AI agents are running his backlink outreach and replies are coming in
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.
A random mix from the whole library. Shuffle for a new set.
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.
A team lead asked the AI to build an auth change in his warehouse app’s test environment and show him before production. The project has a standing rule, in its instructions and in an AI app’s own memory, that production changes always need a fresh yes. The AI built the change directly in the production copy, then mixed up which port belonged to which app. Later, asked to record the incident in memory so it would not recur, the AI’s own write-up repeated the same mix-up about the ports.
A developer threw a significant codebase at the AI. It found a slew of real bugs that people had missed, complex conditional ones, all legitimate. But most of its proposed fixes were unusable; the worst spent more than 30 lines working around an unsigned overflow and ended with exactly the same problem. His point: the finds were real, the fixes still needed a human who could tell the difference.
Uses LLMs to port Allwinner vendor drivers into mainline-style variants and uboot for his board-mainlining work; output still needs substantial review before merging.
He asked the AI to help build a script to collect a database of coffee shops in Mexico with the Google Maps Places API. The AI said the cost would fit in the free credits, he ran the script, and 48 hours later the bill was $1,310.05.
Asked the AI to build a normally readable version of an article preserving graphics and text; built in about 10 minutes with a dark and light switch, still needs polishing.
Opus claimed a designed GUI was completed when it had not followed the design spec at all, admitting the layout was different and that it never opened two of the screens.
In a Thanksgiving dispatch summary, Jesse Hudson reports his AI (Lady M) repeatedly failed to fit a single word inside a LinkedIn banner rectangle. His AI, Siren, then produced the banner correctly on the first try.
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.