Should you build your own IdeaFast?
Scans Reddit conversations, clusters them into scored pain themes backed by real quotes, and turns the strongest into startup ideas
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.
ENOriginal research content in English. Original prompt preserved in English.
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.The prompt opens pre-filled in your agent. Review it before running.
What would building your own look like?
Pull posts and comments from a handful of public subreddits, classify complaints with an LLM, cluster them into named pain themes, and rank them with clickable quote evidence.
What you will need
- Anthropic or OpenAI API key
- embedding model
- SQLite
- patience with Reddit rate limits
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.
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
How much does IdeaFast cost?
- Monthly billing
- $19/mo$19/mo
- Per year
- $228/yr$228/yr
- On a Brazilian card, with 3.5% IOF
- R$99.29/moR$1,191/yr
Saved to My list. You will see a notice on this site when the price changes.
You complete the purchase on IdeaFast’s site. Vibe Radar does not handle payments.
| Plan | Monthly | Annual (per month) | What is included |
|---|---|---|---|
| explorer | $9/workspace≈ $9 | - | 1 scan/day; 1 subreddit/scan; 3 evidence quotes/pain point; 2 ideas/pain point. |
| founder | $19/workspace≈ $19 | - | 5 scans/day; 2 subreddits/scan; 10 evidence quotes/pain point; 5 ideas/pain point. |
| builder | $49/workspace≈ $49 | - | 10 scans/day; 5 subreddits/scan; 30 evidence quotes/pain point; 10 ideas/pain point. |
Free tierno free tier
Billing termsMonthly only; no annual plan was publicly offered. Each paid plan has a 7-day trial.
Additional costsExtra scan packs cost $5 for 2 scans and do not expire.
verified 2026-08-12 · source ↗
Is it cheaper to build or buy IdeaFast?
Adjust the numbers: hours to build, your hourly rate, running costs and the subscription price.
Over 24 months, subscribing is cheaper.
Starting hours estimated from the analysis (multi-day). Does not price what you give up (support, integrations, security).
Can I rebuild IdeaFast?
Kinda. The core of IdeaFast is buildable in a weekend with the prompt on this page, but there are real gaps: 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. Read the honest list above before committing.
How much does IdeaFast cost?
IdeaFast costs about $19/mo (Founder, checked 10/20/2026), which is $228 per year.
What do I lose by replacing IdeaFast?
Honestly: 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. If any of those are load-bearing for you, keep paying.
Is there an open-source alternative to IdeaFast?
Yes: 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). Using prior art is also vibecoding; the prompt is for when you want it exactly your way.