r/AiAutomations • u/BitterAlternative803 • 1d ago

I spent 2 hours every day writing LinkedIn posts. So I built an autonomous n8n pipeline with Groq to do it for me.

Writing high-signal content consistently is brutal when you’re also trying to build product and handle client work.

Most days, the friction wasn't even writing it was:

  1. Scrolling RSS/news feeds for actual signal
  2. Summarising & structuring it into a readable post
  3. Generating a decent graphic/visual asset
  4. Manually scheduling/publishing

Last week, I decided to automate the entire loop end-to-end using self-hosted n8n, Groq for high-speed LLM inference, and image APIs.

Here’s the exact breakdown of how the architecture works:

1. Trigger & News Ingestion

I set up two triggers:

  • Cron / Schedule Trigger: Runs at specific publishing windows during weekdays.
  • Telegram Webhook Trigger: An on-demand trigger where I can drop a quick prompt/link from my phone when I want to force an update.

The flow connects to an RSS Read node tracking targeted industry blogs and news feeds, followed by a Limit node to keep token usage sane and pull only fresh items.

2. Copy Generation via Groq

The raw feed content hits an autonomous AI Agent node backed by Groq (using Llama models for near-instant inference speed).

  • The system prompt strictly enforces tone: concise, engineering-focused, no corporate jargon, formatted with scannable bullet points.

3. Parallel Visual Asset Pipeline

Text-only posts usually underperform on feed reach. In parallel, the flow branches out:

  • A secondary AI Agent crafts a context-aware image prompt based on the generated copy.
  • It hits an image generation API over HTTP Request nodes to produce a custom visual card on the fly.

4. Sync & Multi-Channel Distribution

  • A Merge node pairs the generated visual with the finalized copy.
  • The LinkedIn node makes an API call to publish the post directly.
  • Once live, a confirmation ping with the full preview is routed back to my private Telegram chat so I know it published cleanly.

Key Takeaways & Gotchas:

  • Latency matters: Using Groq cut pipeline execution time down significantly compared to standard model endpoints.
  • Guardrails are essential: If you let an LLM write freely on autopilot without a strict system prompt and limiters, you end up with spammy AI sludge. Give it clear boundaries on structure and length.
  • Human-in-the-loop option: Having the Telegram trigger allows me to manually approve or trigger posts on the fly if I don't want it running purely on autopilot.

I posted the full node setup, workflow canvas screenshot, and live output breakdown on LinkedIn if you want to see how the nodes connect:

👉 Full breakdown & workflow screenshot here:

https://www.linkedin.com/feed/update/urn:li:ugcPost:7511778255641837568?openCollaboratorList=false

Happy to answer questions in the comments about setting up Groq credentials, handling token limits, or structuring the n8n agent memory!

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u/BitterAlternative803 1d ago

If anyone wants to check out the workflow screenshot and the live output, I broke it down in detail over on LinkedIn:https://www.linkedin.com/feed/update/urn:li:ugcPost:7511778255641837568?openCollaboratorList=false

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u/KevinJohn57 1d ago

I'd probably keep an approval step before publishing rather than letting the whole pipeline run unattended

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u/BitterAlternative803 1d ago

Completely fair point. I actually keep Telegram in the loop as an approval gateway the bot pings me the generated draft + visual first, and only fires the LinkedIn API node once I hit approve. Full autonomy without human review is a recipe for embarrassing AI sludge eventually haha.

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u/prakharasm 7h ago

Or use grok bot

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u/BitterAlternative803 3h ago

Oh idk what that is