Non-Brand Data | Cornellius Yudha Wijaya | Substack

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RAG-To-Know🔍

RAG Evaluation Monitoring and Logging with Opik

NBD Lite #53 How you splitting your data can affect the RAG performance

May 14, 2025 • Cornellius Yudha Wijaya

9 Chunking Strategies to Improve RAG Performance

NBD Lite #52 How you splitting your data can affect the RAG performance

Mar 10, 2025 • Cornellius Yudha Wijaya

Explainable RAG for More Trustworthy System

NBD Lite #51 Evaluate both the retrieval and generation in systematic ways

Feb 14, 2025 • Cornellius Yudha Wijaya

Enhance RAG Accuracy with Corrective-RAG (CRAG)

NBD Lite #50 Implement self-reflection for the retrieved documents

Feb 6, 2025 • Cornellius Yudha Wijaya

career

My book is out: Python Data Analysis, Fourth Edition

Co-written with my co-author, and what the year of writing it was like.

Jul 4 • Cornellius Yudha Wijaya

Fix it or throw it away: deciding what to do with an AI output

The harder part is knowing which problems you can fix and which ones mean starting over.

Jun 30 • Cornellius Yudha Wijaya

Why Most GenAI Workflows Need a Review Loop

A Better Prompt Is Not Enough

Jun 24 • Cornellius Yudha Wijaya

Manager Memo: Reviewing GenAI Output Before It Reaches Stakeholders

A guide for managers who approve AI-assisted work: what to check, when to reject, and how to talk to stakeholders about it.

Jun 20 • Cornellius Yudha Wijaya

python

My book is out: Python Data Analysis, Fourth Edition

Co-written with my co-author, and what the year of writing it was like.

Jul 4 • Cornellius Yudha Wijaya

Batch Screening Fundamentals with Financial Modeling Prep and Streamlit

Build a Lightweight Stock Screener For Your Fundamental Analysis

Jan 7 • Cornellius Yudha Wijaya

Building an Open-Source Microservice for Financial Data Retrieval with Financial Modelling Prep

Company-Fundamental Tracking Microservice that is Suitable For Your Requirements.

Dec 6, 2025 • Cornellius Yudha Wijaya

Python 3.14: 12 Features You Can Use Today

The addition features you should not miss

Oct 22, 2025 • Cornellius Yudha Wijaya

🚀 Join Non-Brand Data for free AI + Data Science tips

Recent posts

Fix it or throw it away: deciding what to do with an AI output

The harder part is knowing which problems you can fix and which ones mean starting over.

Jun 30 • Cornellius Yudha Wijaya

Why Most GenAI Workflows Need a Review Loop

A Better Prompt Is Not Enough

Jun 24 • Cornellius Yudha Wijaya

Manager Memo: Reviewing GenAI Output Before It Reaches Stakeholders

A guide for managers who approve AI-assisted work: what to check, when to reject, and how to talk to stakeholders about it.

Jun 20 • Cornellius Yudha Wijaya

What Most GenAI Evaluation Workflows Get Wrong

Reliability is not a property of the final answer. It is a property of the whole system that produced it.

Jun 14 • Cornellius Yudha Wijaya

From Prompt to Reliable Output: A Practical GenAI Evaluation Workflow

A concise guide to achieve success in your production GenAI generation

May 31 • Cornellius Yudha Wijaya

Best MCP Servers for Stock Market Data

The best MCP servers for connecting AI agents to financial workflow

May 21 • Cornellius Yudha Wijaya

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