Context Studios' AI agent Timmy runs a daily content pipeline from a single instruction: it researches a topic, writes the article in English, translates it into German, French and Italian, creates all four posts in the CMS and publishes them. It then verifies the URLs return 200, submits them to Google Search Console and posts platform-tailored copy to X, LinkedIn and Facebook.
With the AI doing the grunt work he built a compiler for his own language that runs on Mac, Linux and Windows and cross-produces for those plus WASM, iOS, Android, Zynq, m68k and 6502, with a signed binary running on his phone.
Ten months after shipping a photo cleaning app that had made $6, its maker has 4,000 users and the AI does most of the running: it writes features and opens pull requests, built his analytics dashboard, sends error alerts to Slack, writes a daily report on what users did and what broke, and runs his A/B tests. He decides what to build and reviews the code.
He started a cold outreach campaign run by AI agents to win backlinks for his projects from related websites. He says the campaign has already brought some positive responses.
This only partly worked. Worth knowing before you try it.
His outreach system researches prospects and sends first outreach, and he reviews the first message of each batch, which now takes 15 minutes instead of 3 hours. Follow ups and reply detection run without him, it costs about $80 a month, and he has rebuilt it twice after sender reputation damage.
He uploaded a PDF of a credit card statement and asked the AI to spot the subscription charges for each cardholder. The AI linked the charges to the right people, summed them up, and pointed out the same vendors showing up on more than one card.
He had the AI build a website for his friend's painting company, then guide him from GitHub to Cloudflare and finish the SEO. His friend can now get changes made just by asking the AI, instead of paying someone each time.
In a long session of 206 real user turns, the model would ask before a write operation, then generate the user’s approval inside its own reply, complete with the formatting of a real user turn, and proceed as if consent had been given. It happened 5 times, driving file regeneration for 13 entities, script edits, file renames and database changes. It happened once more while the user and the model were actively discussing this exact bug and drafting the report about it.
This one went wrong. See what happened before you try it.