AI Agent Use Cases

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Trying Codex Automated QA for a Flutter App

The author reports that after integrating Codex automated QA into a Flutter app under development, slow tests and unintended changes to features became problems.

Codex
Dev

Making a 3D Cube Net App for Children's Math Study

Grok Bot reportedly created a 3D app where children can fold all 11 cube nets from their textbooks, which are usually shown only as flat diagrams, using their fingers.

Grok Bot
Learning & Careers

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Marketing & DesignWalkthrough

Creating a Blog Post from Research to Images in One Workflow

The author reports connecting research, outline creation, section-by-section writing, and image generation in a single flow using n8n, based on SEO information entered in Airtable.

How it works

  1. The author entered SEO data, company information, target audience, and writing guidelines into Airtable, and set up n8n to fetch this information.
  2. Gemini 2.5 Pro generated the outline, while Gemini 2.5 Flash and Perplexity handled the research. Then, for each section, the workflow wrote the content and generated images, finally updating the Airtable record as completed.
  3. The author set up the generated posts to be reviewed separately within the Airtable interface.

Results

The author reports that a single test run took 28 minutes and 1.649 seconds, using 636,964 tokens in total. The image generation node accounted for 34,610 tokens.

Notes

The author stated that these figures are not optimized. In fact, accuracy, source verification, cost, and execution time are still being improved.

Source

Reddit Original post ↗

Example prompt · n8n

Design an n8n workflow that creates an SEO blog post in a single flow, from research and outline to section-by-section writing and image generation.

Input: Blog topic and main keyword [keyword], company introduction [company information], audience [target audience], writing style guidelines [guidelines], and where to store the information [e.g., Airtable base name]. First, check if your n8n is actually connected to Airtable, a text generation model, and a search tool; if not, just tell what connections are needed.

Order: 1) Fetch one record and read the topic and guidelines. 2) Use the search tool to gather supporting materials and save the source URLs. 3) Create an outline and divide it into sections. 4) For each section, write the content and append it to the same record. 5) Generate a representative image. 6) Change the record status to 'pending review' and clear temporary data. Do not publish the post immediately; only move it to the publishing stage after a person approves it in the review screen.

Deliverables: Node structure and connection order, input and output fields for each step, review screen setup, and how to record execution time and token usage. First, test with just one record to show execution time, token count, and the proportion of sentences with sources attached, then scale up to multiple records after reviewing the results.