The article "Towards Spec-Driven Test Automation: Part 1" discusses how a green test suite may not truly reflect software quality. It explores the limitations of relying solely on test pass rates and introduces the concept of specification-driven testing as a more robust approach. The post is published on Towards Data Science.
The article titled "Towards Spec-Driven Test Automation: Part 2" discusses the implications of a single test run and what it actually proves. It appears on the Towards Data Science platform.
I tried to make my ETL pipeline production-ready. Three things broke.
Increase the effectiveness of your coding agents through end-to-end testing. The post How to Run End-to-End Tests with Claude Code appeared first on Towards Data Science .
Turning Codex from an interactive assistant into a programmable automation component The post Running Codex as a Headless Agent appeared first on Towards Data Science .
My approach to guiding the choice between Eppo and Statsig, and the lessons learned The post Picking an Experimentation Platform: A Retrospective appeared first on Towards Data Science .
A practical data engineering onboarding workflow for environment setup, automated testing, and AI-assisted development. The post Your First Task as a Data Engineer in a New Company?
Enterprise Document Intelligence [Vol. 1 #8B] - A fixed BASE, the rules each question needs, one registry: the dispatcher that turns a parsed question into a typed LLM call The post Assemble Each RAG Generation Prompt from a Base Prompt Plus the Rules Each Question Needs appeared first on Towards Data Science .
The article discusses how context engineering is evolving and outlines practical ways data scientists can incorporate the newest guidelines into their everyday work. It explains the importance of adapting to these changes to improve model performance and relevance. The piece offers actionable steps for integrating context engineering into typical data science workflows.
Enterprise Document Intelligence [Vol. 1 #8C] - Structured output is the start of validation, not the end: check the evidence, accept not-found, loop the feedback The post Validating the RAG Answer Before the User Sees It: Spans, Quotes, and the Feedback Loop appeared first on Towards Data Science .
A practical walkthrough using text-to-SQL as the example The post Why I Stopped Using One Agent and Built a Multi-Agent Pipeline Instead appeared first on Towards Data Science .
The article "How to Fine-Tune an LLM: An End-to-End Guide" offers a practical, hands‑on walkthrough for fine‑tuning large language models in real‑world scenarios. It covers the entire process from data preparation to deployment, providing readers with actionable steps to adapt LLMs to specific tasks. The guide is aimed at practitioners looking to implement fine‑tuning in a structured, end‑to‑end manner.
Prompt engineering helps you write better prompts—but it doesn’t help you change them safely. This article explores a common production failure where a simple variable rename breaks every live call, and introduces a lightweight static analysis tool that treats prompts like contracts, catching breaking changes before they ship.