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Day 1: Tokens, Context Windows, and Why Models Forget Mid-Task3 views · 1 like
PostgreSQL Performance Tuning: The Configuration Changes That Actually Matter2 views
System Design Interview Cheat Sheet: The Framework That Gets You Hired at FAANG2 views
Day 9: Eval Harness Day One1 view · 1 like
Day 3: Embeddings That Survive Domain Jargon1 view · 1 like

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CheatCoders

Day 1: Tokens, Context Windows, and Why Models Forget Mid-Task

Tokenization, context windows, and recency bias silently break chatbots — measure token budgets and attention to the middle before you pick a model or RAG design.

AI Machine Learning System Design

Day 2: Transformer Attention as a Systems Diagram

Treat transformer attention, KV cache, and batching as a production data path — latency, memory, and throughput come from systems choices, not paper diagrams.

AI Machine Learning

Day 3: Embeddings That Survive Domain Jargon

Generic Wikipedia embeddings fail on code and ops jargon — choose, version, and evaluate embedding models against your domain queries and corpus.

AI System Design

Day 4: Vector Indexes Without Magical Thinking

HNSW vs IVF vs pgvector: pick indexes by latency, recall, and filter patterns — a SQL predicate often beats a larger ANN index.

AI AWS Machine Learning

Day 5: Your First RAG Pipeline That You Can Debug

Build a debuggable RAG loop — ingest, chunk, retrieve, generate — with traces, citations, and an explicit failure budget.

Day 6: Chunking Strategies for Code, Tickets, and Runbooks

Fixed, recursive, AST, and late chunking each win on different corpora — pick by code, tickets, and runbooks, not blog defaults.

AI System Design

Day 7: Prompt Contracts: System, Developer, User, Tool

Separate system, developer, user, and tool prompt layers like IAM roles — privileges leak when everything is one blob.

Day 8: Structured Outputs That Compile

JSON Schema, tool-choice, and validators so model output compiles — inventing fields is a bug, not creativity.

AI Machine Learning

Day 9: Eval Harness Day One

Golden questions, faithfulness, hit-rate, and a CI job that fails the build — evals on day one, not after the outage.

AI AWS Machine Learning

Day 10: Project: Internal Docs Chat With Citations

Ship an internal docs chat on Bedrock + OpenSearch or pgvector that refuses uncited answers — a project lab you can demo.