[Hiring] Content Researcher

The gap in what exists

While manual content researchers are available, a tool that automates the initial discovery and filtering process could be significantly more efficient and cost-effective, filling a gap for businesses that need constant content feeds but lack the budget for a full-time researcher.

Wedge to win

Offer a service or tool that can deliver highly targeted social media content faster and cheaper than human researchers for SMBs who need a consistent content stream.

Reputation value (worth doing free for proof) — 60/100

Building an AI-driven social media content discovery tool and showing its effectiveness could be a strong portfolio piece, demonstrating AI integration and data processing skills to potential clients needing automation.

Likely monetization

hourly service / subscription for automated content feeds

Incumbents to beat

manual content researchers

You are an expert AI developer using Next.js 16 App Router, React 19, Tailwind v4, AI SDK v6 (with Gemini for NLP), and Neon Postgres on Vercel. Your task is to build a web application that automates social media content research, targeting the specific needs outlined in the Reddit gig post: 'finding content from social media'.

**MVP Scope:**
1.  **User Input:** A simple form where a user can input keywords/hashtags (e.g., 'sustainable fashion', '#AIart'), target social media platforms (Reddit, X/Twitter initially), and optionally, specific user accounts to monitor.
2.  **Automated Scraping (Mock/Limited):** For the MVP, simulate data retrieval or use a simplified, rate-limited scraping mechanism for Reddit (using `praw` if feasible) and X/Twitter (using `tweepy` if a developer account is available). Focus on retrieving post titles, body, and URLs.
3.  **Basic AI Filtering:** Use Gemini via AI SDK v6 to perform basic relevance filtering on the scraped content. For example, instruct Gemini to score content on a 1-5 scale for relevance to the input keywords and filter out posts below a certain threshold.
4.  **Content Display:** Display the filtered content in a clean, scrollable list with links to original posts and a brief AI-generated summary/relevance score.
5.  **Export:** Allow users to export the curated content to a CSV file.

**Technical Stack:**
*   Frontend: Next.js 16 (App Router), React 19, Tailwind v4
*   Backend: Next.js API Routes (Node.js)
*   Database: Neon Postgres (for storing user queries and results)
*   AI: AI SDK v6 with Gemini (for NLP/filtering)
*   Deployment: Vercel
*   Social Media APIs: Python `praw` for Reddit (consider `snscrape` for X/Twitter if `tweepy` setup is too complex for MVP)

**Build and Verify Gate:**
Develop the core application to allow a user to define a research query, trigger a (simulated or real, limited) content search across Reddit/X, apply basic AI filtering, and display the relevant results in the UI. Ensure the data can be exported to CSV. Prioritize functionality over exhaustive scraping for this MVP.

Begin by outlining the main components: `src/app/page.tsx` for the input form and results display, `src/app/api/research/route.ts` for handling search requests, and basic database schema for `queries` and `content_items` in Neon Postgres. Focus on creating placeholder API calls and integrating Gemini for the filtering logic first.