Structured Data Extraction with LLM JSON Schemas
How to use OpenAI's structured outputs to turn unstructured text into reliable database records — without parsing fragile prose.
Read more →Articles tagged "AI Tooling"
← All articlesEvaluation-Driven ML Development: Test Your Parser Before Production
How to build an evaluation harness that catches LLM regressions before they hit production — using YAML test cases and structured comparison.
Read more →LLM Provider Abstraction: Design for Swappability
Why wrapping LLM calls in provider classes is essential for production AI features — and how to design the abstraction layer.
Read more →Human-in-the-Loop ML: Building Quality Control Into AI Pipelines
Why every production ML system needs human oversight — and practical patterns for building it into your pipeline from day one.
Read more →Building an LLM Conversation Agent That Maintains Context
How to build an LLM agent that generates contextual messages by combining conversation history, user preferences, and available data.
Read more →Epic: From Scrape to Suggestion — Building an AI-Powered Recruiting Pipeline
A four-part series building an end-to-end AI recruiting pipeline — from scraping job listings to generating personalized candidate messages.
Read more →AI-Assisted Refactoring: A Process That Creates Content
How to use AI tools to refactor code and generate blog content from the same conversation.
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