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Automatic LinkedIn engagement with AI comments using GPT-4o and Phantombuster

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2/3/2026
Lead ManagementWebhookHubSpotSalesforceCRM
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Who’s it for

B2B marketers, recruiters, and personal-brand builders who want to spark conversations on LinkedIn by automatically posting short, relevant comments on fresh industry content—while staying under daily limits.

How it works / What it does

  1. Schedule Trigger fires every hour.
  2. Select Cookie picks a rotating LinkedIn session-cookie (time-slice logic).
  3. Generate Random Search Term (GPT-4o) outputs a realistic AI/BPA keyword.
  4. LinkedIn Search Agent (Phantombuster) scrapes recent posts.
  5. Get Random Post chooses one post and passes its text to Create Comment (GPT-4o) which returns a ≤150-character reply in the chosen language.
  6. Builds linkedin_posts_to_comment.csv, uploads to SharePoint, and launches the Auto-comment Agent to post the reply.
  7. Post URL is logged to linkedin_posts_already_commented.csv to avoid duplicates.
  8. Wait nodes throttle launches to ~120 comments/day.

How to set up

  1. Add credentials: Phantombuster API, SharePoint OAuth2, OpenAI API key.
  2. In SharePoint › “Phantombuster” folder create:
    • linkedin_session_cookies.txt – one cookie per line.
    • linkedin_posts_already_commented.csv with header postUrl.
  3. Edit Set ENV Variables to set default language, comment prompt, company ID, etc.
  4. Adjust schedule or comments-per-launch as needed.
  5. Activate the workflow; it will run hourly and comment on one new post each launch.

Requirements

  • n8n 1.33 +
  • Phantombuster Growth plan (API access)
  • OpenAI account
  • Microsoft 365 SharePoint tenant

How to customize

  • Change tone/length: edit the prompt in Create Comment.
  • Comment more often: raise numberOfLinesPerLaunch and schedule frequency.
  • Use Google Drive/Dropbox instead of SharePoint by swapping storage nodes.

n8n Workflow: Automatic LinkedIn Engagement with AI Comments using GPT-4o and Phantombuster

This n8n workflow automates the process of engaging with LinkedIn posts by generating AI-powered comments and posting them. It leverages Phantombuster to scrape LinkedIn posts, uses OpenAI's GPT-4o model to generate relevant comments, and then posts these comments back to LinkedIn. The workflow includes robust error handling, delays, and conditional logic to ensure reliable operation.

What it does

This workflow automates the following steps:

  1. Schedules Execution: The workflow is triggered on a predefined schedule (e.g., daily) to initiate the engagement process.
  2. Scrapes LinkedIn Posts: It uses Phantombuster to extract a list of recent LinkedIn posts based on configured criteria.
  3. Filters and Prepares Data: The extracted data is processed to ensure it's in the correct format for subsequent steps. It filters out any posts that might not be suitable for commenting.
  4. Generates AI Comments: For each eligible LinkedIn post, it sends the post content to an OpenAI Chat Model (GPT-4o) to generate a relevant and engaging comment.
  5. Conditional Commenting: It checks if a comment was successfully generated by the AI agent.
  6. Posts Comments to LinkedIn: If a valid comment is generated, the workflow uses Phantombuster to post the AI-generated comment to the respective LinkedIn post.
  7. Manages Delays: A Wait node is included to introduce delays between operations, preventing rate limiting and ensuring a more natural engagement pattern.
  8. Error Handling & Logging: The workflow includes logic to handle cases where no comments are generated or other issues occur during the process.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running n8n instance (self-hosted or cloud).
  • Phantombuster Account: With an active session and access to the LinkedIn Post Commenter and LinkedIn Post Scraper Phantoms.
  • OpenAI API Key: For the OpenAI Chat Model (GPT-4o) to generate comments.
  • Microsoft SharePoint (Optional): While a SharePoint node is present in the JSON, it is not connected to the main flow. Its purpose is unclear from the provided JSON and might be a remnant or intended for future expansion. It is not required for the core functionality described.

Setup/Usage

  1. Import the Workflow:
    • Download the provided JSON workflow.
    • In your n8n instance, go to "Workflows" and click "New".
    • Click the "Import from JSON" button and paste the workflow JSON.
  2. Configure Credentials:
    • Phantombuster: Set up your Phantombuster credentials in n8n. You will likely need your Phantombuster API key.
    • OpenAI: Set up your OpenAI credentials in n8n with your API key.
  3. Configure Nodes:
    • Schedule Trigger: Adjust the schedule to your desired frequency (e.g., daily, hourly).
    • Phantombuster Nodes:
      • LinkedIn Post Scraper: Configure the Phantom's arguments, such as the LinkedIn profile URL to scrape from, number of posts, etc.
      • LinkedIn Post Commenter: Configure the Phantom's arguments, ensuring it can receive the post URL and the generated comment.
    • AI Agent (OpenAI Chat Model): Review the prompt used by the AI Agent to generate comments. You may want to refine it to ensure the comments align with your desired tone and content. The current setup uses gpt-4o.
    • Edit Fields (Set) Nodes: Review and adjust any data transformations if your specific Phantombuster output or AI output requires different mapping.
    • If Node: The conditional logic checks for the presence of an AI-generated comment. Ensure this condition ({{ $json.comment }}) matches the output field from your AI Agent.
    • Wait Node: Adjust the delay duration as needed to avoid rate limits on LinkedIn.
  4. Activate the Workflow: Once configured, activate the workflow to start automating your LinkedIn engagement.

Note: The Microsoft SharePoint, Convert to File, and Extract from File nodes are present in the JSON but are not connected to the main flow, implying they are either unused, for future expansion, or part of a different workflow segment not included in this definition. They do not impact the core functionality of automated LinkedIn commenting.

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