The PayEng Playbook·36wHow To Review Code That Deals With Money
A systematic 4-step approach to reviewing code in financial systems: start with test files to understand context, verify alignment with issue requirements, mentally solve the problem yourself, then compare the actual implementation against your approach. This method helps catch errors early, provides deeper understanding, and is especially critical for payment systems where mistakes can be costly.
Reinier·34wBuild and Deploy a Real-Time Stock Market App with Alerts, Charts & AI Insights | Next.js, Inngest
A comprehensive tutorial for building a full-featured stock market application with real-time price updates, personalized alerts, interactive charts, AI-powered market insights, and daily news summaries. The project uses Next.js for the frontend, Better Auth for authentication, and Inngest for workflow automation, creating a complete financial dashboard with watchlist functionality.
Medium·37wHow Python + GraphDB Transforms ETF and Company Relationship Analysis
Demonstrates how to use Python and Neo4j graph database to analyze relationships between ETFs and their holdings. Shows data collection from Financial Modeling Prep API, database setup, and visualization techniques to uncover hidden patterns in financial data. Includes practical examples of querying ETF portfolios, identifying overlapping holdings, and discovering investment insights through graph visualization.
DEV·38wI built an AI Agent That reveals Wall Street Sentiment in seconds
A developer built an AI agent using n8n and Bright Data that analyzes Wall Street sentiment by scraping financial news sites and social media posts. The system uses Google Gemini for text summarization and delivers automated sentiment reports via email within seconds. The workflow handles asynchronous data collection, processes unstructured text, and generates actionable market insights without manual intervention.