90-Day LLM Engineer Roadmap
Sprint from strong software engineer to production LLM engineer in 90 days.
Overview
| Week | Theme | Primary Output |
|---|---|---|
| 1-2 | Vocabulary and mental models | Personal glossary, model card fluency |
| 3-4 | How transformers and LLMs work | Architecture diagram, KV cache explanation |
| 5-6 | Model cards, catalogs, selection | Model selection matrix for 5 use cases |
| 7-8 | Local inference and hardware | Benchmark report for 3 local models |
| 9-10 | Production serving | vLLM deployment + throughput benchmark |
| 11-12 | LLM gateway | Working gateway with routing + cost tracking |
| 13-14 | RAG systems | Working RAG pipeline with eval |
| 15-16 | Agents and tool calling | Working agent with observability |
| 17-18 | Evaluation | Eval harness with model comparison |
| 19-20 | Security, fine-tuning | Security checklist + LoRA lab |
| 21-22 | Startup playbook | MVP spec + cost model |
| 23-24 | Capstone | Full platform + demo narrative |
Week 1 — LLM Vocabulary: Tokens, Context, Models
Goal: Be able to read any model card and understand every term.
Read:
- 01-llm-vocabulary/00-core-mental-model.md
- 01-llm-vocabulary/01-tokenization-and-context.md
- 01-llm-vocabulary/02-parameters-weights-and-checkpoints.md
- 01-llm-vocabulary/03-inference-parameters.md
Lab: Pick any two models from models.dev. List every term you do not understand. Look up each one in the vocabulary guide.
Artifact: Personal glossary with 40+ terms defined in your own words.
Week 2 — Vocabulary: Serving, Pricing, Local Models
Goal: Understand pricing, hardware, and serving terminology.
Read:
- 01-llm-vocabulary/05-serving-terms.md
- 01-llm-vocabulary/06-local-model-terms.md
- 01-llm-vocabulary/07-evaluation-terms.md
- 01-llm-vocabulary/08-business-and-pricing-terms.md
- 01-llm-vocabulary/09-complete-glossary.md
Lab: Read the OpenRouter pricing page. Understand every column and every term.
Artifact: Annotated pricing-page screenshot with every term explained.
Week 3 — Transformer Foundations: Big Picture to Attention
Goal: Explain tokenization → embeddings → attention → generation.
Read:
- 02-transformer-foundations/00-transformer-big-picture.md
- 02-transformer-foundations/01-token-embeddings.md
- 02-transformer-foundations/02-attention-and-self-attention.md
- 02-transformer-foundations/05-autoregressive-generation.md
Lab: Run a tokenizer (tiktoken or HuggingFace tokenizer). Tokenize 10 different prompts. Observe token counts. Estimate costs.
Artifact: Tokenization study with 10 examples + cost calculations.
Week 4 — Transformer Foundations: KV Cache, Prefill, MoE
Goal: Understand why LLMs use memory and why batching matters.
Read:
- 02-transformer-foundations/06-kv-cache.md
- 02-transformer-foundations/07-prefill-vs-decode.md
- 02-transformer-foundations/08-moe-and-dense-models.md
- 02-transformer-foundations/09-reasoning-models.md
Lab: Using the vLLM docs or any local model server, observe memory usage at different context lengths.
Artifact: Memory vs context length graph or table.
Week 5 — Model Cards and System Cards
Goal: Extract every relevant field from a model card in under 5 minutes.
Read:
- 03-model-cards-and-system-cards/00-how-to-read-model-cards.md
- 03-model-cards-and-system-cards/01-how-to-read-system-cards.md
- 03-model-cards-and-system-cards/06-model-card-checklist.md
Lab: labs/lab-00-model-card-reading/ — Read and annotate three model cards.
Artifact: Three completed model card worksheets.
Week 6 — Model Catalogs and Model Selection
Goal: Use models.dev fluently. Build a model selection matrix.
Read:
- 04-model-catalogs-and-trend-reading/00-how-to-use-models-dev.md
- 04-model-catalogs-and-trend-reading/01-column-by-column-guide.md
- 05-model-selection/00-model-selection-framework.md
- 05-model-selection/09-cost-quality-latency-framework.md
Lab: labs/lab-01-models-dev-explorer/
Artifact: Model selection matrix for 5 real use cases.
Week 7 — Local Inference: Hardware and GGUF
Goal: Run a local model. Understand hardware requirements.
Read:
- 06-local-inference/00-local-inference-overview.md
- 06-local-inference/01-hardware-literacy.md
- 06-local-inference/02-ram-vram-unified-memory.md
- 06-local-inference/03-gguf-and-llama-cpp.md
Lab: labs/lab-02-local-llama-cpp/
Artifact: Hardware profile + llama.cpp benchmark report.
Week 8 — Local Inference: Quantization, Ollama, MTP
Goal: Compare quantization levels. Run Ollama. Understand MTP.
Read:
- 06-local-inference/04-ollama-and-lm-studio.md
- 06-local-inference/06-quantization-guide.md
- 06-local-inference/07-mtp-and-speculative-decoding.md
Labs: labs/lab-03-ollama-and-openai-compatible-api/ + labs/lab-05-quantization-benchmark/
Artifact: Quantization comparison benchmark.
Week 9 — Production Serving: vLLM Core
Goal: Deploy vLLM. Understand continuous batching, PagedAttention, streaming.
Read:
- 07-production-serving/00-serving-architecture.md
- 07-production-serving/01-vllm.md
- 07-production-serving/03-continuous-batching.md
- 07-production-serving/04-pagedattention.md
Lab: labs/lab-04-vllm-serving/
Artifact: vLLM benchmark: throughput vs batch size, latency vs context length.
Week 10 — Production Serving: Caching, Routing, Observability
Read:
- 07-production-serving/05-prefix-and-prompt-caching.md
- 07-production-serving/07-routing-and-fallbacks.md
- 07-production-serving/08-observability.md
- 07-production-serving/09-cost-controls.md
Lab: Add prefix caching to vLLM setup. Observe hit rate and latency improvement.
Artifact: Cache hit rate study.
Week 11 — LLM Gateway: Architecture and Providers
Goal: Understand what an LLM gateway does and why.
Read:
- 08-llm-gateways/00-what-is-an-llm-gateway.md
- 08-llm-gateways/01-openrouter-style-architecture.md
- 08-llm-gateways/02-litellm-style-proxy.md
- 08-llm-gateways/03-provider-adapters.md
Lab: labs/lab-07-model-gateway/ — Part 1: provider adapter and model registry.
Artifact: Working provider adapter with tests.
Week 12 — LLM Gateway: Routing, Metering, Streaming
Read:
- 08-llm-gateways/05-routing-engine.md
- 08-llm-gateways/06-usage-metering.md
- 08-llm-gateways/07-streaming-proxy.md
Lab: labs/lab-07-model-gateway/ — Part 2: routing + streaming + cost tracking.
Artifact: Full gateway with routing config, cost dashboard, and streaming test.
Week 13 — RAG: Ingestion through Retrieval
Read:
- 09-rag/00-rag-overview.md
- 09-rag/01-document-ingestion.md
- 09-rag/02-chunking.md
- 09-rag/03-embeddings.md
- 09-rag/04-vector-databases.md
Lab: labs/lab-08-rag-system/ — Part 1: ingestion, chunking, embedding, retrieval.
Week 14 — RAG: Reranking, Context Packing, Citations, Eval
Read:
- 09-rag/05-hybrid-search.md
- 09-rag/06-reranking.md
- 09-rag/08-citations-and-grounding.md
- 09-rag/09-rag-evaluation.md
Lab: labs/lab-08-rag-system/ — Part 2: reranking, citations, eval.
Artifact: RAG eval report with faithfulness and relevance scores.
Week 15 — Agents and Tool Calling
Read:
- 10-agents-and-tools/00-agent-overview.md
- 10-agents-and-tools/01-tool-calling.md
- 10-agents-and-tools/02-json-schema-and-structured-output.md
- 10-agents-and-tools/05-sandbox-and-approval.md
Lab: labs/lab-09-agent-with-tools/
Artifact: Working agent with 3+ tools, approval gates, and traces.
Week 16 — Agents: Memory, Browser, Code Execution
Read:
- 10-agents-and-tools/04-agent-memory.md
- 10-agents-and-tools/06-code-editing-agents.md
- 10-agents-and-tools/08-agent-observability.md
Week 17 — Evaluation Harness
Read:
- 12-evaluation/00-evaluation-overview.md
- 12-evaluation/02-llm-as-judge.md
- 12-evaluation/08-model-selection-eval-harness.md
Lab: labs/lab-11-eval-harness/
Artifact: Eval report comparing 3 models on your use case.
Week 18 — Observability and Production Operations
Read:
Lab: labs/lab-12-production-observability/
Week 19 — Security, Privacy, Governance
Read:
- 14-security-privacy-and-governance/00-ai-security-overview.md
- 14-security-privacy-and-governance/01-prompt-injection.md
- 14-security-privacy-and-governance/04-tenant-isolation.md
Artifact: Security checklist for your gateway project.
Week 20 — Fine-Tuning with LoRA
Read:
- 13-fine-tuning-and-adaptation/00-when-to-finetune.md
- 13-fine-tuning-and-adaptation/02-lora-and-qlora.md
Lab: Fine-tune a small model with QLoRA. Evaluate before/after.
Week 21-22 — Startup Playbook
Read:
- 15-startup-playbook/00-startup-opportunity-map.md
- 15-startup-playbook/03-ai-native-product-design.md
- 15-startup-playbook/05-cost-model-and-unit-economics.md
Artifact: MVP spec, cost model, and ICP statement for your startup idea.
Week 23-24 — Capstone
Lab: labs/lab-13-capstone-platform/
Deliver:
- LLM gateway
- RAG demo
- Agent demo
- Eval report
- Architecture diagrams
- Demo narrative
Quick Reference
| If you want to... | Go to... |
|---|---|
| Understand a term | 01-llm-vocabulary/ |
| Read a model card | 03-model-cards-and-system-cards/ |
| Choose a model | 05-model-selection/ |
| Run a local model | 06-local-inference/ |
| Deploy vLLM | 07-production-serving/01-vllm.md |
| Build a gateway | 08-llm-gateways/ |
| Build RAG | 09-rag/ |
| Build an agent | 10-agents-and-tools/ |
| Run evals | 12-evaluation/ |
| Start a company | 15-startup-playbook/ |