“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 ITeSBeginner
AI Coding Agents Foundations
Developers learn how modern coding agents read context, propose edits, run tools, and fail. The program builds habits for prompting with intent, reviewing diffs critically, and keeping humans accountable for merges. Labs use representative IDE and agent workflows without claiming any vendor certification.
Duration
8 hours
Level
Beginner
Format
Virtual, On-site, or Hybrid
Language
English
Executive brief for stakeholdersDownload Program Brief (PDF)
Enterprise Track
Microsoft
FoundationsIT
AI Coding Agents Foundations
AI Coding Agents
AI Coding
On this page
Ideal for
Software Engineer, Tech LeadFoundationsTailored Team DeliveryImplementation-Focused
Audience Profile
Built for these roles
Software engineers adopting AI coding tools Tech leads enabling team practices QA engineers collaborating with agent-assisted delivery
Overview
Executive overview
Hands-on foundations for using AI coding agents safely and productively in day-to-day software delivery.
Readiness
Prerequisites
- Professional software development experience
- Familiarity with Git and a modern IDE
Program Outcomes
Capabilities your teams will gain
Operate a coding agent through a complete change loop
Provide repository and task context that improves generation quality
Review AI-generated diffs for correctness, security, and style
Document team norms for AI-assisted commits and pull requests
Curriculum
Curriculum roadmap
1
How coding agents work
2
Context, prompts, and repository grounding
3
Review and verification discipline
4
Applied labs across common engineering tasks
1Module 1
How coding agents work
+
Module 1
How coding agents work
VNode-designed module covering how coding agents work for enterprise AI coding adoption.
- Agent loop: plan, edit, run, verify
- Context windows, repositories, and grounding
2Module 2
Context, prompts, and repository grounding
+
Module 2
Context, prompts, and repository grounding
VNode-designed module covering context, prompts, and repository grounding for enterprise AI coding adoption.
- VNode-designed module covering context
- and repository grounding for enterprise AI coding adoption
3Module 3
Review and verification discipline
+
Module 3
Review and verification discipline
VNode-designed module covering review and verification discipline for enterprise AI coding adoption.
- VNode-designed module covering review
- verification discipline for enterprise AI coding adoption
4Module 4
Applied labs across common engineering tasks
+
Module 4
Applied labs across common engineering tasks
VNode-designed module covering applied labs across common engineering tasks for enterprise AI coding adoption.
- Applied labs across common engineering tasks
Delivery Models
Delivery models
Virtual ILTOnsiteHybridExecutive WorkshopBootcampWeekend
Engagement Fit
Engagement fit
Implementation-focused labsPrivate cohort deliveryBeginner practitioner depthBusiness outcome alignment
Enterprise Customization
Enterprise customization
Tailor this program to your organization's priorities: Raises baseline productivity and review discipline so AI-assisted coding improves throughput without increasing defect or security risk.
- •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