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AI is easier to understand once you stop treating every product as the same kind of thing. ChatGPT, Claude, Cursor, Codex, Nvidia GPUs and Groq LPUs all belong to the AI ecosystem, but they live at different layers. This primer builds one coherent mental model from ordinary-user level through senior-software-engineer level. Updated August 2026. The evergreen sections explain architecture and engineering. Time-sensitive company, financial and product-access notes are explicitly dated. How to read this If you are non-technical, sections 1–4 are enough for the core picture. If you work in software, continue through coding agents, RAG/tool use, security and inference. Senior engineers should focus especially on sections 8–13. Contents 1. The AI stack: do not mix the layers 2. What an LLM actually is 3. Closed, open-weight and open-source 4. The major AI ecosystems 5. Cursor, Claude Code, Codex and coding agents 6. From autocomplete to delegated engineering 7. Perplexity and the orch...

Understanding the Modern AI Landscape A layered knowledge-transfer guide: beginner → senior software engineer Compiled and fact-checked as of August 21, 2026. Financial and event figures cite press reporting current to that date — treat as a snapshot, not a permanent record. How to use this document This guide is organized in layers. Read Level 0–2 if you're new to AI. Stop after Level 3 if you just need the competitive/business picture. Continue through Level 4–6 if you're technical. Corrections to earlier drafts of this material are folded into the relevant sections rather than left for the end, and are marked clearly wherever they occur. Level 0 — The five-minute mental model The single most useful idea for untangling this topic: "AI company," "AI model," "AI application," and "AI infrastructure" are four different layers, not synonyms. Most confusion in casual AI discussion comes from comparing things that live at different ...