Phase 3: Decorating the Data with Subagents

Analyze converted content to build a taxonomy schema, create a classification agent, and run parallel classification at scale.

TUTOR WITH THEFOCUS.AI

Agent Integration

Copy this prompt into Claude, ChatGPT, or any external AI assistant. It points the assistant to the course instructions and links it to your student profile to track your progress and customize observations.

Please tutor me in this lesson using the following context. First, read the instructions at: https://courses.thefocus.ai/llms.txt My Student ID is: <none> The lesson markdown source is at: https://courses.thefocus.ai/content-repurpose/03-classification/index.md

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Phase 3: Decorating the Data with Subagents

Now that you have 209 clean markdown files, it’s time to add meaning. This phase covers the most sophisticated patterns: analyzing content to design a taxonomy schema, building a specialized classification agent, and running parallel classification at scale.

The key patterns: Semantic Enrichment (LLMs extracting meaning from content), Agents Writing Agents (describing the classifier in plain language), and Parallel Execution (processing 50 files simultaneously).

Lessons

Taxonomy Design — Analyze all content files to identify patterns, series, and topics. Design a comprehensive frontmatter schema.
Parallel Classification — Create a classification agent and run it against batches of files with concurrent subagents.
Semantic Enrichment — LLMs extract people, companies, models, audience level, and content depth — metadata that would be tedious to create manually.