gwonxhj · hyeokjun32 · Jun 11, 2026 · Jun 11, 2026
diff --git a/README.ko.md b/README.ko.md
@@ -63,6 +63,9 @@ InferEdge는 다음을 연결하는 validation pipeline입니다.
 Local Studio는 CLI/API/job workflow를 브라우저에서 조작하고 관찰하는 local-first interface입니다.
 cloud SaaS dashboard가 아니며, 사용자의 PC에서 실행되는 demo/review UI입니다.
 
+역할별 브라우저 데모 순서는 [Local Studio demo walkthrough](docs/portfolio/local_studio_demo_walkthrough.md)
+([한국어: Local Studio 데모 가이드](docs/portfolio/local_studio_demo_walkthrough.ko.md))를 기준으로 확인합니다.
+
 ### 브라우저 데모 실행
 
 1. `poetry run inferedgelab serve --host 127.0.0.1 --port 8000` 실행

diff --git a/README.md b/README.md
@@ -136,6 +136,7 @@ Portfolio entry points:
 |---|---|---|
 | [Portfolio submission](docs/portfolio/inferedge_portfolio_submission.md) | [한국어: 포트폴리오 제출 문서](docs/portfolio/inferedge_portfolio_submission.ko.md) | submission-ready project narrative |
 | [Resume/interview summary](docs/portfolio/inferedge_resume_interview_summary.md) | [한국어: 이력서/면접 요약](docs/portfolio/inferedge_resume_interview_summary.ko.md) | short role-specific explanation |
+| [Local Studio demo walkthrough](docs/portfolio/local_studio_demo_walkthrough.md) | [한국어: Local Studio 데모 가이드](docs/portfolio/local_studio_demo_walkthrough.ko.md) | browser demo path and role-specific talking route |
 | [1-page architecture summary](docs/portfolio/inferedge_1page_architecture.md) | [한국어: 1페이지 아키텍처 요약](docs/portfolio/inferedge_1page_architecture.ko.md) | ecosystem diagram and role split |
 | [Pipeline status](docs/portfolio/inferedge_pipeline_status.md) | [한국어: 파이프라인 상태](docs/portfolio/inferedge_pipeline_status.ko.md) | current implementation status |
 
@@ -170,6 +171,9 @@ It runs on the user's machine through the FastAPI server and is intended as a lo
 InferEdge Local Studio can replay the bundled portfolio evidence without requiring a live Jetson device during an interview walkthrough.
 The `Load Demo Evidence` flow imports the ONNX Runtime CPU and TensorRT Jetson Runtime JSON fixtures from [examples/studio_demo](examples/studio_demo), refreshes Compare View, and keeps the demo pair selectable in Recent jobs while the local server process is running.
 
+For a role-specific browser demo route, use [Local Studio demo walkthrough](docs/portfolio/local_studio_demo_walkthrough.md)
+([한국어: Local Studio 데모 가이드](docs/portfolio/local_studio_demo_walkthrough.ko.md)).
+
 ### Run the Browser Demo
 
 1. Run `poetry run inferedgelab serve --host 127.0.0.1 --port 8000`

diff --git a/docs/portfolio/local_studio_demo_walkthrough.ko.md b/docs/portfolio/local_studio_demo_walkthrough.ko.md
@@ -0,0 +1,97 @@
+# InferEdge Local Studio Demo Walkthrough 한국어 Quick Guide
+
+언어: [English](local_studio_demo_walkthrough.md) | 한국어
+
+이 문서는 Local Studio를 보여줄 때 어떤 순서로 설명하고, 역할별로 어떤 메시지를 강조할지 빠르게 확인하기 위한 요약본이다. 대표/canonical 문서는 [InferEdge Local Studio Demo Walkthrough](local_studio_demo_walkthrough.md)이다.
+
+## 데모 경계
+
+Local Studio는 사용자의 PC에서 committed evidence를 재생하고 API/job/report contract를 확인하는 local-first workflow UI다.
+
+production SaaS dashboard, cloud control plane, production worker service, production remote execution proof가 아니다.
+
+## 실행 순서
+
+```bash
+poetry run inferedgelab serve --host 127.0.0.1 --port 8000
+```
+
+`http://localhost:8000/studio`를 열고 `Load Demo Evidence`를 클릭한다.
+
+이 경로는 live Jetson 없이도 다음 evidence를 보여준다.
+
+- ONNX Runtime CPU FP32 baseline fixture
+- TensorRT Jetson FP16 25W candidate fixture
+- Jetson 15W/25W power-mode context
+- review/block problem case
+- available optional AIGuard portfolio evidence
+
+## 보여줄 순서
+
+1. TensorRT Jetson vs ONNX Runtime 비교부터 보여준다.
+2. 이 demo pair가 committed fixture이며 live Jetson 없이 재생 가능하다고 말한다.
+3. Lab-owned deployment decision context를 확인한다.
+4. 문제 케이스로 annotation missing, invalid structure, contract mismatch, latency regression이 review/block evidence로 남는다는 점을 보여준다.
+5. Runtime Intelligence는 Studio live dashboard가 아니라 Lab-owned report chain으로 설명한다.
+
+## 인용할 수치
+
+| Evidence | 값 |
+|---|---:|
+| ONNX Runtime CPU FP32 mean | `45.4299 ms` |
+| ONNX Runtime CPU FP32 p99 | `49.2128 ms` |
+| ONNX Runtime CPU FP32 FPS | `22.0119` |
+| TensorRT Jetson FP16 25W mean | `10.066401 ms` |
+| TensorRT Jetson FP16 25W p99 | `15.548438 ms` |
+| TensorRT Jetson FP16 25W FPS | `99.340373` |
+| Studio demo speedup | 약 `4.51x` |
+
+이 pair는 backend/device/precision context가 다른 deployment review evidence이며, same-condition regression으로 말하지 않는다.
+
+## Runtime Intelligence 연결
+
+Studio evidence에서 Runtime Intelligence로 넘어갈 때는 아래 Lab-owned report chain을 사용한다.
+
+```text
+InferEdgeOrchestrator operation feed / operation_risk_rollup
+-> InferEdgeEnv telemetry history / comparability-first regression context
+-> optional InferEdgeAIGuard deterministic runtime evidence
+-> InferEdgeLab Runtime Intelligence Risk Summary / deployment risk report
+```
+
+함께 볼 문서:
+
+- [EdgeEnv runtime regression Lab handoff](edgeenv_runtime_regression_lab_handoff.md)
+- [Resume/interview summary](inferedge_resume_interview_summary.md)
+- [Pipeline status](inferedge_pipeline_status.md)
+
+핵심 문장: Orchestrator, EdgeEnv, AIGuard는 evidence provider이고, final deployment decision owner는 Lab이다.
+
+## 역할별 경로
+
+| 역할 | 먼저 보여줄 것 | 명확히 말할 것 |
+|---|---|---|
+| AI Inference Engineer | Runtime comparison, latency/p99/FPS, compare identity | 단순 benchmark가 아니라 provenance-aware inference validation이다. |
+| Embedded / Edge Engineer | Jetson FP16 25W/15W evidence, device-local preservation context | demo는 live hardware 없이 재생 가능하지만, 새 live evidence에는 device가 필요하다. |
+| Backend / AI Platform | API/job/report contract, worker boundary, Lab decision context | contract/evidence orchestration이지 DB/queue/auth/billing production SaaS가 아니다. |
+
+## 피할 표현
+
+- production SaaS 완성
+- Local Studio는 cloud dashboard
+- Runtime Intelligence는 production observability
+- remote dispatch가 production remote execution을 증명
+- AIGuard나 Orchestrator가 final deployment decision owner
+- Studio pair가 same-condition regression
+
+## CLI 확인
+
+브라우저를 열지 않을 때는 아래 명령으로 같은 evidence를 확인한다.
+
+```bash
+poetry run inferedgelab demo-evidence-summary
+poetry run inferedgelab portfolio-demo-check
+poetry run inferedgelab export-demo-evidence --output reports/studio_demo_evidence.md
+```
+
+`portfolio-demo-check`는 committed Studio fixture, README metric, portfolio docs, local Studio asset을 빠르게 검증하는 guard다.
diff --git a/docs/portfolio/local_studio_demo_walkthrough.md b/docs/portfolio/local_studio_demo_walkthrough.md
@@ -0,0 +1,97 @@
+# InferEdge Local Studio Demo Walkthrough
+
+Language: English | [한국어](local_studio_demo_walkthrough.ko.md)
+
+Use this walkthrough when reviewing InferEdge through the local browser UI. It keeps the demo focused on committed evidence, role-specific talking points, and Lab-owned decision boundaries.
+
+## Demo Boundary
+
+Local Studio is a local-first workflow UI. It replays committed evidence and inspects API/job/report contracts on the user's machine.
+
+It is not a production SaaS dashboard, cloud control plane, production worker service, or production remote execution proof.
+
+## Run The Demo
+
+```bash
+poetry run inferedgelab serve --host 127.0.0.1 --port 8000
+```
+
+Open `http://localhost:8000/studio`, then click `Load Demo Evidence`.
+
+The stable browser path loads:
+
+- ONNX Runtime CPU FP32 baseline fixture from `examples/studio_demo`
+- TensorRT Jetson FP16 25W candidate fixture from `examples/studio_demo`
+- Jetson 15W/25W power-mode context
+- validation problem cases for review/block paths
+- optional AIGuard portfolio evidence when available
+
+## Review Order
+
+1. Start with the TensorRT Jetson vs ONNX Runtime comparison.
+2. Confirm the demo pair uses committed fixtures and does not require a live Jetson device.
+3. Open the Lab-owned deployment decision context.
+4. Use the problem cases to show that missing annotations, invalid structures, contract mismatch, and latency regression become explicit review/block evidence.
+5. For Runtime Intelligence, pivot to the report path rather than treating Studio as a live observability dashboard.
+
+## Evidence To Quote
+
+| Evidence | Value |
+|---|---:|
+| ONNX Runtime CPU FP32 mean | `45.4299 ms` |
+| ONNX Runtime CPU FP32 p99 | `49.2128 ms` |
+| ONNX Runtime CPU FP32 FPS | `22.0119` |
+| TensorRT Jetson FP16 25W mean | `10.066401 ms` |
+| TensorRT Jetson FP16 25W p99 | `15.548438 ms` |
+| TensorRT Jetson FP16 25W FPS | `99.340373` |
+| Studio demo speedup | about `4.51x` |
+
+Interpret the pair as deployment review evidence across backend/device/precision context, not same-condition regression.
+
+## Runtime Intelligence Hand-Off
+
+When the walkthrough moves from browser evidence to Runtime Intelligence, use the Lab-owned report chain:
+
+```text
+InferEdgeOrchestrator operation feed / operation_risk_rollup
+-> InferEdgeEnv telemetry history / comparability-first regression context
+-> optional InferEdgeAIGuard deterministic runtime evidence
+-> InferEdgeLab Runtime Intelligence Risk Summary / deployment risk report
+```
+
+Point reviewers to:
+
+- [EdgeEnv runtime regression Lab handoff](edgeenv_runtime_regression_lab_handoff.md)
+- [Resume/interview summary](inferedge_resume_interview_summary.md)
+- [Pipeline status](inferedge_pipeline_status.md)
+
+The key sentence is: Orchestrator, EdgeEnv, and AIGuard provide evidence; Lab remains the final deployment decision owner.
+
+## Role-Specific Route
+
+| Role | Show first | Say clearly |
+|---|---|---|
+| AI Inference Engineer | Runtime comparison, latency/p99/FPS, compare identity | This is provenance-aware inference validation, not only a benchmark. |
+| Embedded / Edge Engineer | Jetson FP16 25W/15W evidence and device-local preservation context | The demo can be replayed without live hardware; new live evidence still requires the device. |
+| Backend / AI Platform | API/job/report contract, worker boundary, Lab decision context | This is contract and evidence orchestration, not DB/queue/auth/billing production SaaS. |
+
+## Avoid Saying
+
+- "production SaaS is complete"
+- "Local Studio is a cloud dashboard"
+- "Runtime Intelligence is production observability"
+- "remote dispatch proves production remote execution"
+- "AIGuard or Orchestrator owns the final deployment decision"
+- "the Studio pair is same-condition regression"
+
+## CLI Checks
+
+Use these checks when the browser is not needed:
+
+```bash
+poetry run inferedgelab demo-evidence-summary
+poetry run inferedgelab portfolio-demo-check
+poetry run inferedgelab export-demo-evidence --output reports/studio_demo_evidence.md
+```
+
+`portfolio-demo-check` is the quick guard for committed Studio fixtures, README metrics, portfolio docs, and local Studio assets.