Towards Data Science
Jun 12
I Thought Data Engineering Was Just Writing Scripts. I Was Wrong.
I tried to make my ETL pipeline production-ready. Three things broke.
Why I Stopped Using One Agent and Built a Multi-Agent Pipeline Instead
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 .
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Towards Data Science
Jul 10
I Built My Second ETL Pipeline. This Time, I Started Thinking Like a Data Engineer
Building a production-ready RSS pipeline with Python, Docker, PostgreSQL, and Kestra The post I Built My Second ETL Pipeline. This Time, I Started Thinking Like a Data Engineer appeared first on Towards Data Science .
Towards Data Science
Aug 27
Agentic AI Is Rewriting The Analytics Stack But There's One Skill It Still Can't Touch
The article discusses how agentic AI is reshaping the analytics stack by taking over more execution tasks. It raises the question of which responsibilities should remain with human analysts versus AI agents and explores the importance of this distinction. The piece highlights the evolving role of AI in analytics and the need to define clear boundaries between human and machine work.
Towards Data Science
Aug 17
Webwright: Why AI Web Agents Should Write Code, Not Click
For years, web agents have worked one click at a time—and often fallen apart on long tasks. Microsoft Research’s Webwright makes a different bet: give the model a terminal and let it write the program instead.
Towards Data Science
Sep 18
Multi-Agent Coding Isn’t Enough — Agents Need a Commitment Layer
Multi-agent coding systems don't necessarily fail because agents can't communicate. They can fail because important commitments made in conversation have nowhere to live afterward. The post Multi-Agen...
Towards Data Science
1d ago
Where the Agent Development Lifecycle Fits
The article "Where the Agent Development Lifecycle Fits" discusses how to coordinate the development of agent capabilities with the applications they power. It highlights the importance of aligning agent creation processes with the needs of the end‑use cases they support. The piece appears on Towards Data Science and focuses on integrating agent development into broader application workflows.
Towards Data Science
Aug 14
RAG Workflow and Loop Engineering: The Dispatcher That Decides When to Loop and When to Stop
Enterprise Document Intelligence [Vol. 1 #13] - Putting the patterns together, and why this is what “agentic RAG” should look like The post RAG Workflow and Loop Engineering: The Dispatcher That Decides When to Loop and When to Stop appeared first on Towards Data Science .
Towards Data Science
Aug 10
Building an Agent-Ready Data Warehouse: What Traditional Architectures Do Wrong
Giving an AI agent access to a data warehouse doesn't automatically make it agent-ready. The real challenge lies in teaching the agent what the data means and when it's reliable enough to use.
Towards Data Science
Jun 1
Escaping the Valley of Choice in BI
Why Agentic BI threatens an entire profession The post Escaping the Valley of Choice in BI appeared first on Towards Data Science .
Towards Data Science
Aug 4
Using Agents as Tools
Building manager–specialist workflows with the OpenAI Agents SDK The post Using Agents as Tools appeared first on Towards Data Science .
Towards Data Science
Aug 26
Is Agentic AI Just Automation?
The article titled "Is Agentic AI Just Automation?" argues that many so‑called agents are merely flowcharts in disguise. It explains why this misconception exists and suggests what kinds of systems should be built instead to achieve true agentic AI.
Towards Data Science
Jun 15
The Protocol That Cleaned Up Our Agent Architecture
A detailed look at MCP that turned my scattered tool definitions into a stable, discoverable server The post The Protocol That Cleaned Up Our Agent Architecture appeared first on Towards Data Science .