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You can learn software development through step-by-step threads, frontend/backend/mobile roadmaps, GitHub trending projects, Cursor rules, job portals, and ready-made website templates.

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AI-Automated Reddit Trend Scraper that saved us $1000/month on Content Creation

Using Honojs, OpenRouter and Scrapefast, how we built one on our own

Aug 29, 2026

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AI-Automated Reddit Trend Scraper that saved us $1000/month on Content Creation cover image

Hello and welcome to my new blog

In today’s story, we will be discussing an Automated Trend Scraper that helps us save more than 4hours/day and create stunning content, replacing $1000/month on content creation.

Manual trend monitoring is a time sink.

Scouring Reddit, X, and LinkedIn daily to catch target audience discussions wastes hours that could go into building. To solve this for iHateReading, we built an autonomous AI agent to handle the entire pipeline: collecting raw discussions, enriching them with context, and generating tailored content ideas.

Here is how the system works and how we put it together using Hono, OpenRouter, and our proprietary scraper, ScrapeFast.

The 5-Step Pipeline

1. Collect: Scheduled cron jobs fire four times a day, running within a 10-minute execution window. The agent pulls RSS feeds from key subreddits alongside relevant X and LinkedIn posts using our lightweight ScrapeFast engine.
2. Enrich: Raw posts lack context. The agent passes scraped payloads to OpenRouter, extracting underlying pain points, core questions, and sentiment rather than just storing titles.
3. Store: Structured records land in a clean database with key metadata (source, category, extracted problem) mapped for efficient querying.
4. Read: Instead of endless doom-scrolling, a custom interface aggregates the pipeline into a single daily readout that takes under five minutes to review.
5. Act: A dedicated AI chatbot runs on top of the dataset. It answers natural-language queries about emerging trends and directly generates content ideas. For example, it recently identified strong demand for an “AI Tools List” page optimised for SEO.

Proof of Concept

The image added below is proof of the AI agent running in a terminal with one command

It scrapes the latest trending posts from targeted subreddits and AI enrich it further before storing the database

AI agent running in a terminal, fetching trending posts along with data enrichment

Image 2 shown below renders the 100+ daily fetched subreddit posts of our interests; this helps to provide detailed context about each Reddit post and a relativity score.

Relative score and AI context message become important as they give an overview before reading the full comment/posts; I’ve realised that our Email/Gmail inbox should have this feature 😃

Reddit posts with context summary and relative score in our iHateReading admin dashboard

Image 3, as shown below, is where I did some personal improvisation. I quickly integrated an AI chatbot, which can access tools such as search/filter/find from the Reddit posts database.

I’ll explain in a few words

> The AI chatbot, as shown below, has the Directory posts context.

> The AI chatbot can search/find/filter the posts if needed as a tool for the AI agent

In this way, the AI chatbot can give answers based on trending posts. I can give more context to the AI chatbot by giving a timeframe in the prompt, for example, “Give me the last 20 days' trending posts summary”

Tech Stack Breakdown

Hono: Powers the backend API. Its minimal overhead and edge-ready performance ensure fast, lightweight background scheduling without heavy server footprints.
OpenRouter: Serves as the AI layer, enabling flexible model routing to enrich raw text, summarise discussions, and apply conversational intelligence to stored trends.
ScrapeFast: Our custom in-house scraping tool designed for reliable, fast data ingestion across Reddit, social feeds, and web sources.

Trend Scraper for Reddit, LinkedIn and X

We built the same agent for a trend scraper for LinkedIn and another one for X(formerly Twitter)

We can’t run the platform while spending 4 hours a day doing manual research for our website content, so AI is the best choice for the same.

We built a similar agent for LinkedIn and another one for X; both do the same work in the same process for each of the platforms.

In the end, we manually read all the posts and use an AI chatbot to finalise the next plan of content and do better work, solve real problems

Conclusion

We eliminated manual topic research for iHateReading.

Instead of guessing what to write, the agent continuously surfaces real user problems as they emerge. We step in and build the solutions.

PS — We have sold this AI agent to one of our clients; if you need one, DM me at shreyvijayvargiya26@gmail.com

We can build a custom agent for Agencies, startups, and companies. We look forward to your message.

That would be enough for today; see you in the next oneCheersShrey

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