ParallelCS Start here

The map

One graph. Every concept. A clear path.

Every concept is a node. Every edge is a prerequisite. Tracks run left to right, week by week, follow an edge backward and you find exactly what to master first. No guessing what to learn next.

Concept map

Mapped end to end.

Curved lines connect a concept to its prerequisites. The visual is decorative; the full, screen-reader-friendly version follows as a table.

W1W2W3W4W5W6W7W8W9W10W11W12 Agentic Systems & Harness EngineeringAI Infrastructure & InferenceApplied ML & Model EngineeringProduction AI ProductsFrontier SystemsMultimodal AI & Embodied World ModelingAI Safety, Alignment & InterpretabilityLand the Elite AI Role Foundations of Harness Engineering & Loop Crafting, Week 1 Tool Use, Pre-Compiled Toolmaking & Function Calling, Week 2 Model Context Protocol (MCP) & Context Engineering, Week 3 Planning, Test-Time Compute & Deliberate Reasoning Scaling, Week 4 Context Hubs, JIT Context Delivery & Semantic Routers, Week 5 Sandboxed Execution, Stateful APIs & Runtime Security, Week 6 Multi-Agent Orchestration, A2A Protocols & Verification Loops, Week 8 Agent Verification Loops & HITL Guardrails, Week 10 Agent Security & Prompt Injection, Week 11 Transformer Internals for Serving, Week 1 GPU Architecture & the Memory Wall, Week 2 FlashAttention & Subquadratic Sparse Attention, Week 3 KV-Cache Management, RadixAttention & Multi-Head Latent Attention, Week 4 Continuous Batching & Throughput Scheduling, Week 5 Quantization & Model Compression, Week 7 Speculative Decoding & Latency Optimization, Week 8 Production Serving, PD Disaggregation & Autoscaling, Week 10 Neural Networks & Backpropagation from Scratch, Week 1 Deep Learning Foundations, Week 2 Transformers, Attention & Pretraining, Week 3 Pre-Training Data, Synthetic Mid-Training & Scaling Laws, Week 4 Supervised Fine-Tuning, Week 6 Parameter-Efficient Fine-Tuning: LoRA & QLoRA, Week 7 Preference Optimization & RL from Verifiable Rewards (RLVR), Week 9 Knowledge Distillation & Model Compression, Week 10 Rigorous Model Evaluation, Week 11 LLM Application Foundations, Week 1 Embeddings & Vector Search, Week 2 Production Hybrid RAG & Context Engineering, Week 4 Evaluation-Driven Development (EDD) & Synthetic Data Harnesses, Week 5 AI Observability & Tracing, Week 7 AI Security & Red-Teaming, Week 9 LLMOps, Cost Governance & Geopolitical Fallbacks, Week 10 Shipping & Operating AI Products, Week 12 Distributed Systems Foundations, Week 1 Consensus & Coordination, Week 3 Distributed Training & Parallelism, Week 4 GPU Cluster Scheduling, Week 6 Real-Time & Streaming AI Systems, Week 7 Vector Databases at Scale, Week 9 Fault Tolerance & Resilient Operations, Week 11 Cluster Observability & Capacity Planning, Week 12 Vision Encoders & Image Representation, Week 1 Vision-Language Model Architecture, Week 2 Diffusion, Flow-Matching & Generative Video Foundations, Week 3 Latent Diffusion & Conditioning, Week 5 Video & Temporal Generative Models, Week 6 Any-to-Any Models & World Action Models, Week 8 Multimodal Training & Instruction Tuning, Week 9 Multimodal Inference & Evaluation, Week 11 The Alignment Problem & Safety Foundations, Week 1 RLHF & Preference-Based Alignment, Week 2 Constitutional AI & Scalable Oversight, Week 4 Mechanistic Interpretability Foundations, Week 5 Interpretability in Practice: SAEs, NLAs & Activation Patching, Week 7 Safety Evaluations & Dangerous-Capability Testing, Week 8 Adversarial Robustness & Red-Teaming Depth, Week 9 AI Governance: Model Cards, the EU AI Act & NIST AI RMF, Week 10 Research Methodology: Reading & Reproducing Papers, Week 11 AI / ML System-Design Interviews, Week 1 Running Experiments, Ablations & Tracking, Week 2 Building a Portfolio That Gets Noticed, Week 4 Technical Writing & Communication, Week 6 Open-Source Contribution & Visibility, Week 8 The Elite AI Hiring Pipeline, Week 9 Compensation & Negotiation, Week 11 Sovereign AI, MLX & Local GPU Clustering, Week 11 Hybrid Architectures: SSM-Transformer Hybrids & Attention Alternatives, Week 5 Software 3.0: Verification Harnesses & Self-Improvement, Week 9 Context Hubs & JIT Semantic Routing, Week 3
Agentic Systems & Harness EngineeringAI Infrastructure & InferenceApplied ML & Model EngineeringProduction AI ProductsFrontier SystemsMultimodal AI & Embodied World ModelingAI Safety, Alignment & InterpretabilityLand the Elite AI Role

Every concept, in order

The graph as a table.

A complete, accessible listing of every node, the classic CS subject it bridges to, and its prerequisite edges.

70 concepts with their week, track, subject bridge and prerequisites
WeekTrackConceptBridges toPrerequisites
1 Agentic Systems & Harness Engineering Foundations of Harness Engineering & Loop Crafting Operating Systems — processes, scheduling, and the run loop None
1 AI Infrastructure & Inference Transformer Internals for Serving Computer Architecture — instruction-level parallelism and the memory wall None
1 AI Safety, Alignment & Interpretability The Alignment Problem & Safety Foundations Theory of Computation — specification, correctness, and the limits of formal goals None
1 Applied ML & Model Engineering Neural Networks & Backpropagation from Scratch Calculus & Linear Algebra — gradients, the chain rule, and vector spaces None
1 Frontier Systems Distributed Systems Foundations Distributed Systems — failure models, latency, and the CAP theorem None
1 Land the Elite AI Role AI / ML System-Design Interviews , None
1 Multimodal AI & Embodied World Modeling Vision Encoders & Image Representation Computer Vision — image representation, feature extraction, and convolution None
1 Production AI Products LLM Application Foundations Software Engineering — application architecture and API design None
2 Agentic Systems & Harness Engineering Tool Use, Pre-Compiled Toolmaking & Function Calling Software Engineering — interface design and API contracts Foundations of Harness Engineering & Loop Crafting
2 AI Infrastructure & Inference GPU Architecture & the Memory Wall Computer Architecture — parallelism, memory hierarchy, and the roofline model Transformer Internals for Serving
2 AI Safety, Alignment & Interpretability RLHF & Preference-Based Alignment Machine Learning — reinforcement learning and optimization under feedback The Alignment Problem & Safety Foundations
2 Applied ML & Model Engineering Deep Learning Foundations Machine Learning — optimization, generalization, and the bias-variance tradeoff Neural Networks & Backpropagation from Scratch
2 Land the Elite AI Role Running Experiments, Ablations & Tracking , AI / ML System-Design Interviews
2 Multimodal AI & Embodied World Modeling Vision-Language Model Architecture Machine Learning — representation learning and modality fusion Vision Encoders & Image Representation
2 Production AI Products Embeddings & Vector Search Databases — indexing, search structures, and query optimization LLM Application Foundations
3 Agentic Systems & Harness Engineering Model Context Protocol (MCP) & Context Engineering Computer Networks — protocols, client-server architecture, and RPC Tool Use, Pre-Compiled Toolmaking & Function Calling
3 AI Infrastructure & Inference FlashAttention & Subquadratic Sparse Attention Operating Systems — I/O scheduling and memory-bound versus compute-bound work GPU Architecture & the Memory Wall
3 Applied ML & Model Engineering Transformers, Attention & Pretraining Machine Learning — sequence modeling and representation learning Deep Learning Foundations
3 Frontier Systems Consensus & Coordination Distributed Systems — consensus, replication, and fault tolerance Distributed Systems Foundations
3 Multimodal AI & Embodied World Modeling Diffusion, Flow-Matching & Generative Video Foundations Probability & Statistics — stochastic processes and generative modeling None
3 Production AI Products Context Hubs & JIT Semantic Routing Databases — API/schema versioning, semantic routing, and transactional isolation Embeddings & Vector Search
4 Agentic Systems & Harness Engineering Planning, Test-Time Compute & Deliberate Reasoning Scaling Artificial Intelligence — search, planning, and state-space reasoning Tool Use, Pre-Compiled Toolmaking & Function Calling
4 AI Infrastructure & Inference KV-Cache Management, RadixAttention & Multi-Head Latent Attention Operating Systems — virtual memory, paging, and fragmentation FlashAttention & Subquadratic Sparse Attention
4 AI Safety, Alignment & Interpretability Constitutional AI & Scalable Oversight Distributed Systems — delegation, trust, and verification of work you cannot fully check RLHF & Preference-Based Alignment
4 Applied ML & Model Engineering Pre-Training Data, Synthetic Mid-Training & Scaling Laws Databases — data cleaning, deduplication, and ETL pipelines Transformers, Attention & Pretraining
4 Frontier Systems Distributed Training & Parallelism Parallel Computing — collective communication and parallel decomposition Consensus & Coordination
4 Land the Elite AI Role Building a Portfolio That Gets Noticed , Running Experiments, Ablations & Tracking
4 Production AI Products Production Hybrid RAG & Context Engineering Databases — query processing, joins, and information retrieval Embeddings & Vector Search
5 Agentic Systems & Harness Engineering Context Hubs, JIT Context Delivery & Semantic Routers Operating Systems — memory hierarchy, paging, and caching Planning, Test-Time Compute & Deliberate Reasoning Scaling
5 AI Infrastructure & Inference Continuous Batching & Throughput Scheduling Operating Systems — CPU scheduling, throughput versus latency tradeoffs KV-Cache Management, RadixAttention & Multi-Head Latent Attention
5 AI Safety, Alignment & Interpretability Mechanistic Interpretability Foundations Compilers — reverse engineering, intermediate representations, and program analysis The Alignment Problem & Safety Foundations
5 Applied ML & Model Engineering Hybrid Architectures: SSM-Transformer Hybrids & Attention Alternatives Computer Architecture — specialized processors and hardware-agnostic compilation Pre-Training Data, Synthetic Mid-Training & Scaling Laws
5 Multimodal AI & Embodied World Modeling Latent Diffusion & Conditioning Computer Vision — image synthesis and conditional generation Diffusion, Flow-Matching & Generative Video Foundations, Vision-Language Model Architecture
5 Production AI Products Evaluation-Driven Development (EDD) & Synthetic Data Harnesses Software Engineering — automated testing and continuous integration Production Hybrid RAG & Context Engineering
6 Agentic Systems & Harness Engineering Sandboxed Execution, Stateful APIs & Runtime Security Operating Systems — virtualization, namespaces, and process isolation Context Hubs, JIT Context Delivery & Semantic Routers
6 Applied ML & Model Engineering Supervised Fine-Tuning Machine Learning — transfer learning and supervised training Pre-Training Data, Synthetic Mid-Training & Scaling Laws
6 Frontier Systems GPU Cluster Scheduling Operating Systems — scheduling, resource allocation, and fairness Distributed Training & Parallelism
6 Land the Elite AI Role Technical Writing & Communication , Building a Portfolio That Gets Noticed
6 Multimodal AI & Embodied World Modeling Video & Temporal Generative Models Signal Processing — temporal signals, sampling, and reconstruction Latent Diffusion & Conditioning
7 AI Infrastructure & Inference Quantization & Model Compression Computer Architecture — number representation and fixed-point arithmetic Continuous Batching & Throughput Scheduling
7 AI Safety, Alignment & Interpretability Interpretability in Practice: SAEs, NLAs & Activation Patching Software Engineering — instrumentation, debugging, and observability of complex systems Mechanistic Interpretability Foundations
7 Applied ML & Model Engineering Parameter-Efficient Fine-Tuning: LoRA & QLoRA Linear Algebra — matrix rank, decomposition, and low-rank approximation Supervised Fine-Tuning
7 Frontier Systems Real-Time & Streaming AI Systems Distributed Systems — event-driven architecture and stream processing GPU Cluster Scheduling
7 Production AI Products AI Observability & Tracing Software Engineering — monitoring, logging, and distributed tracing Evaluation-Driven Development (EDD) & Synthetic Data Harnesses
8 Agentic Systems & Harness Engineering Multi-Agent Orchestration, A2A Protocols & Verification Loops Distributed Systems — coordination, message passing, and consensus Sandboxed Execution, Stateful APIs & Runtime Security
8 AI Infrastructure & Inference Speculative Decoding & Latency Optimization Computer Architecture — speculative and out-of-order execution Quantization & Model Compression
8 AI Safety, Alignment & Interpretability Safety Evaluations & Dangerous-Capability Testing Software Engineering — test design, coverage, and validation under uncertainty Constitutional AI & Scalable Oversight
8 Land the Elite AI Role Open-Source Contribution & Visibility , Technical Writing & Communication
8 Multimodal AI & Embodied World Modeling Any-to-Any Models & World Action Models Machine Learning — sequence modeling and unified representations Video & Temporal Generative Models
9 Agentic Systems & Harness Engineering Software 3.0: Verification Harnesses & Self-Improvement Compilers — program optimization, intermediate representations, and iterative refinement loops Planning, Test-Time Compute & Deliberate Reasoning Scaling
9 AI Safety, Alignment & Interpretability Adversarial Robustness & Red-Teaming Depth Information Security — adversarial thinking, threat modeling, and penetration testing Safety Evaluations & Dangerous-Capability Testing
9 Applied ML & Model Engineering Preference Optimization & RL from Verifiable Rewards (RLVR) Machine Learning — reinforcement learning and policy optimization Parameter-Efficient Fine-Tuning: LoRA & QLoRA
9 Frontier Systems Vector Databases at Scale Databases — indexing, sharding, and query optimization Real-Time & Streaming AI Systems
9 Land the Elite AI Role The Elite AI Hiring Pipeline , Open-Source Contribution & Visibility
9 Multimodal AI & Embodied World Modeling Multimodal Training & Instruction Tuning Machine Learning — transfer learning and supervised fine-tuning Any-to-Any Models & World Action Models
9 Production AI Products AI Security & Red-Teaming Information Security — threat modeling, penetration testing, and OWASP AI Observability & Tracing
10 Agentic Systems & Harness Engineering Agent Verification Loops & HITL Guardrails Software Engineering — testing, regression suites, and observability Multi-Agent Orchestration, A2A Protocols & Verification Loops
10 AI Infrastructure & Inference Production Serving, PD Disaggregation & Autoscaling Distributed Systems — load balancing, replication, and capacity planning Speculative Decoding & Latency Optimization
10 AI Safety, Alignment & Interpretability AI Governance: Model Cards, the EU AI Act & NIST AI RMF Information Security — policy, compliance, and audit-ready documentation Safety Evaluations & Dangerous-Capability Testing
10 Applied ML & Model Engineering Knowledge Distillation & Model Compression Machine Learning — model compression and the teacher-student paradigm Preference Optimization & RL from Verifiable Rewards (RLVR)
10 Production AI Products LLMOps, Cost Governance & Geopolitical Fallbacks Software Engineering — release management, versioning, and CI/CD AI Security & Red-Teaming
11 Agentic Systems & Harness Engineering Agent Security & Prompt Injection Information Security — threat modeling and least privilege Agent Verification Loops & HITL Guardrails
11 AI Infrastructure & Inference Sovereign AI, MLX & Local GPU Clustering Computer Architecture — specialized processors and hardware-agnostic compilation Production Serving, PD Disaggregation & Autoscaling
11 AI Safety, Alignment & Interpretability Research Methodology: Reading & Reproducing Papers Software Engineering — the scientific method, controlled experiments, and reproducibility Interpretability in Practice: SAEs, NLAs & Activation Patching
11 Applied ML & Model Engineering Rigorous Model Evaluation Statistics — sampling, confidence intervals, and experimental design Knowledge Distillation & Model Compression
11 Frontier Systems Fault Tolerance & Resilient Operations Distributed Systems — fault tolerance, checkpointing, and recovery Vector Databases at Scale
11 Land the Elite AI Role Compensation & Negotiation , The Elite AI Hiring Pipeline
11 Multimodal AI & Embodied World Modeling Multimodal Inference & Evaluation Machine Learning — model evaluation and benchmark design Multimodal Training & Instruction Tuning
12 Frontier Systems Cluster Observability & Capacity Planning Distributed Systems — monitoring, capacity planning, and performance analysis Fault Tolerance & Resilient Operations
12 Production AI Products Shipping & Operating AI Products Software Engineering — deployment, resilience, and product engineering LLMOps, Cost Governance & Geopolitical Fallbacks