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.
A random mix from the whole library. Shuffle for a new set.
Writing Rust code faster than state of the art by asking agents to make the code faster.
He had about 250 old newsletters sitting on beehiiv doing nothing. He fed them to the AI, had it turn them into blog posts, and the blog is now live with Google already sending readers to it, giving him a new funnel in a couple of hours.
Shipped a RAG customer-service agent for an online seller that sent 1,467 or more replies automatically to real buyers and ran the chat channel unattended.
A contractor onboarded Instinct through a WhatsApp chat that simply asked what he had been putting off; it now prepares his contracting invoices and drafts his outgoing emails - the two admin jobs that used to pile up behind the actual work.
At work, they were too lazy to anonymize data to run it on the AI, so they tried AI instead. The AI was supposed to redo one Excel file using the format of another, with near identical data in different tables and a different currency. Two hours were lost.
Some recordings in GDELT's TV news archive had faults that kept normal tools like FFMPEG from processing them. GDELT used AI 3.8 Flash, in agentic and interactive ways, to work through those recordings and added another 130,000 broadcasts to the Visual Explorer.
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 rebuilt his website, his point of sale, and his online storefront. He no longer pays Shopify $40 a month, his site works better, and payments run through Square.
His team of AI agents, building a biotech-investor decision-support app, turns the agent chat history into a scripted ElevenLabs-voiced podcast episode after each unit of work so he can follow progress by listening; he caught the team planning a roughly $730 API test run instead of using his AI plan and stopped it.
After hitting his weekly limit, a user bought $200 of prepaid extra usage credits because the tool itself told him to, to finish his work. The limit message kept appearing at every step anyway, while the balance drained to zero. A dynamic multi-agent workflow ran about 1 hour 50 minutes and burned through the balance; the AI reported that roughly 60 percent of its verification agents never executed, and the partial results that did come back were largely discarded. The $200 bought an incomplete verification.
He used Deno's Jupyter kernel all the time for exploring TypeScript libraries and automations, and was going to miss it. He pointed the AI at the problem and the result is cdp-kernel, Deno's Jupyter kernel extracted to run notebooks on any V8 runtime, now on GitHub.
After hackers hit their research site meta-analysis.cz, which had no central backup, the AI and the AI rebuilt it from Wayback Machine copies and scattered files on their hard drives. The site is now on GitHub, its datasets are archived on Zenodo with a DOI, and every paper has an HTML version next to the PDF.
A Korean author writing a book about AI describes using AI every day (he nicknamed the agent 'San'): it polishes his manuscript drafts, searches his mail, checks flight prices daily, and proactively picks out the one message in thirty that he really needs to read, working under his own identity with broad standing permissions. Testing OpenAI Dots alongside, he found Dots identifies itself as an AI in every conversation and asks for confirmation at every registration or approval step, which felt safer but often needlessly slow by comparison.
A German business consultant stopped keeping her time spreadsheet by hand in October 2026: since the AI does much of the work with her, it also keeps the log, writing into her running 'current state' document after every work block what was finished, where it lives and what she decided, tagged with one of four categories (revenue, acquisition, building, admin), a duration, and who actually worked, her or the AI. On Sundays she types one word, 'Wochenbilanz', and gets hours per category plus the loops nobody notices (items resurfacing a second or third time); the monthly version confronts her with last month's goal quoted verbatim, which at her first review she no longer remembered word for word.
His frontend launch scripts were failing with nothing in the logs. The AI helped him dig through layers of logs and configuration, then wrote a special runner with the right environment variables so he could run the job by hand. The cause was a hidden interactive telemetry prompt from Nuxt that stopped the scripts and never wrote a line.
A Japanese non-programmer who posts about shochu, his garden and the AI across X, Instagram and Facebook gets a 7 AM message from the AI with today's paste-ready post text, the photo to use and 3-4 posting steps, prepared from a one-page work memo of what is due and what is already posted. Drafts are scored against his rules and only those scoring 80+ are sent; the agent must ask him rather than invent personal experiences it cannot know.
Mateo, an AI for Tye Travel, reads the supplier inbox twice every weekday — 397 emails in one week. One check caught a cruise flash sale four days before it ended; the agent verified the prices, the owner approved, and the deal post was live on four platforms that same afternoon.
He used AI and the AI to build a setup that automatically made one LINE sticker a day. He stopped the setup once he was happy just having built it, and the stickers stay on sale in the LINE Store.
Uses Sonnet 5.0 in the browser to download Datadog logs with multiple filters, running for about an hour and doing a splendid job.
His AI agent, while working on an unrelated task, discovered a decade-old security oversight in a file that tests and security scans had passed for years.
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.