Step-by-step Gemini workflows from How I AI expert interviews. Each guide includes prompts, code snippets, and practical tips.
Use the Jev AI model to cheaply and quickly cluster thousands of GitHub pull requests into thematic areas. This helps engineering and product leaders understand the breakdown of work between new features, tech debt, and maintenance.
Go from an idea to a finished promotional video in minutes. This workflow shows how to use Google Flow to brainstorm a storyboard, generate video scenes with a custom avatar, and edit the final cut.
Learn to create a recognizable digital twin of yourself in minutes using Google Flow. This workflow guides you through scanning your face with your phone to generate a custom AI avatar for videos.
Create a repeatable exercise demonstration by pairing a consistent AI character with a real motion reference.
Photograph a curriculum book, let a dedicated teaching agent organize it into sources and lesson plans, then turn individual concepts into printable learning materials shaped by the agent's teaching style.
Prepare for customer interviews automatically by triggering on the right calendar events, gathering product and CRM context before the meeting, and placing a concise source-linked brief directly in the notes page.
Turn repeated AI commands into safe shell aliases, then promote a stable multi-step prompt into a small CLI with explicit inputs, visible configuration, and reproducible output.
Build a deliberate code analysis packet by selecting the smallest sufficient set of repository files, stating the question and constraints, and giving a reasoning model exact paths and contents without hidden context or irrelevant generated code.
Build a small multimodal app that turns a slow video sweep of a bookshelf into a reviewable book catalog, then correct duplicates and uncertain matches before exporting or sharing the collection.
When one model remains stuck, give a second model the original request, failed output, and desired example, use its critique to identify the mismatch, and test a targeted revision instead of repeating the same prompt.
Organize reusable business context, instructions, and small automations in a private GitHub repository so different AI tools can work from the same governed source without mixing client data, secrets, or unrelated tasks.
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