+ "Ask the docs"· Claude full-context (docs <500pp) + prompt cache · no RAG
Execution — all additive (lexical hot path never blocked)
build-time
Embed ~400 docs
@xenova ONNX, ~50-80MB, NOT tfjs-node (383MB > Vercel 250MB)
→
ship
search-vectors.json
~0.8MB artifact, loaded server-side
→
runtime
Orama mode:hybrid
load vectors → lexical ∪ vector query
→
measure
recall vs held-out set
must beat lexical-only to keep
Risk heat map
tfjs-node at runtime — 383MB breaks Vercel 250MB limit🔴→🟢 MITIGATED · @xenova ONNX, build-time only
recall improvement unproven at ~400 docs🟡 GATE · held-out query set must show gain
+0.8MB vector payload🟡 server-side load, NOT shipped to browser
lexical hot path — untouched🟢 fully additive, zero regression
cold start — embed is build-time, no runtime model load🟢 no added cold cost
Trigger gate — should we build this at all?
Does query telemetry show lexical search missing synonym / concept matches users expect?
NO → stay deferred ✅
Live verify 2026-06-08: "agnt"→783 hits, typo tolerance + 5 tabs all work. Lexical closes ~80-90% of the gap. Don't build speculatively.
YES → build Approach C
Add the build-time embed step + hybrid mode, then prove recall gain on a held-out set before keeping it. Effort ≈ 2 sprints.
Decision (ADR-lite): defer. Lexical is sufficient per live verification; semantic adds a ~0.8MB artifact + build complexity for unproven recall gain on a 400-doc corpus. Revisit only when telemetry proves a synonym/concept gap. Fully reversible — nothing on the lexical hot path changes.