diff --git a/README.md b/README.md
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+++ b/README.md
@@ -135,11 +135,78 @@ Use `.env.example` as your baseline env configuration.
 
 ## Storage Backend Notes
 
-- This project defaults to **SeaweedFS S3 API** for object transit in development and compose deployments.
-- The Python server uses the `minio` Python SDK, which is intentional because SeaweedFS is S3-compatible.
+- Local development defaults to **SeaweedFS** (S3-compatible) via Docker Compose.
+- Production can use any S3-compatible provider; **AWS S3** is the expected choice.
+- The Python server uses the `minio` Python SDK against the S3 API.
 - Runtime configuration uses `S3_*` environment variables.
 - All conversions share one bucket (`S3_BUCKET`, required). Each conversion's objects live under a `{conversion_id}/` key prefix (for example `{conversion_id}/input/source.pptx` and `{conversion_id}/output/slide-0001.jpg`).
 
+### AWS setup
+
+**Bucket**
+
+1. Create one bucket (for example `officeconvert-prod`) in the region where the server runs.
+2. Leave **Block Public Access** enabled. Presigned URLs work without a public bucket.
+3. Optional: add a lifecycle rule to expire objects after a few days as a safety net if cleanup fails.
+
+**Server environment**
+
+Set at minimum:
+
+```bash
+S3_BUCKET=officeconvert-prod
+S3_ENDPOINT=s3.us-east-1.amazonaws.com
+S3_PUBLIC_ENDPOINT=s3.us-east-1.amazonaws.com
+S3_REGION=us-east-1
+S3_USE_SSL=true
+S3_PUBLIC_USE_SSL=true
+S3_ACCESS_KEY=...
+S3_SECRET_KEY=...
+```
+
+Use your bucket's regional hostname for both endpoints unless you deliberately split internal vs client-facing access. `S3_PUBLIC_ENDPOINT` must be reachable by whatever uploads and downloads via presigned URLs (clients, not just the server).
+
+On startup the server calls `CreateBucket` if the bucket is missing. In AWS it is simpler to **pre-create the bucket** and grant object permissions only (see IAM below).
+
+**IAM permissions**
+
+Scope access to the single bucket. Object keys are per-conversion prefixes, so list/delete can target the whole bucket:
+
+```json
+{
+  "Version": "2012-10-17",
+  "Statement": [
+    {
+      "Effect": "Allow",
+      "Action": ["s3:ListBucket"],
+      "Resource": "arn:aws:s3:::officeconvert-prod"
+    },
+    {
+      "Effect": "Allow",
+      "Action": ["s3:GetObject", "s3:PutObject", "s3:DeleteObject"],
+      "Resource": "arn:aws:s3:::officeconvert-prod/*"
+    }
+  ]
+}
+```
+
+Add `s3:CreateBucket` on `arn:aws:s3:::officeconvert-prod` only if you want the server to create the bucket on first boot.
+
+**CORS**
+
+Required only if uploads or downloads go **directly from a browser** to presigned URLs. Server-side clients (`curl`, the Go client) do not need CORS. Allow `PUT` and `GET` for your web origin on the bucket.
+
+**IAM roles vs IAM users**
+
+AWS recommends **roles** over long-lived **IAM user** access keys when the server runs on AWS compute (ECS, EC2, Lambda): a role grants **temporary** credentials that rotate automatically, with no static keys to store or leak.
+
+For this project today, the server reads explicit `S3_ACCESS_KEY` and `S3_SECRET_KEY` via the MinIO SDK. That maps cleanly to:
+
+| Where you run | Practical choice |
+|---------------|------------------|
+| Docker on a VPS, bare metal, or outside AWS | IAM **user** with the policy above; store keys in env or a secrets manager. Fine for a single service at low volume. |
+| ECS / EC2 / EKS on AWS | Prefer an IAM **role** attached to the task or instance. Your orchestrator injects short-lived credentials; you still pass them into `S3_ACCESS_KEY` / `S3_SECRET_KEY` (and a session token if your runtime provides one — the server does not yet read a dedicated `S3_SESSION_TOKEN` env var). |
+
 ## Conversion Tuning Notes
 
 If conversion fails on larger decks, tune these environment variables: