Prerequisites
- Node.js and npm installed.
- An OpenAI or Google model API key.
- Upstash Redis credentials if you want production-grade rate limiting.
- A product idea stated as a customer problem, not just a solution name.
Step 1 - Clone and run the project
git clone https://github.com/Eldergenix/Reddit-Product-Validation.git
cd Reddit-Product-Validation
npm install
npm run dev
Open the local Next.js URL printed by the dev server. Before adding real research volume, run a narrow idea through the UI and confirm that the workflow can reach the report screen.
Step 2 - Configure model and rate-limit credentials
Create .env.local and add one model provider. Add Redis when you want to protect the workflow from accidental repeated runs.
OPENAI_API_KEY=...
# or
GOOGLE_GENERATIVE_AI_API_KEY=...
UPSTASH_REDIS_REST_URL=...
UPSTASH_REDIS_REST_TOKEN=...
Keep model keys server-side. Do not expose them to browser components or analytics events.
Step 3 - Write the product idea as a research brief
The agent will do better if the input separates the customer, painful workflow, current workaround, and buying trigger.
Example brief:
Customer: freelance designers who work with local service businesses.
Pain: they lose project history across email, Slack, Google Drive, and invoices.
Current workaround: manual folders and search.
Buying trigger: a client disputes scope or requests follow-up work after months.
Idea: an AI workspace that creates searchable project memory from approved sources.
Avoid asking the agent to validate "AI for designers." Ask it to validate a costly situation that people already complain about.
Step 4 - Run phase one: community discovery
Start with broad communities, then let the agent suggest narrower subreddits. Review the suggestions manually before phase two.
Good acceptance checks:
- The subreddit has recent posts from the likely customer, not only vendors.
- The posts discuss the workflow pain directly or adjacent workarounds.
- The subreddit rules permit research observation.
- The comments include repeated language, not one viral outlier.
- At least three candidate communities preserve source URLs for later review.
Reject communities that are mostly promotional, inactive, or unrelated to the buyer.
Step 5 - Run phase two: signal extraction
Ask the analysis phase to separate evidence types. A useful report should include:
| Signal | What to look for | How to use it |
|---|
| Pain points | repeated complaints, manual work, lost time | sharpen the problem statement |
| Alternatives | tools people already use | map competitive displacement |
| Payment intent | budget, procurement, paid-workaround language | estimate monetization confidence |
| Demand trend | repeated posts across time and communities | avoid one-off anecdotes |
| Early adopters | roles that complain most specifically | choose first outreach segment |
| Scorecard | build, refine, research more, or stop | decide next product step |
Reasoning rule: every extracted signal should answer "what would I build or test differently because this evidence exists?" If the answer is nothing, keep the note as context rather than a decision driver.
Step 6 - Convert the report into an experiment
The validation report is not the final decision. Turn it into one concrete experiment:
- Pick the highest-confidence customer segment.
- Write a landing-page headline using the actual problem language from the report.
- Create one prototype or mock workflow.
- Ask five target users whether the problem is painful enough to change behavior.
- Compare their responses against the agent's assumptions.
Step 7 - Add governance before scaling
If you connect live Reddit APIs or automated collection, add:
- Rate limits by user and idea.
- Source URLs for every extracted claim.
- A terms-of-service review checklist.
- A rule that the agent summarizes public discussion without automated outreach.
- A confidence label for weak or sparse evidence.