Un proyecto de Mauricio Gallmur· el prompt es gratis · si quieres que un agente lo corra solo, eso es lo que instalo

¿Puedo vibecodear IdeaFast?

PARCIAL · un fin de semana
precio $19/mesahorrarías $228/añotiempo de build varios díascategoría 🔬 investigación de usuarioreemplazada por 0 personas

The pipeline is honest work an agent can do: pull public Reddit JSON, prefilter complaint-shaped text, classify with an LLM, embed and cluster, rank by frequency times severity times recency. A weekend gets you ranked pain themes with real permalinks for two or three subreddits you already know. What does not fall out of one session is everything after the demo: staying inside Reddit's rate limits at scale, picking which communities are worth scanning when you do not already know, deduping the same pain across runs so week two is not week one again, and keeping the LLM bill under the price of the subscription. Verdict is kinda, not yes, because the first run is easy and the tenth is where the product actually lives.

el prompt
Build me a Reddit pain finder: a local CLI plus a small dashboard that reads public
Reddit and turns complaints into ranked pain themes with clickable evidence.

- TypeScript on Node 22, SQLite via better-sqlite3, Hono for the dashboard. One
  repo, one `npm run scan` entrypoint. No accounts, no cloud, no telemetry.
- Input: subreddits.txt plus a timeframe flag (default 90 days). Fetch posts and
  top level comments from Reddit's public JSON endpoints, for example
  https://www.reddit.com/r/<sub>/top.json?t=year. One request every 2 seconds, a
  real descriptive User-Agent, and cache every raw response in SQLite so re-runs
  cost nothing. No OAuth, no logged-in scraping.
- Prefilter to complaint-shaped text with cheap regexes ("I hate", "why is there
  no", "wasted hours", "workaround", "gave up on") before spending a single
  token. This is the whole cost story, do it first.
- Classify survivors with Claude (ANTHROPIC_API_KEY in .env, batched, cached by
  content hash) into: is_pain, severity 1 to 5, one line summary.
- Cluster: embed the summaries, group at cosine similarity above 0.82, then have
  Claude name each cluster and pick its 5 strongest verbatim quotes with
  permalinks. Never paraphrase a quote, evidence has to be clickable or it is
  worthless.
- Score each cluster as frequency x mean severity x recency decay, and persist
  scores per run so a later scan can show what moved.
- Dashboard on localhost:3000: ranked clusters, expandable quotes with permalinks,
  filter by subreddit, CSV export.
- README: how to choose subreddits, the rate limit rule and why breaking it gets
  you blocked, and rough token cost per 1000 comments.
- Out of scope: sources other than Reddit, idea generation, and cross-scan dedupe.
  Get one subreddit list producing clusters you actually trust first.

$ ábrelo en tu agente (prompt listo, tú das enter) o cópialo crudo

por qué la gente sigue pagando

The clustering is not the hard part, the boring infrastructure around it is. Reddit throttles aggressive clients, so a real corpus takes patient background ingestion rather than a scan you kick off and watch. People pay to skip the warm-up and the API bill, not because the data is secret. It is all public.

qué pierdes

xcommunity discovery, you can only scan subreddits you already thought of

xcross-scan dedupe, so repeat runs resurface the same pains as if they were new

xa warmed corpus, every fresh scan pays the full ingestion wait

xcost control, naive LLM classification of a busy subreddit gets expensive fast

xthe idea generation and validation layer on top of the raw clusters

arte previo · úsalo en vez de construir, si prefieresPRAWPython Reddit API wrapper, the usual starting point for the ingestion halfBERTopicTopic clustering over embeddings, covers the grouping step without an LLM
compartir en X ↗"Acabo de reemplazar IdeaFast ($19/mes) con un prompt"
los números

Precio de IdeaFast

planmensualanual (por mes)qué incluye
explorer$9/workspace1 scan/day; 1 subreddit/scan; 3 evidence quotes/pain point; 2 ideas/pain point.
founder$19/workspace5 scans/day; 2 subreddits/scan; 10 evidence quotes/pain point; 5 ideas/pain point.
builder$49/workspace10 scans/day; 5 subreddits/scan; 30 evidence quotes/pain point; 10 ideas/pain point.

plan gratisno free tier

facturaciónMonthly only; no annual plan was publicly offered. Each paid plan has a 7-day trial.

costos ocultosExtra scan packs cost $5 for 2 scans and do not expire.

verificado 2026-08-12 · fuente ↗

preguntas
¿Puedo vibecodear IdeaFast?

Parcial. El núcleo de IdeaFast se arma en un fin de semana con el prompt de esta página, pero hay huecos reales: community discovery, you can only scan subreddits you already thought of, cross-scan dedupe, so repeat runs resurface the same pains as if they were new. Lee la lista honesta arriba antes de comprometerte.

¿Cuánto cuesta IdeaFast?

IdeaFast cuesta unos $19/mes (Founder, revisado 2026-08-01), o sea $228 al año.

¿Qué pierdo si reemplazo IdeaFast?

Con honestidad: community discovery, you can only scan subreddits you already thought of; cross-scan dedupe, so repeat runs resurface the same pains as if they were new; a warmed corpus, every fresh scan pays the full ingestion wait; cost control, naive LLM classification of a busy subreddit gets expensive fast; the idea generation and validation layer on top of the raw clusters. Si alguno de esos te sostiene el negocio, sigue pagando.

¿Hay una alternativa open source a IdeaFast?

Sí: PRAW (Python Reddit API wrapper, the usual starting point for the ingestion half), BERTopic (Topic clustering over embeddings, covers the grouping step without an LLM). Usar arte previo también es vibecodear; el prompt es para cuando la quieres exactamente a tu modo.

Cada semana mueren más suscripciones.

Veredictos nuevos, prompts nuevos, las apps más condenadas de la semana.
Un correo. Te sales en un clic.

gratis para siempre · sin spam · el prompt se queda en el sitio, las muertes te llegan a ti

$semanal: qué recibió veredicto, qué murió.