Skip to content

AI Engineering — technical knowledge base

A curated, scholarly knowledge base for practitioners and power users who want to understand the research, architecture, and tooling behind large language models (LLMs), agentic AI, and modern AI systems.

Who this is for: Engineers, technical PMs, researchers, and advanced Cursor users who want primary sources — not summaries of summaries. If you're looking for a gentler introduction, start with onboarding/.

Topic map

Article What it covers Sources
Context engineering The discipline of designing what an LLM sees at inference time — beyond prompt engineering to the full information pipeline ~12
LLM foundations Transformer architecture, training paradigms, scaling laws, and the key papers that define the field ~12
Agentic AI Agent architectures, tool use, planning, memory, multi-agent systems, and the research frontier ~12
Full-stack LLM development Fine-tuning, inference serving, evaluation, deployment, and production engineering ~10
AI services and APIs Commercial and open-source model APIs, comparison frameworks, security, and governance ~8

Master bibliography: SOURCE_INDEX.md — every URL across all articles in one place with metadata.

How to use this section

If you're building with LLMs: Start with context engineering and full-stack LLM — they cover the decisions you'll face daily.

If you're evaluating AI strategy: Read AI services and APIs for the commercial landscape, then LLM foundations for the "why" behind model capabilities.

If you're researching agents: Agentic AI collects the foundational papers and emerging architectures.

If you want the raw reading list: SOURCE_INDEX.md has every source with domain, category, and year.

Source standards

Every source in this section meets at least one of these criteria:

  • Primary research — published on arXiv, in peer-reviewed venues (NeurIPS, ICML, ACL, TMLR), or as official technical reports
  • Official vendor documentation — Anthropic, OpenAI, Google, Meta, Hugging Face
  • Established practitioners — Lilian Weng, Chip Huyen, Andrej Karpathy, Simon Willison, Jay Alammar
  • Recognized standards bodies — NIST, OWASP, EU AI Act

Blog posts and opinion pieces are included only when they offer unique practitioner insight not available elsewhere. They are marked as such.

Area Where Audience
AI context (quick reading list) cursor-knowledge/ai-context-reading-list.md 26-link companion list for the onboarding guides
Non-technical AI onboarding onboarding/ Beginners and non-developers
PM knowledge and glossary product-management/ Product managers and non-technical readers
Session log (build diary) session-log.md Seeing real Cursor sessions in action