LinkedIn Content Automation
Reducing content cycle from hours to seconds with Multi-API orchestration and stateful deduplication.
Speed
Hours → Seconds
Quality
Zero duplicate topics
Integrations
5-API Orchestration
Control
Discord Interface
The Problem
LinkedIn content creation is time-intensive, repetitive, and often lacks real-time relevance, reducing posting consistency. Previously, it required manual context-switching across tools, ad-hoc notes, and repetitive tasks to get a post out.
The Solution
Built an AI-driven n8n automation pipeline with live research, LLM-based generation, and Discord-triggered workflows with Supabase state management. It provides end-to-end automation from research and ideation to drafted posts and one-click publish.
- n8n over custom code: Allowed iterating on LLM prompts and API integrations rapidly without code deployments.
- Discord as a control plane: Made Discord the single interface for triggering, reviewing, and publishing. Minimal context switching.
Architecture
Three interconnected workflows handle ideation → drafting → publishing with LLM reasoning.
Key Incidents & Learnings
API Rate Limiting
Issue: Web search API rate limiting and free tier limits causing workflow failures.
Resolution: Implemented multi-AI fallback mechanisms, cached research results, and batched searches. Prompt engineering was also optimized to reduce token usage.
Webhook Connectivity
Issue: Discord bot webhook connectivity issues causing missed triggers.
Resolution: Configured n8n webhook nodes with robust retry logic and proper Discord bot token management to ensure no events are dropped.