1. Overview of Core Exam Updates

The DevNet Expert certification has been officially renamed CCIE Automation, effective February 3, 2026. The Lab Exam remains at version 1.1; only the name has changed, with no substantive adjustments made to the exam content or blueprint. SPOTO courses and question banks have already been updated to reflect the latest version.

The final date to take the original DevNet Expert exam is February 2, 2026; the new name will be fully adopted starting February 3. The entire DevNet certification track has been renamed Cisco Automation, establishing a complete hierarchical structure: CCNA Automation → CCNP Automation → CCIE Automation.

2. Written Exam (350-901 AUTOCOR v2.0): Core Content Adjustments

For the written component, the 350-901 AUTOCOR exam (formerly DEVCOR) has a duration of 120 minutes, and the registration fee is $400.

The Lab Exam lasts 8 hours and costs $1,600; it is divided into a Design module and a Deploy/Operate/Optimize module, comprehensively assessing practical, real-world skills.

Candidates who pass both the AUTOCOR written exam and the Lab Exam will earn the CCIE Automation certification.

3. Written Exam (350-901 AUTOCOR v2.0) Core Content Updates

(1) Updates to the Five Key Modules

Infrastructure as Code (IaC) (30%): Enhanced coverage of AI-driven automation, LLM network agents, and MCP server applications; expanded coverage of advanced Git operations (cherry-pick, reset, revert) and CI/CD pipeline troubleshooting.

Network Programmability & Automation (25%): Added in-depth coverage of Cisco NSO (Network Services Orchestrator); expanded practical application of YANG models (OpenConfig/IETF) and NETCONF/RESTCONF; enhanced coverage of the pyATS testing framework and model-driven telemetry.

Container Technologies (10%): Focused on Docker and Kubernetes network integration; added coverage of designing and deploying containerized automation solutions.

Security (15%): Added coverage of OAuth 2.0 and key management practices; enhanced coverage of applying OWASP security principles within automation scripts.

Automation Operations (20%): Expanded practical exercises using Cisco Modeling Labs (CML); added coverage of network automation log collection, troubleshooting, and performance optimization.

(2) Key Technology Updates

AI and Automation Convergence: Added coverage of building and applying Large Language Model (LLM) network agents, assessing how to leverage AI to enhance network automation efficiency.

Toolchain Expansion: Added core examination content for Terraform and Cisco NSO, positioning them alongside Python and Ansible as core automation tools; enhanced troubleshooting coverage for GitLab CE CI/CD pipelines, including scenarios involving missing dependencies, version conflicts, and test failures.

Cisco Platform Integration: Expanded practical application of APIs across Cisco platforms, including IOS XE, ACI, Meraki, Catalyst Center, and SD-WAN; added coverage of Webex messaging integration and automation, assessing how to utilize APIs to facilitate network event notifications and responses.

4. Lab Exam (CCIE Automation v1.1) Core Focus Areas

(1) Weighting of the Eight Core Domains

Software Design, Development, and Deployment (20%): Designing hybrid, public, or private cloud automation solutions, while considering factors such as maintainability, high availability, and scalability.

Automation Frameworks and Tools (20%): Practical application of Ansible, Terraform, Python, NETCONF/RESTCONF, and YANG models.

Network Device Programmability (15%): Cisco platform API calls, pyATS testing, and model-driven telemetry.

Containers and Orchestration (10%): Automated deployment and management of Docker and Kubernetes networking environments.

Security and Compliance (10%): Automation script security, key management, access control, and compliance checks.

Automation Operations (10%): Monitoring, log collection, troubleshooting, and performance optimization.

Cisco Platform Integration (10%): Automated configuration and management of platforms such as ACI, SD-WAN, and DNA Center.

AI and Automation (5%): Application of LLMs as network agents, and AI-driven fault diagnosis and remediation.

(2) Lab Exam Module Structure

Design Module (3 hours): Analyzing requirements and designing the architecture for automation solutions, including tool selection, deployment models, security policies, etc.

Deploy / Operate / Optimize Module (5 hours):

Writing automation scripts and Playbooks to implement batch configuration and management of devices.

Building CI/CD pipelines to enable automated testing and deployment.

Configuring containerized environments to facilitate automated application deployment.

Troubleshooting and performance optimization to ensure the stable operation of the automation system.

5. The Core Impact of the Exam Update

Short-term Impact:

The written exam now includes new content on AI and advanced automation tools; the difficulty has increased slightly, requiring candidates to acquire additional knowledge regarding new technologies such as LLMs, Terraform, and NSO.

The structure of the lab exam remains unchanged, but it now demands a higher level of proficiency with tools and practical application skills—particularly regarding the use of AI and container technologies.

The period from February 3 to May 3, 2026, serves as a transition phase; during this time, the pass rate may decline by 5–10% as candidates require time to adapt to the new exam titles and content adjustments.

Long-term Impact:

The core body of knowledge remains stable, allowing the foundational preparation built for the previous DevNet Expert certification to be directly applied to the CCIE Automation certification.

The exam is now more closely aligned with actual industry demands; the integration of AI and automation has become an essential skill set for network engineers, thereby significantly enhancing the value of the certification.

As preparation resources become more comprehensive, the pass rate is expected to gradually return to historical levels (approximately 20–30%).

6. Comprehensive Adjustment of Exam Preparation Strategies

(1) Focus Areas for Written Exam Preparation

Prioritize Mastering New Content:

Systematically study the construction and application of LLM network agents, mastering how to leverage AI to simplify network automation tasks.

Deeply research the core concepts and practices of Terraform and Cisco NSO, acquiring proficiency in Infrastructure as Code (IaC) and network service orchestration capabilities.

Strengthen advanced Git operations and CI/CD pipeline troubleshooting skills to enhance the stability and maintainability of automation systems.

Consolidate Core Knowledge:

Review Python scripting, with a specific focus on Cisco platform API calls and NETCONF/RESTCONF configuration.

Master YANG models (OpenConfig/IETF) and network device programmability to improve the compatibility of automation scripts.

Reinforce container technologies (Docker/Kubernetes) and network integration practices to align with cloud-native automation trends.

(2) Focus Areas for Lab Exam Preparation

Enhancing Tool Proficiency:

Practice writing Ansible Playbooks daily, focusing on batch configuration, troubleshooting, and report generation for Cisco devices.

Master the integration of Terraform with Cisco platforms to implement Infrastructure as Code deployments.

Study Cisco NSO in depth, mastering network service definition, template design, and service deployment workflows.

Strengthening Practical Capabilities:

Utilize Cisco Modeling Labs (CML) to build complex network environments for testing and validating automation scripts.

Simulate real-world failure scenarios to practice troubleshooting and restoring automation systems.

Participate in open-source community projects to gain practical experience in automation projects and enhance real-world skills.

AI Automation Practices:

Learn to use LLM tools to assist in writing automation scripts, thereby boosting development efficiency.

Explore AI-driven network fault diagnosis and remediation to enhance the intelligence of automation systems.

7. Recommended Core Learning Resources

CCIE Automation Official Exam Blueprint: Understand the latest exam scope and requirements.

AUTOCOR Official Learning Path: Systematically study the core content for the written exam.

Cisco DevNet Community: Access the latest documentation on automation technologies, practical use cases, and community support.

The newly updated CCIE Automation training courses on the SPOTO platform can save you time and help you master the critical exam topics.

Summary: The latest changes to the CCIE Automation exam primarily involve name changes; the content of the Lab Exam and the Exam Blueprint remain stable. The Written Exam now includes new content regarding AI and advanced automation tools. While the overall difficulty has increased slightly, the core knowledge framework remains unchanged.

SPOTO's courses and question banks have been updated to the latest versions, aligning perfectly with the exam requirements to help you grasp the core focus areas and pass the exam successfully on your first attempt!