This article provides a complete, practical walkthrough of the Linkedin Wait Create Webhook n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:
   From Hacker News to Video: Automated Content Creation with AI and n8n
   
   Meta Description:
   Discover how this powerful n8n workflow transforms Hacker News articles into engaging videos using AI tools like OpenAI, Leonardo AI, RunwayML, and Creatomate. Learn how automation streamlines content generation and publishing.
   
   Keywords:
   AI content automation, n8n workflow, Hacker News, OpenAI GPT, RunwayML, Leonardo AI, Creatomate, AI video generation, auto content creator, AI summarizer, generative video, automation tools, AI pipeline
   
   Article:
   
   Turn Hacker News Into Viral Video Content—Automatically with n8n, AI, and Automation Tools
   
   In today's digital-first world, content creation reigns supreme, and automation is fast becoming a core strategy for staying competitive. Imagine turning trending Hacker News articles into captivating, AI-generated video stories—fully automated, beautifully animated, and ready to share on social media. That’s exactly what a custom-built n8n workflow by Alex Kim (@alexk1919) does using an impressive stack of third-party AI services.
   
   This article breaks down how this remarkable automation works, what tools are involved, and how it can transform your content strategy.
   
   🧠 What Does This Workflow Do?
   
   At its core, this n8n workflow pulls trending articles from Hacker News, checks if their topics are related to automation or AI, summarizes them, creates relevant visuals, generates video scenes, and stitches everything into a polished video—ready to be uploaded or posted to multiple platforms like YouTube, Instagram, LinkedIn, and more.
   
   The pipeline blends natural language processing, image generation, video rendering, and voiceover synthesis to achieve this in a seamless loop.
   
   📥 Step 1: Import Trending Hacker News Items
   
   Starting with the Hacker News node, the workflow fetches the most recent top articles. A limiter ensures only 50 articles are processed per batch.
   
   🎯 Step 2: Filter & Analyze for Relevance
   
   An OpenAI-powered agent analyzes each article’s content, checking whether it aligns with automation or AI. If not, the article is skipped. For qualifying articles, the next steps include generating a short summary and identifying relevant images from the original article URL.
   
   📄 Step 3: Summarize and Prep for Video
   
   Using OpenAI’s GPT-4o Mini model, the workflow creates:
   
   - A title and blurb for newsletters (limited to 15 words)
   - Two distinct summary blurbs
   - Two unique AI image prompts
   
   Markdown is the chosen format, ensuring structured and programmatically readable output.
   
   🖼️ Step 4: Generate Visuals with Leonardo AI
   
   Each text prompt gets optimized via Leonardo’s Prompt Improve endpoint. Then, high-quality images are generated using Leonardo’s image generation API with artistic presets like MONOCHROME and high-resolution settings. Wait nodes ensure generation time is accommodated before continuing.
   
   🎞️ Step 5: Animate with RunwayML
   
   The output images are sent to RunwayML’s Gen-3 Turbo model, which transforms static images into short dynamic video clips. The workflow waits for each video render to complete before proceeding.
   
   🎙️ Step 6: Turn Text into Voice & Subtitles
   
   OpenAI’s TTS model (“tts-1”) is used to create voiceovers for each scene using the article title and summary blurbs. These voice clips are synchronized with subtitles to elevate accessibility and engagement.
   
   🎬 Step 7: Assemble in Creatomate
   
   Everything comes together with Creatomate, a video automation platform that combines:
   
   - Intro scenes with generated images
   - Voiceovers with animated subtitles
   - RunwayML-generated background videos
   
   The workflow constructs a full video composition with highlighted talking points—perfectly stylized for social media.
   
   ☁️ Step 8: Upload & Distribute
   
   After rendering, videos are uploaded to several platforms with the final nodes including integrations for Dropbox, Google Drive, Microsoft OneDrive, and social channels like YouTube, Twitter (X), Instagram via HTTP APIs, and LinkedIn. This makes it easy to share content across multiple channels instantly.
   
   🧩 Third-Party APIs & Services Used
   
   This advanced automation relies on robust integrations:
   
   1. Hacker News — Source of trending articles via public API
   2. OpenAI GPT models — Summarization, prompt creation, TTS voice generation
   3. Leonardo AI — Prompt improvement and high-res image generation
   4. RunwayML — Image-to-video generation using its Gen-3 model
   5. Creatomate — Video template editor and renderer (audio, subtitles, animations)
   6. Dropbox, Google Drive, OneDrive — Optional storage destinations
   7. YouTube, LinkedIn, Twitter (X) — Optional publishing endpoints
   8. MinIO — S3-compatible object storage, optional
   9. n8n — Orchestration engine tying the process together
   
   🏗️ Why This Workflow Matters
   
   This workflow showcases the frontier of AI-native content automation. It allows creators, startups, and marketers to scale their content dissemination efforts without a production team. By combining AI-powered summarization, voice synthesis, and generative visuals, one person can now automate an entire media pipeline from idea to video.
   
   Whether you’re building a newsletter, an AI YouTube channel, or looking to stay ahead in the content game, this workflow may be your blueprint for a fully-automated, always-on content engine.
   
   🔗 Want to Learn More?
   
   Check out the full visual overview here: https://youtu.be/XaKybLDUlLk  
   More about the creator, Alex Kim (alexk1919): https://beacons.ai/alexk1919
   
   —
   
   By combining AI models and n8n, we are stepping into a new era of intelligent automation where storytelling, data, and digital creativity converge—to stunning effect.
   
   — Written by your assistant, powered by automation 🤖✨

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.