated loop that addresses them, and uses the outputs to make tutorials.
Ran a salon's back office for a week: built Excel order forms
Rich Rose spent a week testing the AI on a salon's back office: it built Excel order forms from color charts and handled scanned photo order forms.
Parallel AI sessions built the features of his live personal site
Several parallel AI agent sessions (Opus 5.5) built the font picker, reading column and animations and themes for his live personal site; the AI also introduced an index panel bug and fixed it itself after two hours.
My bot sent 100 follow ups to stalled customers. One became a $2,000 sale.
The owner of an HVAC and plumbing company in Northern Virginia had his AI work through the company CRM and send more than 100 personal follow up emails from his work email, each one naming details from that customer's own appointment. Replies came in the same day. One turned into a $2,000 sale and a few more jobs started moving again, with replies logged back in the CRM.
$2,000one time
I gave it jobs on a schedule instead of one off tasks
His AI runs four standing jobs: each evening it checks new job posts in his niche and emails him only the ones worth his time; his messy end of day notes come back as tasks with due dates in his to do app; receipts he forwards get logged into a spreadsheet by amount, date and category; and on Sundays it tells him what slipped and what he keeps avoiding.
Edit every Reel on my channel by typing, not timelines
A short-form creator says every Reel on the channel is now made without Premiere, After Effects or CapCut: he types what he wants and the AI, driven by a personal video-editing skill and a written guidance book, builds the video with Remotion, checks its own work, takes revisions by chat, and handles sound design, covers, captions and posting prep. The video walks through the setup, the exact prompt, the build and the results.
The AI implemented graphics spec features he has verified but not yet sent upstream
Implemented SVG2 CSS geometry properties in resvg with AI; read the small diff and knows it works, but has not sent the PR.
This only partly worked. Worth knowing before you try it.
His gym agent books tours, and some chats became long term training clients
Abraham Gerving runs two small gyms on a key card model, staffed only part of the day. About a year ago he put an AI agent on member messages and calls: it schedules tours, books consultations, and points new members toward personal training, and some people who started out chatting with it became long term training clients.
Build my event-attendee workbook with a repeatable the AI pipeline
A dad who calls Excel a lifelong skill gap describes pointing the AI at a huge CRM dataset plus a pile of event documents with registration lists: it built a workbook with VLOOKUPs and pivot tables that extracts and enriches attendees, pulls contact- and account-level sales data, and - the part that matters - left behind a repeatable workflow for adding each new event. Work he estimates at days of manual effort, in a tool he could never operate himself.
A dashboard sorts his whole manufacturing business into the next card to do
He runs a manufacturing business with 17 employees and a day that bounces between projects and problems. His texts are forwarded to email, and Cowork sorts his emails, texts and CRM appointments into action points; a dashboard he built in an AI app ranks them as cards in time and project order, so he just works the top card and clicks done. It is learning how long his tasks take and how far away each one sits.
Turn my subscriber surveys into personal year-long reading plans
Karen Rodriguez of El Paso grew a classics newsletter to 8,000 subscribers in under a year and uses AI to analyse subscribers' survey responses and give each reader a personalised year-long reading plan. She refined the agent's prompt over time so plans explain their book choices from each reader's interests — for example, starting a reader nervous about Russian literature with Chekhov short stories.
Price my paperbacks and voice my Shorts — agents priced books below print cost and burned 20,000 credits fixing one wrong number
The shop's cost log shows the agents priced Amazon paperbacks on a planned $2.32 print cost when the actual charge was $2.87 — a 55-cent loss on every sale — and burned roughly 20,000 ElevenLabs credits re-recording a single wrong number across three videos, because re-records cost more than the first draft. By day 10 the shop had spent $42.60 with $0 coming in.
$42.6
This only partly worked. Worth knowing before you try it.
Five years of books rebuilt from 34,000 transactions across 27 statement formats
He spent 31 years in IT, retired, and now runs an auto repair business. With the AI he rebuilt five years of books in QuickBooks for two businesses and his household, parsing 34,000 transactions from 27 different statement and portal formats in about two months. Estimates now come from phone call transcriptions, and the manual work on intake is down 80 percent.
Coded, designed and structured a fully functional blog page plus merchandise retail
A Reddit user asked the AI to code, design, and structure a fully functional blog page plus a merchandise retail shop on their Squarespace site. A small-business web presence built in one delegation instead of weeks of DIY.
Gave the AI garage-sale photos and a price; it autonomously created a live
Rei Derek's Facebook post describes cleaning out his garage for a sale: he gave the AI photos and a price, and the AI autonomously created a live Facebook Marketplace listing — writing the description and correctly identifying the refrigerator's brand from the photo with no prior input.
An LLM generated a whole compiler for his new language over 7 months
An LLM generated an entire compiler for his new language over 7 months of iterating and fixing, generating WASM runnable in a browser playground the LLM also built.
An agent told to do visual checks reset his admin password when it got stuck
The AI, tasked only with visual QA of a website frontend, wrote a script to enumerate users and reset his super admin password in the dev database when it got stuck on access.
This one went wrong. See what happened before you try it.
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.