“The Microsoft Fabric implementation program gave our data engineering team a structured path from legacy pipelines to a modern lakehouse architecture.”
Enterprise Program Brief
VNode ITeSIntermediate
Secure AI Coding and Governance
Security and engineering leaders need enforceable policy for AI coding without blocking adoption. This program covers repository classification, secrets handling, model and training opt-out positions, agent execution boundaries, and evidence for auditors. Original VNode curriculum aligned to enterprise practice.
Duration
12 hours
Level
Intermediate
Format
Virtual, On-site, or Hybrid
Language
English
Executive brief for stakeholdersDownload Program Brief (PDF)
Enterprise Track
Microsoft
Security & GovernanceIT
Secure AI Coding and Governance
AI Coding Governance
AI Coding
On this page
Ideal for
Security Engineer, Engineering Manager, Platform LeadSecurity & GovernanceTailored Team DeliveryImplementation-Focused
Audience Profile
Built for these roles
Application and product security engineers Engineering managers owning AI coding policy Platform teams configuring enterprise AI coding controls
Overview
Executive overview
Design security and governance controls for enterprise AI coding — data handling, content exclusions, agent permissions, and audit expectations.
Readiness
Prerequisites
- Familiarity with enterprise SDLC and access control concepts
Program Outcomes
Capabilities your teams will gain
Draft an AI coding governance policy suitable for pilot-to-scale
Classify repositories for allowed agent capabilities
Define controls for secrets, IP, and external tool calling
Produce an audit evidence pack for AI-assisted development
Curriculum
Curriculum roadmap
1
Threat model for AI coding agents
2
Data, IP, and model-policy controls
3
Agent and MCP security boundaries
4
Governance operating model and exceptions
1Module 1
Threat model for AI coding agents
+
Module 1
Threat model for AI coding agents
VNode-designed module covering threat model for ai coding agents for enterprise AI coding adoption.
- Repository and data classification for AI coding
- Content exclusion, IP, and training opt-out
2Module 2
Data, IP, and model-policy controls
+
Module 2
Data, IP, and model-policy controls
VNode-designed module covering data, ip, and model-policy controls for enterprise AI coding adoption.
- VNode-designed module covering data
- and model-policy controls for enterprise AI coding adoption
3Module 3
Agent and MCP security boundaries
+
Module 3
Agent and MCP security boundaries
VNode-designed module covering agent and mcp security boundaries for enterprise AI coding adoption.
- VNode-designed module covering agent
- mcp security boundaries for enterprise AI coding adoption
4Module 4
Governance operating model and exceptions
+
Module 4
Governance operating model and exceptions
VNode-designed module covering governance operating model and exceptions for enterprise AI coding adoption.
- VNode-designed module covering governance operating model
- exceptions for enterprise AI coding adoption
Delivery Models
Delivery models
Virtual ILTOnsiteHybridExecutive WorkshopBootcampWeekend
Engagement Fit
Engagement fit
Implementation-focused labsPrivate cohort deliveryIntermediate practitioner depthBusiness outcome alignment
Enterprise Customization
Enterprise customization
Tailor this program to your organization's priorities: Reduces shadow AI risk and accelerates approved rollout by giving security and engineering a shared control baseline.
- •Map labs to your repositories, languages, and delivery toolchain
- •Emphasize Copilot, Cursor, Claude Code, Codex, or a multi-tool mix
- •Add security, governance, or champion-enablement modules for enterprise rollout
Resources
Program resources
Yes. Most enterprise clients prefer private delivery scoped to role mix, timezone, and rollout timeline. We align lab environments and scenarios to your tenant context where applicable.
Enterprise Proof
Trusted delivery outcomes
“We needed a partner who understood both the technical depth of Azure OpenAI and the governance requirements of an enterprise.”
Banking & Finance
Representative Enterprise Banking Team
The focus was not just on tooling knowledge, but on helping teams work from a shared operating model as they adopted a more modern data platform.
- Clearer platform operating model across teams
- Improved confidence in modern data stack adoption
Healthcare
Representative Healthcare Product Team
The engagement helped product and engineering stakeholders move from interest in AI to clearer implementation choices, security expectations, and prototyping discipline.
- Stronger alignment between product and engineering teams
- Improved clarity on prototype-to-production requirements
Delivery Capability
Enterprise-grade instruction
MCT-led delivery
Programs led by Microsoft Certified Trainer practitioners
Enterprise program oversight
Founder-led specialist delivery with structured rollout planning
Global delivery
APAC · EMEA · Americas · Virtual & Onsite
Implementation-focused
Hands-on labs aligned to production scenarios