Notes
Every folder below is one of two things: a book — a
README.mdtable of contents whose chapters wikilink out to concept notes instead of duplicating them — or an applied/reference folder (Projects) that the books link into. Single-tool/concept reference notes (e.g. Mimir, GitOps, Envoy) live in areference/subfolder inside the one book they belong to most, rather than in a separate staging folder. Start at a book’sREADME.md; follow wikilinks from there rather than browsing files directly.
MAANG interview-prep core
- Data Structures & Algorithms — Python foundations through advanced DS/algorithms and MAANG interview mastery
- Low-Level Design — OOP, SOLID, UML, and design patterns for LLD interviews
- Object-Oriented Programming — paradigm foundations through OOP at system scale
- System Design — Principal/Staff-level system design reference collection
- Operating Systems — processes, memory, file systems, and Linux internals at interview depth
- Computer Networks — Ethernet through QUIC, DNS, HTTP, and cloud networking
- Database Management Systems — relational foundations through distributed databases and NoSQL
- Aptitude — quantitative, logical, and verbal prep for aptitude-gated pipelines
Observability & SRE
- Observability Engineering — the full discipline, foundations through AI-driven operations
- Prometheus — monitoring foundations through PromQL and production operation
- Grafana Cloud — platform foundations through Mimir/Loki/Tempo/Pyroscope
- Site Reliability Engineering — the 184-chapter SRE curriculum, foundations through Staff/Principal interview prep
Platform & cloud-native engineering
- Kubernetes — cloud-native foundations through CKAD/CKA/CKS depth
- Kubernetes Platform Engineering — multi-tenancy, platform automation, Helm, Crossplane
- Infrastructure Platform Engineering — IaC, Terraform/OpenTofu, cloud platform design
- Internal Developer Platforms — IDP fundamentals, Backstage, golden paths
- Platform Engineering Fundamentals — platform-as-a-product thinking, DORA/SPACE metrics
- CI/CD Platform Engineering — pipeline foundations through GitHub Actions, Argo Workflows, Tekton
- Patterns — reusable engineering patterns across OOD, distributed systems, and agentic AI
AI & data systems
- AI & LLM Foundations — the pre-agentic substrate through turning a raw model API into a dependable component
- Agentic AI Engineering — agent cognition, memory, planning, tools, retrieval, and context engineering
- Building & Evaluating Agents — single- and multi-agent systems, evaluation, and the framework landscape
- Production Agent Systems — infrastructure, observability, reliability/security, performance/cost, and platform engineering
- AI Architecture & System Design — the cross-cutting pattern catalog and enterprise system-design case studies
- Agentic AI: Projects & Engineering Mastery — hands-on builds, Principal/Staff-level judgment, and reference appendices
- Data Engineering — modeling, storage, ingestion, Spark/Flink, pipeline observability
Personal practice
- Productivity for Knowledge Workers — self-management, PKM, task systems, digital productivity
- Philosophy — cognitive biases, mental models, stoic practice
Applied & reference
- Projects — real, running systems documented end to end (SignalForge, the ShipSolid platform)
Metadata
| Author | Amit Singh |
| Scope | notes |
Local graph
Related notes
Projects
Applied documentation for real, running systems — SignalForge (an OTel validation lab) and the ShipSolid observability platform — as opposed to the cross-linked reference books in the rest of this wiki.
OpenAI Agents SDK
Python SDK for OpenAI's Agents framework — the concrete API surface: Agent/Runner construction, the function_tool and handoff() call shapes, Session-backed state, guardrail decorators, and built-in tracing.
What is LangGraph
LangChain's graph-based orchestration library — agents as a StateGraph of nodes and edges, with durable checkpointing and human-in-the-loop interrupts as native graph mechanics rather than bolted-on features.
LlamaIndex Workflows
The API surface behind LlamaIndex's event-driven orchestration layer — Workflow/Step/Event class mechanics, Context state and fan-out/fan-in, and how a Workflow sits directly on top of the existing Index/QueryEngine retrieval stack.