427 new ideas this week

Level up how you use AI

Real things everyday people got it to do, and how to try them yourself.

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A random mix from the whole library. Shuffle for a new set.

Laid off two weeks ago, he spent the time finishing the poker site his friend group had wanted for years

His poker group has played together since high school. During Covid they played on a website that later shut down, and there was no good replacement for friends who just want a game of Texas hold'em online. He started building his own with AI while playing with the group, and after he was laid off from his database engineering job he spent two weeks going full time on it: front end, logins, authentication and stats. It is live in beta and free while he waits for his bank to approve that it is not a gambling website.

Build me a marathon training dashboard from my own running data

Simmons asked László to learn his Zone 2 method from his training community and analyse three months of pace and heart-rate data ahead of the New York City Marathon. Finding Garmin's API needed a developer account, the Dot signed up for Intervals.icu on its own, pulled his runs, built a dashboard called Steady and set up post-run messages.

The AI built the interactive probability guide I had always wanted

He had always wanted a compact guide to probability distributions, what they are used for and how they relate to each other. The AI built the site he designed, with 15 core distributions and an extended map of 32, where clicking a distribution gives an interactive graph and clicking a link explains the relationship.

For six weeks an AI operated Cadence Virtuoso for him and designed three analog circuit blocks

Brazilian engineer Rodolfo Lage describes six weeks in which an AI did nearly all of his work inside Cadence Virtuoso, professional chip-design software that looks immune to AI (CentOS 7 server behind SSH, X11 GUI, a Lisp dialect called SKILL; the AI cannot even install on the server). Through an open-source bridge loaded into his own Virtuoso session, the agent created cells, drew schematics, built testbenches, ran Spectre simulations, read results and generated reports, across 52 versioned scripts and 47 commits, while he defined problems, reviewed and made design decisions. Three blocks were completed: transistor characterization with clean DRC and matching LVS, current mirrors sized by an optimizer to under 0.005% current error, and a common-source amplifier reaching 26.8 V/V gain and 109 MHz gain-bandwidth. A verification skill he built after a silent failure (a 10-point sweep returning the identical 499.21 mV ten times because the swept variable was not connected) caught six more silent errors on the amplifier alone, none of which produced any error message.

Re-screen the same hiring pool against an outcomes scorecard — and hire

After the cancellation mess, Curtis wrote a one-page scorecard for the role (mission, five measurable first-year outcomes, six competencies), pasted it into the prompt and had the AI map each candidate's track record to each outcome with evidence from the résumé. With a human making every cut and applications closed before booking, the process ended in a Director of Ecommerce hire who has already optimized the company's Amazon listings and helped launch a product — and a declined candidate was later hired as a TikTok consultant.

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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.