Ebooks &
cheatsheets.
Reference cards and deep-dive guides on RAG, agents, and AI engineering careers. Free to download, keep one open next to your IDE.
Curated by Param Harrison
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See pricingThe RAG Cheatsheet
The production RAG reference. Chunking, retrieval, reranking, evaluation, failure modes.
AI Engineer Interview Prep Guide
The reference for AI engineering interviews: scope by level, recurring questions, system design patterns, and portfolio shapes.
Advanced agentic RAG: Self-improving retrieval
Routing agents, relevance checks, reflection loops. The patterns that turn a RAG prototype into a self-improving system.
Production AI agents: Architecture and operations
Event loops, tool contracts, memory tiers, evals, deploy flags. The agent patterns that survive production load.
Production coding agents: A harness engineering guide
Build a Claude Code-style agent: streaming loop, permission-governed tools, context management, sandboxing.
The architect's handbook for resilient AI systems
The patterns, budgets, and bulkheads that keep an AI system running when the model, the vendor, or the load turns against you.
Systematic debugging: A forensic engineering guide
Stop guessing. Start investigating. The four-phase forensic process for bugs that refuse to die.
Advanced query rewriting for RAG
HyDE, multi-query fan-out, decomposition, step-back. The rewriting layer that rescues vague user queries.
Vector databases for RAG
Indexing, HNSW vs IVF, hybrid wiring, scaling cost, migration. The vector DB reference you pin.
Data preprocessing for RAG pipelines
Clean, normalize, dedup, gate. The preprocessing layer that decides RAG quality before retrieval runs.
Filtering and structured LLM output
JSON schemas, validators, repair loops, grounding checks. Structured output that holds under load.
Summarization strategies for production RAG
Extractive, abstractive, hierarchical, map-reduce. The summarization strategies that survive long context and tight budgets.
Text data cleaning for RAG pipelines
Unicode, tokenization, encoding, language, PII. The text cleaning rules that keep RAG retrieval honest.
Secure shell execution for coding agents
Sandbox, timeout, allowlist, audit. The shell layer that lets a coding agent run commands without burning the host.
Building a web UI for your coding agent
Streaming, tool events, state visualization, error recovery. The UX patterns that make coding agents usable.
Advanced document processing for RAG
Layout-preserving PDFs, AST-aware code, table extraction, multi-modal. The parsing layer RAG needs for real docs.
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