Two days of planning bought a 2-hour build of a high-risk feature
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.
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Work
Jobs, side gigs and small business · 1,693 ideasA loose prompt wasted all his tokens rebuilding a tool that already exists
Mis-prompted the AI on a toy project; it wasted all his tokens building a specialized Docker clone instead of building on Docker.
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The AI promoted itself from opening issues to submitting the fixes
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.
The AI found waste in my cloud setup and saved me about $2,000 a month
The AI went through his setup and found years of pending uploads that were never being cleared, which saved $2,000 a month. It also found more than $1,000 a month in S3 transfer costs to imgproxy, and moving that work from Railway to Fargate makes the transfer free.
$2,000a month
Rust code faster than the state of the art, by asking agents to make it faster
Writing Rust code faster than state of the art by asking agents to make the code faster.
The AI Notebook makes his board meeting minutes from recordings and handouts
He feeds the AI Notebook a transcript of the meeting recording plus scans of the printed handouts with his notes on them. It writes the minutes as bullet points grouped by topic, and the technical terms and names come out right more often than with apps that only use the audio.
The AI only checked 25 emails when I asked it to scan my whole inbox
He asked the AI to scan his entire work inbox and count emails from accounts he had never sent mail to, so he could weed out newsletters. It came back with two, which he knew was wrong, and when he asked why, it said it had only looked at the 25 most recent emails and given up.
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Every two hours my agent checks my app's issues, fixes them and opens the pull requests
A developer gave the AI a token for his code repo and set a two hour cycle. The AI checks the issues page, makes a branch for each issue, writes the fix or change, and opens a pull request. Merges rebuild the app and serve it on his home network, and the AI texts him on Telegram when it has a question or when work is done. He uses the app daily and files features as issues, which are handled within a couple of hours.
My bots hold a daily standup. I read the notes and say yes or no.
His bots on the AI hold a daily standup before he has had coffee. One main assistant and a chief for each project or area sort out who owns what, and he mostly reads the notes and says yes or no.
Agents shrank his AI model container from 6 GB to 900 MB and off the GPU
LLMs migrated a 6GB GPU SciBERT container to a 900MB ONNX CPU container.
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.