Can AI replace Rankhog?
KINDA · weekend projectThe code here is the easy half, and it is worth building. A script that watches subreddits, keeps the threads already ranking in Google, and drafts a reply against the sub's rules is a one-sitting build that will genuinely find you the conversations worth joining. The gap is what happens next. No agent writes you a Reddit account with a year of comment history in the subs you care about, and Reddit's spam enforcement is aimed exactly at accounts that show up new and start mentioning a product. A shadowban is silent: your comments look live to you and are invisible to everyone else, so you learn about it weeks later. Build the finder, then spend the weeks yourself, or pay someone to have already spent them.
Build me a Reddit opportunity finder and reply drafter to replace Rankhog, personal scale. Requirements: - A Node CLI plus a local page: node find.js runs the sweep, then a page on 127.0.0.1:3000 lists the hits with a draft beside each thread. - My keywords and target subs live in keywords.json. Sweeps hit Reddit's public JSON endpoints (/r/<sub>/search.json, no OAuth) with a real User-Agent, one request every two seconds. - Keep only the threads already ranking in Google for the keyword, checked via Serper.dev (key in .env), those are the ones the models read back. - Store hits in SQLite (better-sqlite3) with age, upvotes, comment count, and whether my keyword appears in the top comments. Never resurface one I dismissed. - Draft each reply with an LLM (key in .env), fed the thread text and the sub's rules from /r/<sub>/about/rules.json, told to answer first and name my product only where it fits. Store the draft, do not send it. - The page shows title, score, the rule summary, and the draft in an editable box with a copy button and a link out. Everything stays on my machine, localhost only, no accounts, no telemetry. I post by hand, from my own account. - Out of scope: anything that posts, comments, upvotes, or logs into Reddit for me. Automated posting is what gets accounts shadowbanned, say so in the README. - README: the Serper and LLM keys, cost per sweep, and a note to spend a few weeks commenting in my target subs before I mention the product.
$ open in your agent (prompt prefilled, you press enter) or copy it raw
prompt copied. want to know what dies next week?
new verdicts + top votes, weekly. free. one-click out.
Because the failure mode is invisible and expensive. Getting a product mentioned on Reddit needs an account people and moderators already trust, and building one is weeks of participation before the first mention. People pay to skip the warm-up, to have posting happen through a real browser session instead of an API that gets flagged, and to have someone else carry the ban risk.
xaccount age, karma, and comment history in the subs that matter
xthe warm-up: weeks of ordinary participation before you can mention a product
xposting through a real browser session rather than the API, which is what keeps accounts unflagged
xper-subreddit rule knowledge and pacing judgment
xshared accounts across a team, and the managed service
Can AI replace Rankhog?
Kinda. The core of Rankhog is buildable in a weekend with the prompt on this page, but there are real gaps: account age, karma, and comment history in the subs that matter, the warm-up: weeks of ordinary participation before you can mention a product. Read the honest list above before committing.
How much does Rankhog cost?
Rankhog costs about $99/month (Standard, checked 2026-07-30), which is $1188 per year.
What do I lose by replacing Rankhog?
Honestly: account age, karma, and comment history in the subs that matter; the warm-up: weeks of ordinary participation before you can mention a product; posting through a real browser session rather than the API, which is what keeps accounts unflagged; per-subreddit rule knowledge and pacing judgment; shared accounts across a team, and the managed service. If any of those are load-bearing for you, keep paying.
Is there an open-source alternative to Rankhog?
Yes — redsignal (Watches subreddits for keyword matches, filters the noise with an LLM, and drafts replies. Covers the finder half, no license declared.). Using prior art is also a valid exit; the prompt is for when you want it exactly your way.