The Curriculum
Every chapter, ordered from foundations to advanced. Prerequisites guide the path — master the basics and the harder patterns unlock.
Data Structures
Arrays & Hashing
The foundation: indexing, hash maps, and frequency counting.
Strings
String manipulation, parsing, and encoding.
Stacks & Queues
LIFO/FIFO structures, monotonic stacks, and deques.
Linked Lists
Pointer manipulation, reversal, and cycle detection.
Trees & BSTs
Binary tree traversal, recursion on trees, and search trees.
Traverse binary trees recursively and level-by-level.
Prereqs: Traversal & Reversal
Heaps & Priority Queues
Top-K, streaming medians, and scheduling with heaps.
Use heaps for top-K, k-way merges, and streaming order statistics.
Prereqs: Tree Traversals (DFS/BFS)
Tries
Prefix trees for fast string lookups and autocomplete.
Graphs
Graph representation, traversal, and connectivity.
Model graphs as adjacency lists/matrices and traverse them.
Prereqs: Tree Traversals (DFS/BFS)
Track connectivity with union by rank and path compression.
Prereqs: Graph Representation & Traversal
Algorithms
Two Pointers & Sliding Window
Linear-scan patterns for pairs, subarrays, and substrings.
Converge pointers to solve pair, palindrome, and partition problems.
Prereqs: Hashing & Frequency Maps
Maintain a moving window to optimize subarray/substring scans.
Prereqs: Two Pointers
Binary Search
Searching sorted data and binary searching the answer space.
Halve the search space on sorted (and rotated) arrays.
Prereqs: Hashing & Frequency Maps
Binary search a monotonic feasibility function over a value range.
Prereqs: Binary Search on Arrays
Recursion & Backtracking
Recursive enumeration of subsets, permutations, and combinations.
Greedy
Locally optimal choices that yield a global optimum.
Dynamic Programming
Overlapping subproblems, memoization, and tabulation.
Define a state and recurrence over a single dimension.
Prereqs: Recursion Fundamentals
Grid and two-sequence DP (edit distance, LCS, unique paths).
Prereqs: 1-D Dynamic Programming
Choose items under a capacity/target constraint.
Prereqs: 1-D Dynamic Programming
Graph Algorithms
BFS/DFS patterns, topological sort, and shortest paths.
Flood fill, connected components, and shortest unweighted paths.
Prereqs: Graph Representation & Traversal
Order a DAG and detect cycles (course scheduling).
Prereqs: BFS & DFS Patterns
Intervals
Merging, scheduling, and sweeping over intervals.
Bit Manipulation & Math
Bitwise tricks, number theory, and math-heavy problems.
System Design
System Design Fundamentals
Scalability, latency vs throughput, load balancing, and caching.
Reason about latency vs throughput and scale up vs scale out.
Distribute traffic with load balancers, reverse proxies, and health checks.
Prereqs: Scalability & Performance
Data Storage & Scaling
Choosing data stores, sharding, replication, and indexing.
Match the data store and schema to access patterns.
Prereqs: Scalability & Performance
Shard for scale and replicate for availability and reads.
Prereqs: SQL vs NoSQL & Data Modeling
Distributed Systems
CAP & consistency, messaging, idempotency, and rate limiting.
Trade consistency, availability, and partition tolerance.
Prereqs: Partitioning & Replication
Decouple services with queues, pub/sub, and streams.
Prereqs: Scalability & Performance
Cloud System Design
Cloud building blocks, autoscaling, serverless, reliability, and cost.
Compose compute, object storage, managed databases, and networking.
Prereqs: Scalability & Performance
Scale elastically and survive zone/region failure in the cloud.
Prereqs: Load Balancing & Proxies, Cloud Building Blocks
Build event-driven systems with functions, managed queues, and streams.
Prereqs: Cloud Building Blocks, Message Queues & Async Processing
AI & FDE
LLM Foundations
Tokens, context, prompting, embeddings, and model selection.
Design prompts, manage context windows, and choose decoding settings.
Choose embedding models and similarity metrics for retrieval.
Prereqs: Prompting & Context
RAG & Retrieval
Chunking, vector search, hybrid retrieval, re-ranking, and citations.
Agents & Tools
Tool calling, orchestration, memory, multi-agent, and failure modes.
ML Systems
Training vs inference, feature stores, online/offline paths, and drift.
Production AI
Latency, cost, caching, guardrails, observability, and evals in prod.
Offline/online evals, golden sets, LLM-as-judge, and regression gates.
Prereqs: RAG Pipeline Design
Prompt injection, PII, content filters, and policy enforcement.
Prereqs: Tool Calling
FDE Delivery
Customer discovery, scoping, integration, rollout, and stakeholder delivery.
Frame customer problems, MoSCoW scope, and success metrics.
Connectors, ACLs, on-prem/cloud deploy, and rollout plans.
Prereqs: Discovery & Scoping
Agent Engineering
AI Developer Workstation
Cursor, Claude Code, Codex, Copilot — surfaces, modes, and the daily agent loop.
Context Engineering
AGENTS.md, CLAUDE.md, rules, instructions, and token budgets.
Superstar Practices
Spec-driven development, TDD with agents, parallel worktrees, model routing, debugging, and agents in CI.
Agent Skills
SKILL.md, progressive disclosure, triggering, evaluation, and trust.
Plugins & Subagents
Commands, subagents, plugins, marketplaces, and portability.
OpenClaw
Self-hosted agent gateway, channels, ClawHub, bundles, and safety.
Model Context Protocol
Primitives, transports, client config, context cost, and auth.
LangGraph & Workflows
Workflow vs agent, state, checkpoints, interrupts, and create_agent.
Build Your Own Agents
Claude Agent SDK, OpenAI Agents SDK, Cursor SDK, browser/computer use, A2A, and operating agents.