“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
AI-Assisted Testing, Review and Quality Engineering
Quality engineering changes when agents generate tests and suggest reviews. This program teaches risk-based test strategies, AI-assisted review checklists, flaky-test triage patterns, and how to reject low-value generated coverage. VNode-designed applied workshop content.
Duration
12 hours
Level
Intermediate
Format
Virtual, On-site, or Hybrid
Language
English
Executive brief for stakeholdersDownload Program Brief (PDF)
Microsoft
Testing & ReviewIT
AI-Assisted Testing, Review and Quality Engineering
AI Quality Engineering
AI Coding
On this page
Ideal for
QA Engineer, Software Engineer, Tech LeadTesting & ReviewTailored Team DeliveryImplementation-Focused
Audience Profile
Built for these roles
QA and SDET practitioners Developers owning quality gates Tech leads setting review standards
Overview
Executive overview
Use coding agents to accelerate test design, code review, and quality signals while keeping human accountability for merge decisions.
Readiness
Prerequisites
- Experience writing automated tests
- AIC-110 or equivalent recommended
Program Outcomes
Capabilities your teams will gain
Generate and critique AI-authored tests against risk priorities
Run structured AI-assisted code reviews
Distinguish useful coverage from vanity tests
Integrate agent quality checks into CI expectations
Curriculum
Curriculum roadmap
1
Quality engineering with coding agents
2
Test generation and critique labs
3
Review playbooks and merge criteria
4
CI signals and continuous improvement
1Module 1
Quality engineering with coding agents
+
Module 1
Quality engineering with coding agents
VNode-designed module covering quality engineering with coding agents for enterprise AI coding adoption.
- Risk-based test design with agents
- AI-assisted code review playbooks
2Module 2
Test generation and critique labs
+
Module 2
Test generation and critique labs
VNode-designed module covering test generation and critique labs for enterprise AI coding adoption.
- VNode-designed module covering test generation
- critique labs for enterprise AI coding adoption
3Module 3
Review playbooks and merge criteria
+
Module 3
Review playbooks and merge criteria
VNode-designed module covering review playbooks and merge criteria for enterprise AI coding adoption.
- VNode-designed module covering review playbooks
- merge criteria for enterprise AI coding adoption
4Module 4
CI signals and continuous improvement
+
Module 4
CI signals and continuous improvement
VNode-designed module covering ci signals and continuous improvement for enterprise AI coding adoption.
- VNode-designed module covering ci signals
- continuous improvement 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: Improves defect detection efficiency and review throughput without mistaking generated volume for quality.
- •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