How Auto‑Ontology Powers Explainable AI Agents for Nepal Finance Data
Fintech developers in Nepal often need an AI assistant that can answer regulatory‑level questions over public‑API feeds—like a list of transaction‑…
Latest posts
How to Use LLM Function Calling for Structured Extraction from JSON APIs
You need clean, typed rows from a noisy JSON endpoint, but writing custom parsers for every schema quickly becomes a maintenance nightmare; using L…
How Generators and Lazy Evaluation Can Stream Millions of RSS Posts Efficiently
You’ve built a plugin architecture that pulls RSS data into Python, but when the Discord Engineering feed grows or you start aggregating dozens of …
How to Build a Robust Plugin Architecture in Python Using Real RSS Data
You're running an RSS ingestion pipeline that hard‑codes every transformation, so every new business need forces you to edit core code, risk re…
How to Build Autonomous Data Pipelines in Python Using AI Agent Skills
Ever wondered why your LLM‑driven agents still need Airflow or a custom scheduler to move data from an API to a CSV? You can skip the heavyweight o…
How Async/Await Can Speed Up RSS Feed Harvesting for Production LLM Pipelines
You're feeding external news into a multi‑agent LLM pipeline and notice that a single blocking HTTP call stalls the entire message bus. The ans…