IdeaFast

Scans Reddit conversations, clusters them into scored pain themes backed by real quotes, and turns the strongest into startup ideas

KINDA · partial replacement
price $19/mosubscription / year $228estimated build time multi-dayreplaced by 0 people

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.

Build verification: not recorded. How we judge buildability

What you give up

  • 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

Why people still pay

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.

Your build guide

The stack, security requirements, and agent rules for a focused replacement.

Before you start

  • Runtime and tools: Python, SQLite FTS5, a PDF/text extraction worker and a React evidence notebook.
  • Before starting: User-owned or licensed source documents, a local data folder and an optional explicitly configured model provider.
01
Python, SQLite FTS5, a PDF/text extraction worker and a React evidence notebook
02
Data design: Store SourcePost, QuotedComplaint, Theme, MembershipDecision and EvidenceCount; repeated copies by one author do not masquerade as independent demand.
03
Setup: User-owned or licensed source documents, a local data folder and an optional explicitly configured model provider
engineering roadmap

Implementation plan

1

Phase 1

Pin the working slice and create its example input: Review permitted community posts for recurring pain points, cluster source-backed complaints and produce a problem brief with contradictory evidence. Confirm setup: User-owned or licensed source documents, a local data folder and an optional explicitly configured model provider.

2

Phase 2

Implement persistence and write-time invariants before decorating the UI: Store SourcePost, QuotedComplaint, Theme, MembershipDecision and EvidenceCount; repeated copies by one author do not masquerade as independent demand.

3

Phase 3

Connect the working view to real saved state. Preserve source hashes, page/section anchors and exact quotations. OCR and optional generated summaries are derived views, never replacements for originals; label missing text and unsupported claims.

4

Phase 4

Expose the app-specific limits and recovery path in context: This is qualitative research, not a market-size estimate. Use authorized API access or imports, preserve removal states and avoid automatically messaging contributors.

5

Phase 5

Walk through this concrete acceptance case and preserve its exported evidence: Import a cross-posted complaint and a reply explaining an existing solution; count the duplicate transparently and attach the counter-evidence to the proposed theme. Finish the README and backup/restore instructions; report unfinished capabilities explicitly.

the pro prompt
download AGENTS.md
Build the following focused alternative to IdeaFast. This is a deliberately limited personal or small-team substitute, not parity with the paid service.

WORKING SLICE
Review permitted community posts for recurring pain points, cluster source-backed complaints and produce a problem brief with contradictory evidence.

SETUP AND ARCHITECTURE
Use Python, SQLite FTS5, a PDF/text extraction worker and a React evidence notebook. Prerequisites: User-owned or licensed source documents, a local data folder and an optional explicitly configured model provider. Before integrating anything, record actual versions and permissions, plus model files or provider limits only where used, in the README; make unavailable dependencies visible rather than simulating success.

DOMAIN MODEL AND INVARIANTS
Store SourcePost, QuotedComplaint, Theme, MembershipDecision and EvidenceCount; repeated copies by one author do not masquerade as independent demand.

IMPLEMENTATION CONTRACT
Preserve source hashes, page/section anchors and exact quotations. OCR and optional generated summaries are derived views, never replacements for originals; label missing text and unsupported claims. Provide an input/setup view, the main work view, and a review/export view appropriate to this workflow. Preserve the last saved state if a job or save fails. Include empty, loading, permission-denied, partial and retryable-error states. Log identifiers and error categories without secret values or unnecessary private content.

APP-SPECIFIC BOUNDARY AND RECOVERY
This is qualitative research, not a market-size estimate. Use authorized API access or imports, preserve removal states and avoid automatically messaging contributors.

ACCEPTANCE SCENARIO
Import a cross-posted complaint and a reply explaining an existing solution; count the duplicate transparently and attach the counter-evidence to the proposed theme. Also reopen the app after an interrupted operation, confirm the saved record/export remains inspectable, and document the recovery action. These are implementation acceptance requirements, not a claim that this guide has been tested.

DELIVERY
Deliver a runnable repository with migrations or project-format versioning, a non-sensitive example, environment/permission setup, the exact manual acceptance steps, and a backup/export-and-restore walkthrough. Implement the working slice before optional integrations; list any deferred paid-product capabilities honestly. Do not add capabilities outside the working slice just to resemble the original product.

PROJECT RULES FOR AGENTS.md
Keep the domain invariants above executable at the write boundary. Propose scope changes before adding providers or permissions. Never fabricate source evidence, publish results, identity matches or successful delivery. Preserve user originals and require an explicit confirmation for destructive changes or external publication.

$ open in your agent (prompt prefilled, you press enter), copy the prompt or copy or download AGENTS.md

prior art · use these instead of building, if you'd ratherPRAWPython Reddit API wrapper, the usual starting point for the ingestion half↗BERTopicTopic clustering over embeddings, covers the grouping step without an LLM↗
share on X ↗

IdeaFast pricing

planmonthlyannual (per mo)what you get
explorer$9/workspace—1 scan/day; 1 subreddit/scan; 3 evidence quotes/pain point; 2 ideas/pain point.
founder$19/workspace—5 scans/day; 2 subreddits/scan; 10 evidence quotes/pain point; 5 ideas/pain point.
builder$49/workspace—10 scans/day; 5 subreddits/scan; 30 evidence quotes/pain point; 10 ideas/pain point.

free tierno free tier

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

hidden costsExtra scan packs cost $5 for 2 scans and do not expire.

pricing sources checked 2026-08-12 · pricing source ↗

Questions about IdeaFast

Can you build your own IdeaFast with AI?

Partly. 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.

What does the IdeaFast build prompt cover?

The prompt starts with this scope: Review permitted community posts for recurring pain points, cluster source-backed complaints and produce a problem brief with contradictory evidence. Full-product capabilities excluded from the comparison include: 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. Follow the implementation plan and its prerequisites before expanding the build.

How do I use the prompt, AGENTS.md and agent skills?

Start with the IdeaFast prerequisites and stack, then copy the prompt into your coding agent. Save the project rules as AGENTS.md in the project root. Linked skills are optional packages or source instructions for specific tasks; review their current contents and install only those matching the chosen stack. A skill does not supply API credentials or verify the finished app.

How long will this IdeaFast project take?

The catalogue estimate is multi-day for the limited scope. Setup, integration approvals, debugging, deployment and ongoing maintenance can add time. This is an estimate, not a delivery guarantee.

What would I give up by replacing IdeaFast?

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. 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.

What price is this guide comparing against?

The recorded Founder plan is $19/mo (monthly), checked 2026-08-01. Check the linked pricing source before buying. Building your own also has hosting, API and maintenance costs; the recorded amount is not a guaranteed saving.

What can I use instead of building IdeaFast?

The prior-art section lists PRAW, BERTopic as starting points. Review their current scope, license and maintenance before adopting one.

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