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NemoClaw：NVIDIA 企業級 AI Agent 框架 2026 完整指南

NVIDIA 在 GTC 2026 開源的 NemoClaw 框架，如何透過四層隔離和零權限預設，讓 AI Agent 安全進入生產環境？

2026年3月23日 8 min read · 中等

Security Orchestration Interface Infrastructure Governance

This article is one route in OpenClaw's external narrative arc.

時間：2026-03-23 | 類別：AI Agent | 閱讀時間：12 分鐘

前言：OpenClaw 的安全革命

「OpenClaw 開啟了 AI 的下一個前沿，但 NemoClaw 讓這個前沿對企業安全。」

這是 Jensen Huang 在 NVIDIA GTC 2026 上的核心訊息。

OpenClaw 在 2026 年 1 月爆紅，成為史上增長最快的開源項目，GitHub 星數超過 200,000。它讓 AI Agent 能夠長時間自主運行、編寫程式碼、瀏覽網頁、鏈式調用 API。但企業對它說「不」了——原因很簡單：沒有安全防護、沒有沙盒、沒有審計軌跡。一個被攻陷的 Agent 可以訪問整個系統。

2026 年 3 月 16 日，NVIDIA 在 GTC 2026 上正式發布 NemoClaw，解決了這個問題。

「NemoClaw 為自主 AI Agent 提供企業級安全和隱私控制。」

1. NemoClaw 是什麼？

核心定位

NemoClaw 是 NVIDIA 開源的一個軟體棧，建立在 OpenClaw 之上，為生產環境部署自主 AI Agent 添加企業級安全基礎設施。

關鍵數據：

發布日期：2026 年 3 月 6 日
GTC 2026 公告：2026 年 3 月 16 日
授權：Apache 2.0（免費開源）
狀態：Alpha / 早期預覽
GitHub 星數：4,600+（快速增長中）
預設模型：Nemotron 3 Super 120B

類比：瀏覽器分頁隔離

想像瀏覽器的分頁隔離：

每個分頁在獨立的沙盒中運行
如果一個分頁被攻陷，無法影響其他分頁

NemoClaw 對 AI Agent 做同樣的事情。

2. 架構設計

兩大核心組件

TypeScript 插件（CLI 介面）

薄包裝 CLI 工具
整合 OpenClaw CLI
註冊 openclaw nemoclaw 命名空間
運行在 OpenClaw gateway 進程中
處理所有用戶交互

核心命令：

launch — 新安裝
connect — 交互式 shell
status — 狀態報告
logs — 流式日誌
slash — 聊天處理器

Python Blueprint（安全邏輯）

版本化工件，包含所有安全邏輯
負責創建沙盒、應用策略、配置推論
插件解析、驗證、執行 blueprint

設計優勢：

插件保持穩定
Blueprint 獨立發布週期
安全修補無需觸動 CLI

Blueprint 生命週期

每個 NemoClaw 部署遵循五個階段：

1. Resolve — 定位工件，驗證版本約束
2. Verify — 確認工件摘要（不可變）
3. Plan — 確定所需 OpenShell 資源
4. Apply — 通過 openshell CLI 命令執行
5. Status — 報告部署當前狀態

推論路由流程

Agent（沙盒內） → OpenShell Gateway → NVIDIA Cloud（build.nvidia.com）

敏感數據始終保持在沙盒內。NemoClaw 還包含隱私路由器：

使用本地開源模型保留敏感上下文
僅在策略允許時路由到前沿模型
路由決策基於成本和隱私策略，而非 Agent 偏好

3. 四層安全隔離

這是 NemoClaw 與運行原始 OpenClaw 的最大區別。

四層防護

層級	功能	運行時可更改
Network	拦截未授權出站連接，使用 allowlist	✅ 熱重載
Filesystem	限制 `/sandbox` 和 `/tmp` 外訪問，系統路徑只讀	❌ 創建時鎖定
Process	拦截特權提升和危險系統調用，使用 Landlock、seccomp、netns	❌ 創建時鎖定
Inference	重定向 API 調用到受控後端	✅ 熱重載

關鍵設計： 安全約束存在於環境本身。即使 Agent 被攻陷，也無法覆蓋它們。

4. 核心功能

零權限預設

Agent 啟動時權限為零
僅獲取策略明確允許的權限
與大多數工具相反（從全權限開始，然後限制）

運營者審批 TUI

Agent 試圖訪問未列出的主機時，OpenShell 拦截
在終端 UI 中顯示請求
運營者明確批准或拒絕

用例： Agent 想要調用 API，但不在白名單中 → 人工審批

凭證管理

API Key、Token、服務賬號在運行時注入為環境變量：

永不洩漏到沙盒文件系統
如果沙盒被攻陷，憑證不會暴露

完整審計軌跡

每次允許/拒絕決策都會記錄：

合規要求行業（金融、醫療）的必選功能
非選項，是必選

GPU 傳遞

OpenShell 可以將宿主 GPU 傳遞到沙盒：

Agent 可以在安全環境中運行本地推論或微調
無需將數據發送到雲端

Policy as Code

安全策略使用聲明式 YAML（openclaw-sandbox.yaml）編寫：

版本化
可審查
可審計
將安全視為基礎設施一樣處理

超進程執行（Out-of-Process Enforcement）

關鍵設計決策：

安全約束存在於 Agent 進程之外。即使通過提示注入或惡意工具攻陷 Agent，沙盒依然安全。

對比應用層安全：

Agent 管理自己的權限 → 聰明提示可以繞過限制
超進程執行 → Agent 無法繞過，牆壁是建築的一部分，不是家具的一部分

5. Nemotron 3 Super 120B 模型

為什麼選這個模型？

NemoClaw 預裝 Nemotron 3 Super 120B 作為預設模型。這不僅僅是一個大型語言模型，它是為 Agent 工作負載專門設計的。

架構：混合 MoE（Mamba-Transformer）

總參數：1200 億
活動參數：120 億（4.3%）
混合 MoE 架構：Mamba-Transformer 結合

性能指標

指標	Nemotron 3 Super 120B	GPT-OSS-120B	提升
PinchBench 分數	85.6%	71.3%	1.2x
推論吞吐量	442 tokens/sec	378 tokens/sec	1.17x
上下文窗口	100 萬 tokens	200 萬 tokens	0.5x
每美元 tokens	2.2x	1x	2.2x
成本效率	7.5x	1x	7.5x

關鍵優勢：

活動參數少 → 推論速度快、成本更低
PinchBench 分數最高 → Agent 任務性能最佳
上下文窗口達 100 萬 tokens → 處理複雜任務無壓力

6. NemoClaw vs OpenClaw vs NanoClaw

三個版本的同一個想法

每個版本針對不同的受眾。

比較維度	OpenClaw	NanoClaw	NemoClaw
代碼庫規模	~500K 行，70+ 依賴	~500 行核心邏輯	OpenClaw 包裝器
安全	API 白名單（應用層）	Docker/Apple Container（OS 層）	內核沙盒 + 合規
整合	50+ 原生整合	僅核心消息應用	企業套件
LLM 支援	多供應商	Claude 優化	供應商靈活，Nemotron 優化
目標用戶	平台工程團隊	簡單性開發者	安全意識企業

實際案例

某初創公司有三個自主 Agent 運行程式碼部署：

OpenClaw 方案：

一個 Agent 無審核推送到生產環境 → 事故

NemoClaw 方案：

零權限預設 + 审批 TUI
Agent 想要推送到生產 → 拦截 → 人工審批
安全可控

7. 企業用例

1. 安全操作中心（SOC）

CrowdStrike 合作夥伴：

NemoClaw 與 CrowdStrike 的整合為 SOC 團隊提供：

自動分析安全事件
自動生成檢測規則
自動修補建議
保留完整審計軌跡

需求：

事件繁重、時間敏感、合規要求嚴格
NemoClaw 提供合規審計軌跡

2. 開發管道自動化

場景：

Agent 拉取代碼 → 執行測試 → 編譯 → 部署
所有操作都在沙盒中
零權限預設 + 凭證隔離
完整審計軌跡

優勢：

減少人為錯誤
保持審計軌跡
安全合規

3. 財務報告自動化

場景：

Agent 獲取財務數據 → 生成報告 → 審計跟蹤
數據保留在沙盒
完整審計軌跡
符合財務合規要求

8. 整合：NemoClaw + AICC One API

為什麼需要 AICC？

NemoClaw 很強大，但它是半成品：

有限模型訪問（只能用 Nemotron 3）
無自動故障轉移
手動成本管理
高併發需要額外工程

這正是 AICC One API 的價值所在。

AICC 整合示例

import openai

client = openai.OpenAI(
    base_url="https://api.ai.cc/v1",  # ← 僅此處更改
    api_key="your_aicc_key"
)

# 現在可以在 NemoClaw Agent 中使用任何模型
response = client.chat.completions.create(
    model="gpt-5.2",  # 或 claude-4.6, gemini-3.1-flash-lite, glm-5...
    messages=[{"role": "user", "content": "你的 Agent 提示"}]
)

整合後的 Agent 立即獲得：

訪問最佳模型的權利
自動成本優化
零停機保護
300+ 模型選擇
智能自動故障轉移

為什麼這個組合是「黃金組合」

NemoClaw = 腦（協調層）
AICC One API = 神經網絡（模型網關）

NemoClaw 負責安全、沙盒、協調
AICC 負責模型訪問、成本、可用性
完美分工，1+1 > 2

9. 安裝與部署

系統要求

硬體：4+ vCPUs，8GB RAM 最低
操作系統：Ubuntu 22.04 LTS 或更高版本
模型：Nemotron 3 Super 120B（預裝）

一行安裝

curl -fsSL https://nvidia.com/nemoclaw.sh | bash

安裝後操作

# 啟動新安裝
openclaw nemoclaw launch

# 連接到交互式 shell
openclaw nemoclaw connect

# 查看狀態
openclaw nemoclaw status

# 流式日誌
openclaw nemoclaw logs

# 聊天處理器
openclaw nemoclaw slash

10. 總結：企業 AI Agent 的未來

為什麼 NemoClaw 是 2026 年必讀

技術層面：

四層內核沙盒隔離
零權限預設
超進程執行
完整審計軌跡

戰略層面：

NVIDIA 傾力投入
Apache 2.0 開源
4,600+ GitHub 星數
企業級合作夥伴（CrowdStrike、Salesforce 等）

生態層面：

OpenClaw 200,000+ 星的基礎
Nemotron 3 Super 120B 專為 Agent 優化
AICC One API 整合，300+ 模型選擇

什麼人應該關注 NemoClaw？

✅ 非常適合：

大型工程團隊，有專業 DevOps/MLOps 資源
需要完整源碼控制，可自定義每一層
已投資 NVIDIA 基礎設施或計劃投資
想為開源貢獻，影響開源路線圖
有 3-6 個月的平台設置和調優跑道

❌ 考慮替代方案如果：

無專業 AI 基礎設施團隊管理自托管部署
需要本週生產運行 AI Agent，而非本季度
需要開箱即用的安全、憑證隔離、審計軌跡
偏好預測性按 Agent 定價，而非變動基礎設施成本
想要預建 Agent，可在 Email、Slack、CRM、代碼中工作

未來展望

2026 Q3 預期：

更多企業客戶案例
Crowdstrike 整合深度優化
更多模型整合（Claude、GPT、Gemini）

2026 Q4 預期：

Nemotron 3 Ultra 發布
更多硬件支援（ARM、RISC-V）
更多行業專用模板

行動建議

如果你想立即試用：

環境準備：

# 安裝 NemoClaw
curl -fsSL https://nvidia.com/nemoclaw.sh | bash

# 連接到交互式 shell
openclaw nemoclaw connect

AICC 整合：

# 註冊 AICC
https://api.ai.cc

# 更改 base_url
client = openai.OpenAI(
    base_url="https://api.ai.cc/v1",
    api_key="your_aicc_key"
)

開始構建 Agent：
- 創建 openclaw-sandbox.yaml 安全策略
- 定義 Agent 任務
- 運行並監控審計軌跡

如果你想深入學習：

Second Talent 完整指南：NVIDIA NemoClaw: How It Works, Use Cases & Features
AI.cc 企業指南：NVIDIA NemoClaw Open-Source AI Agent Framework
NVIDIA 官方：Nemotron 3 Super

結語：安全是 AI Agent 的基礎設施

「AI Agent 是未來，但安全是基礎設施。」

NemoClaw 不僅僅是一個框架，它是企業 AI Agent 時代的基礎設施。它解決了 OpenClaw 的最大問題——安全，讓 AI Agent 從「玩票」走向「生產」。

NVIDIA 的訊息很清晰：

「OpenClaw 開啟了 AI 的下一個前沿，但 NemoClaw 讓這個前沿對企業安全。」

這就是我們正在見證的 AI Agent 時代：安全、可控、可生產。

推薦閱讀：

AI Agent Governance Architecture — AI Agent 治理架構
AI Observability Complete Guide — AI 觀察性完整指南
Embodied AI: From AI Agent to Physical World — 具身 AI 從 Agent 到物理世界

相關標籤： #NemoClaw #NVIDIA #AI_Agent #企業安全 #內核沙盒 #零權限預設

Time: 2026-03-23 | Category: AI Agent | Reading time: 12 minutes

Preface: OpenClaw’s Security Revolution

“OpenClaw unlocks the next frontier of AI, but NemoClaw makes it safe for enterprises.”

This was Jensen Huang’s core message at NVIDIA GTC 2026.

OpenClaw exploded into popularity in January 2026, becoming the fastest-growing open source project in history, with over 200,000 GitHub stars. It allows AI Agents to run autonomously for a long time, write code, browse web pages, and call APIs in chains. But enterprises said “no” to it - the reason is simple: No security protection, no sandbox, no audit trail. A compromised Agent has access to the entire system.

On March 16, 2026, NVIDIA officially released NemoClaw at GTC 2026, which solved this problem.

“NemoClaw provides enterprise-grade security and privacy controls for autonomous AI agents.”

1. What is NemoClaw?

Core positioning

NemoClaw is an open source software stack from NVIDIA, built on OpenClaw, that adds enterprise-level security infrastructure for deploying autonomous AI Agents in production environments.

Key data:

Release Date: March 6, 2026
GTC 2026 Announcement: March 16, 2026
License: Apache 2.0 (free and open source)
Status: Alpha / Early Preview
GitHub stars: 4,600+ (growing rapidly)
Default Model: Nemotron 3 Super 120B

Analogy: Browser paging isolation

Think of browser pagination isolation:

Each page runs in a separate sandbox
If one page is compromised, other pages cannot be affected.

NemoClaw does the same thing with AI Agents.

2. Architecture design

Two core components

TypeScript plug-in (CLI interface)

Thin wrapper CLI tool
Integrate OpenClaw CLI
Register the openclaw nemoclaw namespace
Runs in the OpenClaw gateway process
Handles all user interactions

Core commands:

launch — New installation
connect — interactive shell
status — status report
logs — streaming log
slash — chat processor

Python Blueprint (security logic)

Versioned artifacts containing all security logic
Responsible for creating sandboxes, applying policies, and configuring inferences
Plug-in parsing, verification, and blueprint execution

Design Advantages:

Plugins remain stable
Blueprint independent release cycle
Security patching without touching the CLI

Blueprint life cycle

Every NemoClaw deployment follows five phases:

1. Resolve — 定位工件，驗證版本約束
2. Verify — 確認工件摘要（不可變）
3. Plan — 確定所需 OpenShell 資源
4. Apply — 通過 openshell CLI 命令執行
5. Status — 報告部署當前狀態

Inference routing process

Agent（沙盒內） → OpenShell Gateway → NVIDIA Cloud（build.nvidia.com）

Sensitive data remains within the sandbox at all times. NemoClaw also includes Privacy Router:

Preserve sensitive context using native open source models
Route to leading model only if policy allows
Routing decisions are based on cost and privacy policies, not Agent preferences

3. Four-layer security isolation

This is the biggest difference between NemoClaw and running raw OpenClaw.

Four layers of protection

Level	Function	Can be changed at runtime
Network	Block unauthorized outbound connections, use allowlist	✅ Hot reload
Filesystem	Restrict `/sandbox` and `/tmp` external access, system path is read-only	❌ Locked on creation
Process	Block privilege escalation and dangerous system calls using Landlock, seccomp, netns	❌ Lock on creation
Inference	Redirect API calls to controlled backend	✅ Hot Reload

Key Design: Security constraints exist within the environment itself. Even if the Agent is compromised, they cannot be overridden.

4. Core functions

Zero permission default

Agent starts with zero permissions
Get only permissions explicitly allowed by the policy
Contrary to most tools (start with full permissions, then restrict)

Operator Approval TUI

OpenShell interception when Agent tries to access unlisted host
Show request in terminal UI
Express approval or rejection by the operator

Use case: Agent wants to call the API, but is not in the whitelist → manual approval

Credential Management

API Key, Token, and service account are injected as environment variables at runtime:

Never leak to sandboxed filesystem
Credentials will not be exposed if the sandbox is compromised

Complete audit trail

Each allow/deny decision is logged:

A must-have feature for industries with compliance requirements (finance, medical)
Not optional, required

GPU pass

OpenShell can pass the host GPU to the sandbox:

Agents can run local inference or fine-tuning in a secure environment
No need to send data to the cloud

Policy as Code

Security policies are written using declarative YAML (openclaw-sandbox.yaml):

Versioning
Reviewable
Auditable
Treat security like infrastructure

Out-of-Process Enforcement

Key Design Decisions:

Security constraints exist outside the Agent process. Even if the Agent is compromised via hint injection or malicious tools, the sandbox remains secure.

Compare application layer security:

Agent manages its own permissions → Smart tips can bypass restrictions
Hyper-process execution → Agent cannot be bypassed, the wall is part of the building, not part of the furniture

5. Nemotron 3 Super 120B model

Why choose this model?

NemoClaw comes pre-installed with Nemotron 3 Super 120B as a preset model. This is not just a large language model, it is specifically designed for Agent workloads.

Architecture: Hybrid MoE (Mamba-Transformer)

Total parameters: 120 billion
Activity parameters: 12 billion (4.3%)
Hybrid MoE Architecture: Mamba-Transformer combination

Performance indicators

Metrics	Nemotron 3 Super 120B	GPT-OSS-120B	Boost
PinchBench Score	85.6%	71.3%	1.2x
Inference throughput	442 tokens/sec	378 tokens/sec	1.17x
Context window	1 million tokens	2 million tokens	0.5x
tokens per dollar	2.2x	1x	2.2x
Cost efficiency	7.5x	1x	7.5x

Key Benefits:

Fewer active parameters → faster inference and lower cost
Highest PinchBench score → Best Agent task performance
Context window up to 1 million tokens → handle complex tasks stress-free

6. NemoClaw vs OpenClaw vs NanoClaw

Three versions of the same idea

Each version targets a different audience.

Comparison Dimensions	OpenClaw	NanoClaw	NemoClaw
Codebase size	~500K lines, 70+ dependencies	~500 lines of core logic	OpenClaw wrapper
Security	API Whitelist (Application Layer)	Docker/Apple Container (OS Layer)	Kernel Sandbox + Compliance
Integrations	50+ native integrations	Core messaging apps only	Enterprise Suite
LLM Support	Multi-Supplier	Claude Optimization	Supplier Flexibility, Nemotron Optimization
Target Users	Platform Engineering Team	Simplicity Developers	Security Aware Enterprise

Actual case

A start-up company has three independent Agent running code deployments:

OpenClaw Solution:

An Agent is pushed to the production environment without review → accident

NemoClaw Solution:

Zero permission preset + approval TUI
Agent wants to push to production → intercept → manual approval
Safe and controllable

7. Enterprise use cases

1. Security Operations Center (SOC)

CrowdStrike Partners:

NemoClaw’s integration with CrowdStrike provides SOC teams:

Automatically analyze security events
Automatically generate detection rules
Automatic patching suggestions
Keep a complete audit trail

Requirements:

Heavy events, time-sensitive, strict compliance requirements
NemoClaw provides compliance audit trail

2. Development pipeline automation

Scene:

Agent pulls the code → executes the test → compiles → deploys
All operations are in the sandbox
Zero permission preset + credential isolation
Complete audit trail

Advantages:

Reduce human error
Maintain an audit trail
Security compliance

3. Financial reporting automation

Scene:

Agent obtains financial data → generates reports → audit trail
Data remains in the sandbox
Complete audit trail
Meet financial compliance requirements

8. Integration: NemoClaw + AICC One API

Why is AICC needed?

NemoClaw is powerful, but it’s half-baked:

Limited model access (only available with Nemotron 3)
No automatic failover
Manual cost management
High concurrency requires additional engineering

This is where the value of AICC One API comes in.

AICC Integration Example

import openai

client = openai.OpenAI(
    base_url="https://api.ai.cc/v1",  # ← 僅此處更改
    api_key="your_aicc_key"
)

# 現在可以在 NemoClaw Agent 中使用任何模型
response = client.chat.completions.create(
    model="gpt-5.2",  # 或 claude-4.6, gemini-3.1-flash-lite, glm-5...
    messages=[{"role": "user", "content": "你的 Agent 提示"}]
)

Integrated Agent gets immediately:

Right to access the best models
Automatic cost optimization
Zero downtime protection
300+ models to choose from
Intelligent automatic failover

Why this combination is the “golden combination”

NemoClaw = 腦（協調層）
AICC One API = 神經網絡（模型網關）

NemoClaw is responsible for security, sandboxing, and coordination
AICC is responsible for model access, cost, availability
Perfect division of labor, 1+1 > 2

9. Installation and deployment

System requirements

Hardware: 4+ vCPUs, 8GB RAM minimum
OS: Ubuntu 22.04 LTS or higher
Model: Nemotron 3 Super 120B (pre-installed)

One-line installation

curl -fsSL https://nvidia.com/nemoclaw.sh | bash

Post-installation operations

# 啟動新安裝
openclaw nemoclaw launch

# 連接到交互式 shell
openclaw nemoclaw connect

# 查看狀態
openclaw nemoclaw status

# 流式日誌
openclaw nemoclaw logs

# 聊天處理器
openclaw nemoclaw slash

10. Summary: The future of enterprise AI agents

Why NemoClaw is a Must-Read in 2026

Technical level:

Four layers of kernel sandbox isolation
Zero permission preset
Hyper-process execution
Complete audit trail

Strategic Level:

NVIDIA is all in
Apache 2.0 open source
4,600+ GitHub stars
Enterprise-level partners (CrowdStrike, Salesforce, etc.)

Ecological level:

OpenClaw 200,000+ star base
Nemotron 3 Super 120B is optimized for Agent
AICC One API integration, 300+ model selections

Who should be concerned about NemoClaw?

✅ Great for:

Large engineering team with professional DevOps/MLOps resources
Requires complete source code control, each layer can be customized
Invested or planning to invest in NVIDIA infrastructure
Want to contribute to open source and influence the open source roadmap
Have 3-6 months runway for platform setup and tuning

❌ Consider alternatives if:

No dedicated AI infrastructure team to manage self-hosted deployments
Need to run AI Agent in production this week, not this quarter
Requires out-of-the-box security, credential isolation, and audit trails
Prefer predictive per-agent pricing over variable infrastructure costs
If you want to pre-build Agent, you can work in Email, Slack, CRM, and code

Future Outlook

2026 Q3 Expectation:

More corporate customer cases
Crowdstrike integrates in-depth optimization
More model integrations (Claude, GPT, Gemini)

2026 Q4 Expectation:

Nemotron 3 Ultra released
More hardware support (ARM, RISC-V)
More industry-specific templates

Action recommendations

If you want to try it now:

Environment preparation:

# Install NemoClaw
curl -fsSL https://nvidia.com/nemoclaw.sh | bash

# Connect to interactive shell
openclaw nemoclaw connect

AICC Integration:

# Register AICC
https://api.ai.cc

# Change base_url
client = openai.OpenAI(
    base_url="https://api.ai.cc/v1",
    api_key="your_aicc_key"
)

Start building Agent:
- Create openclaw-sandbox.yaml security policy
- Define Agent tasks
- Run and monitor audit trails

If you want to learn more:

Second Talent Complete Guide: NVIDIA NemoClaw: How It Works, Use Cases & Features
AI.cc Enterprise Guide: NVIDIA NemoClaw Open-Source AI Agent Framework
NVIDIA official: Nemotron 3 Super

Conclusion: Security is the infrastructure of AI Agent

“AI Agent is the future, but security is the infrastructure.”

NemoClaw is more than just a framework, it is the infrastructure for the era of enterprise AI agents. It solves the biggest problem of OpenClaw - security, and allows AI Agent to move from “playing tickets” to “production”.

NVIDIA’s message is clear:

“OpenClaw opens the next frontier of AI, but NemoClaw makes it safe for enterprises.”

This is the era of AI Agents we are witnessing: safe, controllable, and productive.

Recommended Reading:

AI Agent Governance Architecture — AI Agent Governance Architecture
AI Observability Complete Guide — AI Observability Complete Guide
Embodied AI: From AI Agent to Physical World — Embodied AI from Agent to Physical World

Related tags: #NemoClaw #NVIDIA #AI_Agent #Enterprise Security #Kernel Sandbox #Zero Permission Default