Phase 11 — AI Coding Platforms

How tools like Cursor, Copilot, Windsurf, and Claude Code actually work — and how to build one. The editor surface, codebase indexing + symbol/AST retrieval, reliable apply, the latency-tiered multi-model engine (autocomplete → agent), BYOK/provider routing, and coding-specific evaluation. A synthesis phase that assembles RAG (9), agents (10), gateways (8), model selection (5), and serving (7) into an IDE product.

Why this phase matters

AI coding tools are the most-used LLM products by engineers and the clearest example of a complete LLM application. They don't introduce a new primitive — they compose the curriculum: retrieval over a codebase (Phase 9), an agent loop with tools (Phase 10), multi-model routing/BYOK (Phase 8, Phase 5.09), and brutal latency/serving constraints (Phase 7). Two ideas govern the phase: context selection under a latency budget is the core problem, and latency tiers force a multi-model architecture (you can't serve autocomplete and an agent with one model). Differentiation comes from context selection + apply reliability + routing — rarely the base LLM.

Documents

#DocumentWhat you'll be able to do
00Cursor-Style ArchitectureSee the platform anatomy + the context-selection-under-latency problem
01VS Code Extension ArchitectureBuild the editor surface; the extension-vs-fork decision
02Codebase IndexingRAG for code: code-aware chunking, embeddings, incremental, privacy
03Symbol Search and ASTStructural retrieval (symbols/call graph) — why hybrid beats embeddings
04Inline Edit and Apply-PatchLand edits reliably; apply-rate; the apply model
05Autocomplete ModelsFIM, the latency-extreme tier, acceptance rate
06Planning vs Execution ModelsThe multi-model engine; route per sub-task; planner–executor
07BYOK and Provider RoutingThe gateway-in-the-IDE; managed/BYOK/local; privacy
08Evaluating Code AgentsA metric per feature; programmatic eval; the regression gate

How to work through it

Read 00 (the map + the two governing ideas) first. 01 is the editor surface; 02–03 are context selection (semantic + structural retrieval — the core problem); 04 is reliable apply; 05 is the latency-extreme autocomplete tier; 06 makes the multi-model engine explicit; 07 is the gateway/BYOK/privacy layer; 08 ties it together with coding-specific eval. Every doc opens with a from-zero plain-English primer and ends with a buildable, measured lab. Because this is a synthesis phase, cross-links to Phases 5/7/8/9/10 are dense — read each doc as "how this curriculum concept specializes for code in an IDE."

Phase 11 artifacts

  • A file-level coding assistant + subsystem map (00); a minimal VS Code extension (01).
  • A code index (AST chunks + embeddings) + a hybrid vs embeddings-only recall comparison (02); a symbol table + call graph with impact analysis (03).
  • An apply pipeline with apply-rate + diff-preview (04); a FIM autocomplete (local) with acceptance + latency (05).
  • A sub-task router + planner–executor blended-cost comparison (06); a provider-agnostic BYOK + local-fallback assistant with a fail-closed data-policy route (07).
  • A per-feature eval (acceptance / apply-rate / task-resolution) + a routing-change CI gate (08).

Next

Phase 12 — Evaluation