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Track Cdemo

Your personal AI coach — adaptive feedback on every prompt, every scenario, every eval

active session
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RAG retrieval — chunking strategies
adaptive
Picked because your retrieval recall@5 dropped 12% last week.
Conversation
3
turns
Avg session: 18 turns
Tutor rating
4.9
/ 5
Across 1,247 learners
Drills unlocked
4/ 5
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Next drill: write the eval
Live session — RAG retrieval
The tutor watches every attempt and adapts its next question to your weakest sub-skill.
Today's focus: RAG retrieval. You'll write a chunking strategy for a noisy 200-page support corpus. Ready?
Lesson opener
You
I'd split by section headings, 800 tokens per chunk, 100-token overlap.
Reasonable starting point. Two issues: (1) section headings vary wildly in this corpus (some sections are 50 tokens, some 4000) — fixed boundaries break long sections. (2) 100-token overlap is fine for prose but loses structure on tables. What would you change?
Adaptive critique — caught fixed-boundary assumption
The tutor remembers your last 30 days of practice.
Tutor's notes on you
What the agent has learned about your gaps. Updates as you reply.
Strength
Solid mental model on prompt structure and few-shot framing.
Gap
Defaults to fixed-boundary chunking. Hasn't tried semantic splitters yet.
Plan
Today: chunking. Thurs: retrieval eval. Mon: end-to-end RAG scenario.