[verdict][curated prompt][source: subsignal.ai]
Can I vibecode SubSignal?
// the value is the network, the data or the infrastructure
Do not mistake the loop for the product. Polling subreddits and asking a model "is this a buying signal?" is an evening, and it is also the part that does not matter. What makes this useful is the accumulated archive behind it: years of threads at a scale you cannot backfill, which is what lets it tell a recurring complaint from a one-off and rank a lead against everything already seen. Your build starts empty on day one and stays empty, because Reddit will not sell you the past. That is a data problem, not a code problem.
confidence: medium
what it is: Watches Reddit for people describing the problem you solve, and surfaces them as leads
Buildability index · an editorial game
- Price variable pricing weight: zero
- Time not a true replacement; the loop in one sitting, the corpus never weight: minus 1
- Category sales outreach no weight
- Moat proprietary data · infrastructure scale weight: minus 4
- Confidence medium weight: zero
- What you lose 5 items weight: minus 2
- Site subsignal.ai (si apre in una nuova scheda) no weight
It is not close. The prompt below rebuilds a piece, not the product.
Gioco editoriale: il verdetto dice se un agente può, l’indice se conviene.
What you build
Poll a list of subreddits on a schedule, filter new posts by keyword, ask one model whether each is a buying signal for your product, and send the hits to Slack or email.
what you need
- Reddit API credentials, within Reddit's terms of use
- OpenAI or Anthropic API key in .env
- Node.js 22 and a scheduler such as cron
- SQLite to remember what you have already seen
The polling loop is an evening of code. The moat is a years-deep Reddit archive you cannot backfill from the live API.
The prompt
The verdict is NOT REALLY, and the prompt stays anyway: it does not replace the app, it rebuilds the part that really is code. The rest is the moat.
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.Curated prompt: written and reviewed by hand for this app. In English on purpose — it is the language coding agents work best in.
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
Why people still pay
Because relevance comes from history. Judging a single post in isolation is what a prompt does; knowing that this complaint has surfaced eleven times this quarter and twice from the same team requires an archive. You can start collecting today and be useful in a year, or pay for the year someone else already spent.
moat: Proprietary data Infrastructure scale what a moat is
accumulated historical corpus at terabyte scale
Free alternatives
Not in the mood to build it? These already exist, they are free or open source, and we checked them one by one.
Rejected (1) — and why
- F5Bot (si apre in una nuova scheda) — The free tier is personal-use only, while lead generation is the business use this app exists for.
Who has already built it
Starting from here is still vibecoding: the prompt is for when you want it exactly your way.
- PRAW (opens in a new tab) — Python Reddit API wrapper; the standard way to poll subreddits.
- Huginn (opens in a new tab) — Self-hosted agents that watch feeds and act on events.
- changedetection.io (opens in a new tab) — Self-hosted change monitoring with notifications.
Do you agree?
The vote balance
Ancora nessun voto: il tuo è il primo.
Nessun voto ancora — il primo pesa.