Can I vibecode SubSignal?
price variesyou'd save no subscriptionbuild time not a true replacement; the loop in one sitting, the corpus nevercategory sales-outreachreplaced by 0 people
NOT REALLY
MOATproprietary datascale infra
Watches Reddit for people describing the problem you solve, and surfaces them as leads
The Build Prompt
copy it and go buildready to paste · 1,718 chars
Build a Reddit buying-signal monitor inspired by SubSignal. Use exactly this stack: Node.js 22 + TypeScript + SQLite. Primary job: on a schedule, fetch new posts and comments from a configured list of subreddits, ask one language model whether each one describes a problem the user's product solves, and deliver the matches to Slack or email with a link and a one-line reason. Start from an empty folder and create the complete working project. Use the official Reddit API with credentials from .env and respect its rate limits and terms of use; never scrape around them. Store every item you have seen in SQLite so the same thread is never delivered twice, including across restarts. Let the user describe their product in plain language in a config file, and build the classification prompt from that rather than from a hardcoded keyword list. Score each match and let the user set a threshold, so the digest can be tightened without code changes. Send a digest rather than one alert per hit, and make the schedule configurable. Alert the user when a run fails or returns nothing for several consecutive runs - a silent crawler is the main failure mode of this kind of tool. Put every secret in .env and provide .env.example. Deliberately exclude these paid-product advantages: a curated subreddit and keyword set, accumulated cross-customer history, managed uptime. Do not fake integrations, deliverability or data you do not have. Write unit tests for deduplication and scoring, and one end-to-end smoke test against recorded fixtures rather than the live API. Create a README with setup, Reddit API terms, cost estimate, architecture and limitations. Run the tests and build before finishing, then fix what fails.
What you lose
- ✕a historical archive you cannot backfill from the live API
- ✕ranking a lead against everything seen before, instead of judging it alone
- ✕a curated subreddit and keyword set you did not have to discover
- ✕deduplication and history across runs
- ✕someone tracking Reddit API terms and rate-limit changes for you
Prior art / alternatives
Why it still works
accumulated historical corpus at terabyte scale