diff --git a/docs/LORA.md b/docs/LORA.md
index 9310c110..ae9a1c54 100644
--- a/docs/LORA.md
+++ b/docs/LORA.md
@@ -1,5 +1,9 @@
 # LoRA Adapter Support — dotLLM
 
+> **Status**: design spec, not implemented. This is roadmap step 47. Only the `IAdapterManager`
+> abstraction and `InferenceRequest.AdapterId` exist today — there is no adapter loader, no server
+> endpoint, and no per-request adapter selection. Everything below describes the intended design.
+
 ## Overview
 
 LoRA (Low-Rank Adaptation) enables fine-tuned model behaviors without modifying base weights. Multiple adapters can coexist on the same base model, with per-request adapter selection.
diff --git a/docs/SERVER.md b/docs/SERVER.md
index a8ae065f..41ee2432 100644
--- a/docs/SERVER.md
+++ b/docs/SERVER.md
@@ -28,11 +28,18 @@ Primary chat endpoint. Accepts OpenAI-compatible request format.
   "logit_bias": {"1234": -100},
   "frequency_penalty": 0.5,
   "presence_penalty": 0.3,
-  "n": 1,
-  "lora_adapter": "customer-support"
+  "n": 1
 }
 ```
 
+> **Adapter selection**: there is no `lora_adapter` request field (it is not part of the OpenAI
+> surface either, and the server ignores unknown fields silently). LoRA serving is roadmap step 47
+> and is not implemented: the engine has the `IAdapterManager` abstraction and
+> `InferenceRequest.AdapterId`, but there is no implementation, no adapter admin endpoint, and no
+> way to select an adapter per request. Until then, serve an adapted model by merging the adapter
+> into the weights offline and loading the merged model — via `--model` at startup or
+> `POST /v1/models/load`. See [LORA.md](LORA.md) for the planned design.
+
 **Response** (non-streaming):
 ```json
 {