Reddit Post to Scripted YouTube Video

A 65-node workflow that takes a single Reddit post and transforms it into a polished YouTube script through a 6-stage AI pipeline. Each stage uses a different processing strategy -- from initial analysis through RAG-augmented outlining, web-research-enhanced drafting, and multi-model refinement using both OpenAI and xAI Grok. The result is a script that is not just rewritten Reddit content but a thoroughly researched, multiple-perspective narrative built on the foundation of a trending discussion.

Nodes	Category	Complexity	Key Integrations
65	Content Creation & AI	Advanced	Reddit, SerpAPI, OpenAI, xAI Grok, Qdrant, Cohere, Google Sheets

Prerequisites

• Reddit API credentials (OAuth2 app registration for search access)
• OpenAI API key for analysis, drafting, and polish agents
• xAI Grok API key for the refinement stage
• SerpAPI API key for web research (8 separate query nodes)
• Qdrant instance (cloud or self-hosted) -- 4 separate vector stores for different knowledge domains
• Cohere API key for embedding generation (4 embedding nodes)
• Google Sheets OAuth2 credentials for script output and metadata storage
• Knowledge level: Intermediate to Advanced -- requires understanding of multi-stage AI pipelines, vector databases, and multi-model orchestration

Estimated Setup Time

60-90 minutes including Qdrant vector store setup (4 collections), API credential configuration, and knowledge domain population.

What It Does

The pipeline begins with Reddit Search pulling a post and its comment thread. Stage 1 (Analysis) dissects the post: what is the core topic, what are the dominant perspectives in the comments, what questions remain unanswered, and what emotional hooks exist in the discussion. This analysis feeds into Stage 2 (Outline), where an AI Agent uses the Qdrant vector store to retrieve related content the creator has produced before, then builds a script outline that positions this new piece within the broader content library.

Stage 3 (Draft) is where the script takes shape. The drafting agent has access to SerpAPI for real-time web research, pulling in supporting data, statistics, and expert opinions that go beyond what the Reddit thread contains. Stage 4 (Research Enhancement) runs a second pass of web research, specifically targeting gaps and claims that need verification or deeper context. Eight separate SerpAPI calls run across different query angles.

Stage 5 (Refinement) introduces xAI Grok for a different analytical perspective. Grok reviews the draft for logical consistency, argument strength, and narrative flow, providing a revision that benefits from a second model's reasoning patterns. Stage 6 (Final Polish) brings OpenAI back for the finishing pass -- tightening language, strengthening transitions, punching up the hook, and ensuring the script is optimized for spoken delivery.

Workflow Diagram

Node Breakdown

Triggers

• Manual Trigger
• Schedule Trigger

AI & Language Models

• AI Agent (6)
• OpenAI
• xAI Grok
• Qdrant Vector Store (4)
• Cohere Embeddings (4)

Data & Integrations

• Reddit Search
• SerpAPI (8)
• Google Sheets
• Code
• Merge

Step-by-Step Flow

1. Trigger fires manually or on a schedule to process queued Reddit post URLs.
2. Reddit Search retrieves the full post content and comment thread.
3. Stage 1 -- Analysis Agent dissects the post: core topic, dominant perspectives, unanswered questions, and emotional hooks.
4. Stage 2 -- Outline Agent queries four Qdrant vector stores for related prior content, then builds a structured script outline.
5. Stage 3 -- Draft Agent writes the first full script draft with access to SerpAPI for real-time research and supporting data.
6. Stage 4 -- Research Enhancement runs eight targeted SerpAPI queries to fill gaps, verify claims, and add expert context.
7. Research results are merged and injected into the draft as supporting evidence.
8. Stage 5 -- Refinement Agent (xAI Grok) reviews the draft for logical consistency, argument strength, and narrative flow.
9. Stage 6 -- Polish Agent (OpenAI) delivers the final pass: language tightening, transition strengthening, hook optimization, and spoken-delivery formatting.
10. Google Sheets receives the finished script with metadata: source URL, processing timestamps, word count, and stage-by-stage notes.

What Sets It Apart

• Six-stage AI pipeline. Most AI content workflows use a single prompt. This workflow applies six distinct processing stages, each with a specific objective, producing output quality that a single pass cannot match.
• Multi-model refinement. Using xAI Grok in Stage 5 alongside OpenAI in other stages introduces genuine diversity of reasoning. Different models catch different weaknesses.
• Four separate vector stores. Each Qdrant instance holds a different knowledge domain (prior scripts, topic research, audience data, competitor content), giving agents precisely scoped context for their specific stage.
• Research-first approach. Two full stages of web research (Stages 3 and 4) with eight SerpAPI calls ensure the final script goes far beyond the original Reddit discussion in depth and credibility.

Cost Considerations

• OpenAI: Used across 4 of 6 stages; estimate $0.50-2.00 per script depending on Reddit post length and research depth
• xAI Grok: Used in Stage 5 refinement; ~$0.10-0.50 per script
• SerpAPI: 8 queries per script execution; free tier (100/month) covers ~12 scripts. Paid plans from $50/month
• Qdrant Cloud: Free tier (1GB) sufficient if managing collection sizes; 4 collections will consume more space over time
• Cohere: Free trial tier available; 4 embedding nodes per run is low-cost
• Reddit API: Free for moderate usage
• Google Sheets: Free with Google account
• Estimated cost per script: $1-4 in API costs

Ideal For

• Content creators who turn trending discussions into long-form video content
• Commentary channels that need well-researched scripts quickly
• News explainer channels transforming community discussions into structured narratives
• Content agencies producing video scripts at volume from social media trends

Tip: Key Techniques Used in This Workflow

• Multi-model diversity -- Using both OpenAI and xAI Grok for different pipeline stages introduces genuine reasoning diversity, catching blind spots that a single model would miss.
• Progressive refinement -- Six stages of processing, each with a single clear objective, produces dramatically better output than attempting everything in one pass.
• Scoped vector stores -- Four separate Qdrant instances with different knowledge domains prevent context pollution and give each agent precisely relevant retrieval results.
• Parallel web research -- Eight SerpAPI queries across different angle variations ensure comprehensive coverage of the topic space.
• Reddit as content seed -- Using trending Reddit discussions as starting points guarantees audience-validated topics with built-in engagement signals.

Download

The workflow.json file in this folder can be imported directly into your n8n instance via Settings > Import Workflow.