Back to Catalog

Create Dev.to articles with OpenAI/Gemini - AI-generated content with images

LukaszBLukaszB
105 views
2/3/2026
Official Page

AI Blog Publisher Workflow for Dev.to

Turn a simple idea into a complete blog article with images, ready to publish — fully automated.

How It Works

This workflow takes a single input (your article idea) and transforms it into a polished blog post without manual effort.
It begins with a topic, entered directly in the Set node. For more automation, you can connect it to Google Sheets, a webhook, or even a chatbot that collects ideas from you or your team.

From there, the workflow does all the heavy lifting:

  • The AI creates a structured plan for the article, including outline, section goals, and image suggestions.
  • Image prompts are generated and sent to Gemini (or ChatGPT), which returns high-quality visuals that match the content. These are uploaded to your Cloudinary account so they’re instantly available online.
  • The article is written in clean Markdown by AI, weaving text and images together in a natural way.
  • Finally, the post is automatically published as a draft on Dev.to (or another platform of your choice, such as Medium, WordPress, or Ghost).

Instead of dealing with multiple tools or outsourcing to a copywriter, this workflow handles the entire pipeline — from idea to draft — in one seamless process.

Setup Steps

Getting started takes only a few minutes:

  1. Connect your OpenAI account for the AI writer and planner.
  2. Add your Dev.to API key so the workflow can publish drafts.
  3. Provide your Cloudinary account name and set up an unsigned upload preset for hosting images.
  4. (Optional) Add your Gemini API key, or switch to ChatGPT for image generation.
  5. Enter your first idea into the Set input data/credentials node, then run the workflow manually, on a schedule (Cron), or automatically via Google Sheets or a webhook.

Once configured, the workflow runs on autopilot — generating, illustrating, and publishing content without your input.

What You Get

Think of it as having a 24/7 content team working in the background.

  • Complete blog articles, written in a professional and natural tone.
  • Images that fit directly into the text, giving your content visual appeal.
  • Ready-to-publish drafts delivered straight to Dev.to (or your chosen platform).
  • A modular workflow that you can easily extend — whether you want new inputs (e.g. Slack, chat), new outputs (e.g. Medium, WordPress), or new AI models.

This isn’t just a template. It’s a fully operational content engine you can plug into your business.

Results You Can Expect

Publishing consistently online builds trust, visibility, and authority. With this workflow, you’ll:

  • Maintain a strong presence with regular articles — even when you’re not writing.
  • Increase conversions by showing up more often in searches and recommendations.
  • Build credibility by consistently sharing insights and solutions in your niche.
  • Save money and time, replacing the need for a copywriter with scalable AI-driven automation.

Who This Is For

  • Developers who want to showcase projects without spending hours writing.
  • Marketers looking to scale content strategies without hiring writers.
  • Agencies and SaaS teams who need regular publishing for SEO and community presence.
  • Solopreneurs who want their personal brand to grow online while they focus on building their product.

With this workflow, your blog becomes fully automated. All you need is an idea — the system takes care of everything else.

n8n Workflow: AI-Powered Dev.to Article Creation with Images

This n8n workflow automates the process of generating and publishing articles to Dev.to, complete with AI-generated content and images. It leverages large language models (LLMs) from OpenAI or Google Gemini to create article content and then prepares it for publishing.

What it does

This workflow streamlines the article creation process through the following steps:

  1. Triggers Manually or on Schedule: The workflow can be initiated manually or on a predefined schedule.
  2. Fetches Data from Google Sheets: It retrieves article ideas or prompts from a specified Google Sheet.
  3. Prepares Data for AI Generation: It processes the fetched data, potentially limiting the number of items and splitting them into individual batches for AI processing.
  4. Generates Article Content with AI:
    • It utilizes either an OpenAI Chat Model or a Google Gemini model (configurable via an AI Agent or Basic LLM Chain) to generate article text based on the input from Google Sheets.
    • A Structured Output Parser is used to ensure the AI output conforms to a defined structure.
  5. Generates Images with OpenAI: It uses the OpenAI node to generate relevant images for the article based on the generated content or prompts.
  6. Combines Generated Content: The generated article text and image data are aggregated.
  7. Prepares for Publishing: The content is then formatted and prepared for publication on Dev.to (though the final Dev.to publishing step is not explicitly shown in the provided JSON, the workflow sets up the content for it).

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running instance of n8n.
  • Google Sheets Account: Configured credentials for Google Sheets to read article prompts.
  • OpenAI API Key: Credentials for OpenAI to generate text and images.
  • Google Gemini API Key (Optional): If you choose to use Google Gemini instead of OpenAI for text generation, you'll need its API key.
  • Dev.to Account (Implicit): Although not explicitly configured in the provided JSON, a Dev.to account would be required for the final publishing step.

Setup/Usage

  1. Import the Workflow: Import the provided JSON into your n8n instance.
  2. Configure Credentials:
    • Set up your Google Sheets credentials.
    • Set up your OpenAI credentials for both text and image generation.
    • (Optional) If using Google Gemini, set up your Google Gemini credentials.
  3. Configure Google Sheets Node:
    • Specify the spreadsheet and sheet name where your article prompts are located.
    • Ensure your sheet has the necessary columns for article ideas/prompts that the AI models will use.
  4. Configure AI Nodes:
    • Select your preferred LLM (OpenAI Chat Model or Google Gemini) within the "AI Agent" or "Basic LLM Chain" nodes.
    • Adjust prompts and parameters within the AI nodes to guide content generation as needed.
    • Configure the "OpenAI" node for image generation, specifying image prompts and desired output.
  5. Configure Output Parser: If you modify the AI output structure, ensure the "Structured Output Parser" is updated accordingly.
  6. Activate the Workflow: Enable the workflow.
  7. Run the Workflow:
    • You can execute it manually by clicking "Execute Workflow".
    • Alternatively, configure the "Schedule Trigger" to run the workflow at desired intervals (e.g., daily, weekly).

This workflow provides a powerful foundation for automating your Dev.to content creation, allowing you to generate articles and images efficiently using AI.

Related Templates

Track competitor SEO keywords with Decodo + GPT-4.1-mini + Google Sheets

This workflow automates competitor keyword research using OpenAI LLM and Decodo for intelligent web scraping. Who this is for SEO specialists, content strategists, and growth marketers who want to automate keyword research and competitive intelligence. Marketing analysts managing multiple clients or websites who need consistent SEO tracking without manual data pulls. Agencies or automation engineers using Google Sheets as an SEO data dashboard for keyword monitoring and reporting. What problem this workflow solves Tracking competitor keywords manually is slow and inconsistent. Most SEO tools provide limited API access or lack contextual keyword analysis. This workflow solves that by: Automatically scraping any competitor’s webpage with Decodo. Using OpenAI GPT-4.1-mini to interpret keyword intent, density, and semantic focus. Storing structured keyword insights directly in Google Sheets for ongoing tracking and trend analysis. What this workflow does Trigger — Manually start the workflow or schedule it to run periodically. Input Setup — Define the website URL and target country (e.g., https://dev.to, france). Data Scraping (Decodo) — Fetch competitor web content and metadata. Keyword Analysis (OpenAI GPT-4.1-mini) Extract primary and secondary keywords. Identify focus topics and semantic entities. Generate a keyword density summary and SEO strength score. Recommend optimization and internal linking opportunities. Data Structuring — Clean and convert GPT output into JSON format. Data Storage (Google Sheets) — Append structured keyword data to a Google Sheet for long-term tracking. Setup Prerequisites If you are new to Decode, please signup on this link visit.decodo.com n8n account with workflow editor access Decodo API credentials OpenAI API key Google Sheets account connected via OAuth2 Make sure to install the Decodo Community node. Create a Google Sheet Add columns for: primarykeywords, seostrengthscore, keyworddensity_summary, etc. Share with your n8n Google account. Connect Credentials Add credentials for: Decodo API credentials - You need to register, login and obtain the Basic Authentication Token via Decodo Dashboard OpenAI API (for GPT-4o-mini) Google Sheets OAuth2 Configure Input Fields Edit the “Set Input Fields” node to set your target site and region. Run the Workflow Click Execute Workflow in n8n. View structured results in your connected Google Sheet. How to customize this workflow Track Multiple Competitors → Use a Google Sheet or CSV list of URLs; loop through them using the Split In Batches node. Add Language Detection → Add a Gemini or GPT node before keyword analysis to detect content language and adjust prompts. Enhance the SEO Report → Expand the GPT prompt to include backlink insights, metadata optimization, or readability checks. Integrate Visualization → Connect your Google Sheet to Looker Studio for SEO performance dashboards. Schedule Auto-Runs → Use the Cron Node to run weekly or monthly for competitor keyword refreshes. Summary This workflow automates competitor keyword research using: Decodo for intelligent web scraping OpenAI GPT-4.1-mini for keyword and SEO analysis Google Sheets for live tracking and reporting It’s a complete AI-powered SEO intelligence pipeline ideal for teams that want actionable insights on keyword gaps, optimization opportunities, and content focus trends, without relying on expensive SEO SaaS tools.

Ranjan DailataBy Ranjan Dailata
161

Generate song lyrics and music from text prompts using OpenAI and Fal.ai Minimax

Spark your creativity instantly in any chat—turn a simple prompt like "heartbreak ballad" into original, full-length lyrics and a professional AI-generated music track, all without leaving your conversation. 📋 What This Template Does This chat-triggered workflow harnesses AI to generate detailed, genre-matched song lyrics (at least 600 characters) from user messages, then queues them for music synthesis via Fal.ai's minimax-music model. It polls asynchronously until the track is ready, delivering lyrics and audio URL back in chat. Crafts original, structured lyrics with verses, choruses, and bridges using OpenAI Submits to Fal.ai for melody, instrumentation, and vocals aligned to the style Handles long-running generations with smart looping and status checks Returns complete song package (lyrics + audio link) for seamless sharing 🔧 Prerequisites n8n account (self-hosted or cloud with chat integration enabled) OpenAI account with API access for GPT models Fal.ai account for AI music generation 🔑 Required Credentials OpenAI API Setup Go to platform.openai.com → API keys (sidebar) Click "Create new secret key" → Name it (e.g., "n8n Songwriter") Copy the key and add to n8n as "OpenAI API" credential type Test by sending a simple chat completion request Fal.ai HTTP Header Auth Setup Sign up at fal.ai → Dashboard → API Keys Generate a new API key → Copy it In n8n, create "HTTP Header Auth" credential: Name="Fal.ai", Header Name="Authorization", Header Value="Key [Your API Key]" Test with a simple GET to their queue endpoint (e.g., /status) ⚙️ Configuration Steps Import the workflow JSON into your n8n instance Assign OpenAI API credentials to the "OpenAI Chat Model" node Assign Fal.ai HTTP Header Auth to the "Generate Music Track", "Check Generation Status", and "Fetch Final Result" nodes Activate the workflow—chat trigger will appear in your n8n chat interface Test by messaging: "Create an upbeat pop song about road trips" 🎯 Use Cases Content Creators: YouTubers generating custom jingles for videos on the fly, streamlining production from idea to audio export Educators: Music teachers using chat prompts to create era-specific folk tunes for classroom discussions, fostering interactive learning Gift Personalization: Friends crafting anniversary R&B tracks from shared memories via quick chats, delivering emotional audio surprises Artist Brainstorming: Songwriters prototyping hip-hop beats in real-time during sessions, accelerating collaboration and iteration ⚠️ Troubleshooting Invalid JSON from AI Agent: Ensure the system prompt stresses valid JSON; test the agent standalone with a sample query Music Generation Fails (401/403): Verify Fal.ai API key has minimax-music access; check usage quotas in dashboard Status Polling Loops Indefinitely: Bump wait time to 45-60s for complex tracks; inspect fal.ai queue logs for bottlenecks Lyrics Under 600 Characters: Tweak agent prompt to enforce fuller structures like [V1][C][V2][B][C]; verify output length in executions

Daniel NkenchoBy Daniel Nkencho
601

Automate Dutch Public Procurement Data Collection with TenderNed

TenderNed Public Procurement What This Workflow Does This workflow automates the collection of public procurement data from TenderNed (the official Dutch tender platform). It: Fetches the latest tender publications from the TenderNed API Retrieves detailed information in both XML and JSON formats for each tender Parses and extracts key information like organization names, titles, descriptions, and reference numbers Filters results based on your custom criteria Stores the data in a database for easy querying and analysis Setup Instructions This template comes with sticky notes providing step-by-step instructions in Dutch and various query options you can customize. Prerequisites TenderNed API Access - Register at TenderNed for API credentials Configuration Steps Set up TenderNed credentials: Add HTTP Basic Auth credentials with your TenderNed API username and password Apply these credentials to the three HTTP Request nodes: "Tenderned Publicaties" "Haal XML Details" "Haal JSON Details" Customize filters: Modify the "Filter op ..." node to match your specific requirements Examples: specific organizations, contract values, regions, etc. How It Works Step 1: Trigger The workflow can be triggered either manually for testing or automatically on a daily schedule. Step 2: Fetch Publications Makes an API call to TenderNed to retrieve a list of recent publications (up to 100 per request). Step 3: Process & Split Extracts the tender array from the response and splits it into individual items for processing. Step 4: Fetch Details For each tender, the workflow makes two parallel API calls: XML endpoint - Retrieves the complete tender documentation in XML format JSON endpoint - Fetches metadata including reference numbers and keywords Step 5: Parse & Merge Parses the XML data and merges it with the JSON metadata and batch information into a single data structure. Step 6: Extract Fields Maps the raw API data to clean, structured fields including: Publication ID and date Organization name Tender title and description Reference numbers (kenmerk, TED number) Step 7: Filter Applies your custom filter criteria to focus on relevant tenders only. Step 8: Store Inserts the processed data into your database for storage and future analysis. Customization Tips Modify API Parameters In the "Tenderned Publicaties" node, you can adjust: offset: Starting position for pagination size: Number of results per request (max 100) Add query parameters for date ranges, status filters, etc. Add More Fields Extend the "Splits Alle Velden" node to extract additional fields from the XML/JSON data, such as: Contract value estimates Deadline dates CPV codes (procurement classification) Contact information Integrate Notifications Add a Slack, Email, or Discord node after the filter to get notified about new matching tenders. Incremental Updates Modify the workflow to only fetch new tenders by: Storing the last execution timestamp Adding date filters to the API query Only processing publications newer than the last run Troubleshooting No data returned? Verify your TenderNed API credentials are correct Check that you have setup youre filter proper Need help setting this up or interested in a complete tender analysis solution? Get in touch 🔗 LinkedIn – Wessel Bulte

Wessel BulteBy Wessel Bulte
247