Reddit comment automation

What this does

You give it a list of Reddit threads you want to comment on. The workflow scrapes each thread, understands what the conversation is actually about, then writes a comment in your voice that earns engagement instead of getting downvoted. Every comment lands in a Google Doc for you to review before anything posts to Reddit.

The product mention – if there is one – is a side note inside a comment that's primarily helpful. Not a sales pitch with a link tacked on.

The problem this solves

Reddit is the highest-quality referral traffic source on the internet, and the hardest one to crack. Subreddits eat self-promo for breakfast. Comments that smell like marketing get downvoted within minutes, the account gets shadowbanned, and the post you were defending gets removed by mods. Most "Reddit marketing" attempts make things worse for the brand they're promoting.

The working approach is the slow one: be in the relevant subreddits for months, be genuinely helpful in 90% of your comments, mention your product in 10% only when it actually answers the question. That works. It also takes 20 minutes per comment to do well – read the thread, get the context, write something useful, edit it three times so it doesn't sound like marketing.

Scale that and you can't. A founder can do maybe 5 comments a day before the time cost kills the rest of the work.

This workflow takes the time cost off your team. The comments come back drafted in your voice, tuned to the thread's actual conversation, with the "is the product mention earned here?" decision already made. You review for 30 seconds, accept or edit, post manually. The 20-minute job becomes a 2-minute job.

What you put in

A Google Sheet row per thread you want to comment on:

• The Reddit thread URL
• A short note on why you're commenting (optional but helps – e.g., "client uses our product, give a relevant tip" or "general help, no product mention")
• Which client / product / persona is commenting (so the voice matches)

The workflow picks up rows where status = "Planned."

What you get out

For each thread, a Google Doc with:

• A short summary of what the thread is actually about (so you don't have to re-read it before reviewing)
• 1-2 drafted comments to choose from – different angles, different lengths
• A flag on whether a product mention belongs in the comment, with a one-line reason
• The comment(s) written in plain, conversational language with the kind of small specifics that make a comment read as written by a real person

The sheet status flips to "Drafted" so you know which threads are ready for review.

How long per comment

Workflow time: about 30-60 seconds per thread. The thread scrape + GPT call is fast.

Your review time: 30-60 seconds. Read the summary, pick the better draft, copy-paste to Reddit, post.

End-to-end per comment: about 2 minutes. Down from 15-20 if you wrote them by hand.

When this is a good fit

• You already have target subreddits you're active in. The workflow doesn't pick subreddits or topics – it drafts the comment for a thread you've already identified.
• You're willing to review every comment before it posts. This is not a "set and forget" tool. Reddit punishes anything that looks automated, and the only way to keep it from looking automated is human review.
• You have someone (you, a contractor, an editor) doing the daily routine of reading the queue, picking the best draft, and posting. The workflow is the writing-heavy part, not the posting part.
• Your goal is helpful, earned referral traffic – not link injection.

When this isn't a good fit

• You want a bot that posts comments without review. Don't do this. Reddit will catch it. Your brand will eat the reputation hit.
• You don't have target subreddits yet. Spend a month being active in 3-5 communities before automating anything. Reddit reputation is per-account, and accounts with no history get shadowbanned faster.
• You're posting product mentions in 90% of comments. The workflow draft will reflect that, the comments will get downvoted, you'll waste compute. Adjust the input pattern first.

What's actually under the hood

The workflow is small – 7 nodes – because the Reddit part is the simple bit. Here's the flow:

1. Read the next "Planned" row from your Google Sheet
2. Scrape the thread via Apify's Reddit scraper (gets the post + all comments + scores so the model can see what's been upvoted)
3. GPT-4.1-mini call: write 1-2 comment drafts in the persona's voice, given the thread context. The prompt enforces: sound like a real person sharing experience, the product mention is a side effect (not the goal), match the thread's tone (technical / casual / tactical / venting).
4. GPT-4.1-mini second call: review the drafts and decide if a product mention is earned. Returns the final draft + the reasoning.
5. Write everything to a Google Doc for review
6. Flip the sheet row status to "Drafted"

The "sound like a real person" part is entirely in the prompt. I spent 30+ rounds tuning it against real Reddit accounts to remove the AI tells: no "Great point!", no "I hope this helps," no formal phrasing, no five-paragraph structure when one paragraph fits.

What you own at handover

• The n8n workflow file
• The full prompt text – both the comment-writing prompt and the product-mention-review prompt
• The Google Sheet template
• A Loom walking through the daily workflow: how to add threads to the queue, what to look for in the Google Doc review, common edits to make
• A short doc on Reddit account management – why account age matters, how to avoid getting shadowbanned, how often to post per subreddit

Why I can help

Reddit-tone is a craft. AI-written Reddit comments are almost always bad – wrong register, too formal, too long, too eager. The default behavior of any LLM is to be helpful and structured. Reddit comments need to be helpful and unstructured.

The prompt that bridges that took me 30+ rounds. The key is showing the model what good Reddit comments look like, then constraining the structure: 1-2 short paragraphs, lowercase first word sometimes, the kind of small concrete detail that makes it credible ("I tried this last month and X happened"). That structure isn't in any default LLM output – you have to force it.

I've built this for 4 clients in 2025. Reddit reputation is fragile, and I lost one account in the first month because the prompt was too aggressive about product mentions. The current prompt is the version that came out of that lesson.

What it costs to run

Per comment: about $0.01-$0.02 in OpenAI tokens, plus Apify scraping (a few cents per thread). Under $0.05 per drafted comment.

Build cost: 1-2 weeks of my time to wire the workflow, tune the prompts to the persona's voice, set up the sheet template, and train you (or your contractor) on the review loop.

How to start

Book a call. Bring 5-10 Reddit threads you've wanted to comment on but haven't. We'll run the workflow on them live during the call. You decide on the spot whether the drafts pass the "would I actually post this?" test.