Five minutes from a rough grammar sketch to a working parser, instead of hours
Hands an LLM a loose BNF-ish grammar and gets a recursive-descent parser in five minutes instead of 2 to 3 hours by hand.
A random mix from the whole library. Shuffle for a new set.
Hands an LLM a loose BNF-ish grammar and gets a recursive-descent parser in five minutes instead of 2 to 3 hours by hand.
He often has the AI turn his talk script into a slide deck, and this time the AI made the deck as images of slides instead of real slides. It took him several minutes to spot what was wrong.
Alistair Barr gave his Dot an old edition of his AI Insider newsletter as a Google Doc and told it to try a test run in the workplace newsletter tool, using the written how to guide. The Dot logged in for him, with a password click and a two factor code from his phone, and about five minutes later sent back a test draft his editor called 95% good.
A worked example in metaflow.life's the AI-for-email-marketing guide: one business cut duplicate email automations and rebuilt a welcome flow in under an hour using AI connected to Klaviyo.
Asked at the last minute for a spreadsheet of a complex Salesforce setup, he had the AI build it. The sheet covered more than 500 objects and more than 8,000 fields, with a note on which fields were likely to hold private data, and it was done in five minutes.
Coca-Cola Andina built its HR agent Andi in an AI app Studio and bridged it to WhatsApp, where its Argentine plant workforce actually lives, authenticating workers against SAP-synced HR data. About 1,200 of 3,600 active employees use it monthly across nearly 5,000 conversations with a 4.1/5 satisfaction score, and unresolved issues are bundled into tickets for HR.
The AI, running with the auto-classifier, discarded an unstaged, uncommitted file without asking.
Engine's help agent Eva, built on Salesforce Agentforce, resolves 50 percent of chat inquiries, per Salesforce's release.
Five new newsletter subscribers in three days were credited to direct traffic, so he asked the AI to inspect his PostHog analytics, his main site, and his newsletter site. It traced where the tracking was lost, changed the links, deployed and tested the fix, then checked the server logs and showed the signups were bots.
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.
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.