Turn trending tech stories into short videos and social posts with one run. Ideal for marketing teams that want steady content without manual research, editing, and uploading. It pulls news, checks topic fit, builds images and videos, then saves and prepares posts for your channels.

The flow starts with a manual launch and collects items from Hacker News. It fetches the article page, then uses an AI model and a structured parser to extract a summary and related topics. A topic check decides if the story moves forward. The system prepares prompts, improves them, and generates images with Leonardo. It then creates videos from those images with RunwayML and also supports Creatomate to stitch clips. Wait webhooks handle long jobs and resume when media is ready. Files upload to S3 compatible storage or cloud drives, and you can send finished media to YouTube, X, Instagram, and LinkedIn.

Setup needs API keys and OAuth connections for the tools you use. Expect large time savings by turning hours of content work into minutes. Use it to produce daily explainer clips, thought leadership reels, or quick news roundups. Start small by limiting to one story, then raise the limit to scale output.

• News intake from Hacker News with a limit and batch loop to control volume
• AI summary and topic extraction using an OpenAI chat model with a structured parser
• Topic gating with a conditional check to keep only stories that match your niche
• Prompt preparation and improvement for image generation with Leonardo
• Image to video creation with RunwayML and optional clip assembly with Creatomate
• Async job control using wait webhooks and follow up status checks
• Asset storage to Amazon S3 compatible buckets and cloud drives
• Social distribution to YouTube, X, Instagram, and LinkedIn
• Config notes and nodes to make it easy to extend or swap data sources

• Reduce content creation from 3 hours to 15 minutes per story
• Automate 80 percent of research, asset creation, and posting steps
• Connect 12 systems to move files and posts without manual download and upload
• Handle 20 to 50 articles per day by raising the batch limit
• Cut posting mistakes by 90 percent with consistent mappings to each channel
• Reuse the same pipeline for new topics by changing one filter

1. Import the template into n8n: Create a new workflow in n8n > Click the three dots menu > Select 'Import from File' > Choose the downloaded JSON file.
2. You'll need accounts with Hacker News, OpenAI, Leonardo AI, RunwayML, Creatomate, Dropbox, Google Drive, Microsoft OneDrive, YouTube, X, Instagram, LinkedIn and Amazon S3. See the Tools Required section above for links to create accounts with these services.
3. In the n8n credentials manager, add an OpenAI API Key credential. Create an API key in your OpenAI account and paste it. Give the credential a clear name.
4. Open the Leonardo HTTP Request nodes. In the credential dropdown, create a new HTTP Custom Auth credential. Add your Leonardo API key as a Bearer token in the Authorization header.
5. Open the RunwayML HTTP Request nodes. Create a new HTTP Custom Auth credential and store your Runway API key in the Authorization header.
6. For Creatomate, create a new HTTP Custom Auth credential with your API key. Map any required headers in the node if needed.
7. Connect Dropbox, Google Drive, Microsoft OneDrive, YouTube, X, Instagram, and LinkedIn by creating new OAuth2 credentials for each in n8n. Follow the on screen prompts to grant access and select the right account.
8. For Amazon S3 storage, create an Amazon S3 credential with Access Key ID and Secret Access Key. If you use MinIO, set the custom endpoint and region as required.
9. Open the Upload to S3 node and set the bucket name and folder path. Enable public read if you plan to share links.
10. Open the Hacker News node and confirm the resource and filters. Use the Limit node to 1 while testing to keep costs low.
11. Review the Article Analysis and Article Prep nodes. Select your preferred OpenAI model and adjust temperature to control style. Keep outputs aligned with the Structured Output Parser schema.
12. In the Leonardo and Runway create nodes, map the Wait node webhook URL fields if the API supports callbacks. If callbacks are not available, keep the Wait and Get nodes connected to poll until ready.
13. Configure social nodes with captions and media fields. Start with drafts or private uploads on YouTube to review results before going live.
14. Click Test workflow to run a single item. Check the Runway and Leonardo status nodes, confirm files in S3 or drives, and review the social channel drafts. If a job stalls, verify API keys, scopes, and that the wait webhooks are reachable from the internet.