“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
Prompt and Context Engineering for Coding Agents
Most AI coding failures are context failures. This VNode program teaches engineers how to encode goals, constraints, done-when criteria, and project conventions into reusable prompts, rules files, and AGENTS.md-style guidance. Participants practice iterative refinement without over-prompting.
Duration
8 hours
Level
Intermediate
Format
Virtual, On-site, or Hybrid
Language
English
Executive brief for stakeholdersDownload Program Brief (PDF)
Microsoft
Prompt & Context EngineeringIT
Prompt and Context Engineering for Coding Agents
AI Coding Agents
AI Coding
On this page
Ideal for
Software Engineer, Staff EngineerPrompt & Context EngineeringTailored Team DeliveryImplementation-Focused
Audience Profile
Built for these roles
Developers who use coding agents daily Staff engineers defining team conventions Developer experience engineers authoring repo guidance
Overview
Executive overview
Techniques for structuring prompts, repository instructions, and multi-step agent context so coding agents deliver reliable engineering outcomes.
Readiness
Prerequisites
- AIC-110 or equivalent hands-on AI coding experience
Program Outcomes
Capabilities your teams will gain
Author prompts that produce reviewable, constrained changes
Create repository instruction files that improve agent consistency
Decompose complex tasks into verifiable agent steps
Measure prompt quality via review outcomes and rework rates
Curriculum
Curriculum roadmap
1
Prompt patterns for coding agents
2
Repository memory and project conventions
3
Task decomposition and planning modes
4
Evaluation loops and team playbooks
1Module 1
Prompt patterns for coding agents
+
Module 1
Prompt patterns for coding agents
VNode-designed module covering prompt patterns for coding agents for enterprise AI coding adoption.
- Goal, context, constraints, done-when prompting
- Repository instructions and AGENTS.md patterns
2Module 2
Repository memory and project conventions
+
Module 2
Repository memory and project conventions
VNode-designed module covering repository memory and project conventions for enterprise AI coding adoption.
- VNode-designed module covering repository memory
- project conventions for enterprise AI coding adoption
3Module 3
Task decomposition and planning modes
+
Module 3
Task decomposition and planning modes
VNode-designed module covering task decomposition and planning modes for enterprise AI coding adoption.
- VNode-designed module covering task decomposition
- planning modes for enterprise AI coding adoption
4Module 4
Evaluation loops and team playbooks
+
Module 4
Evaluation loops and team playbooks
VNode-designed module covering evaluation loops and team playbooks for enterprise AI coding adoption.
- VNode-designed module covering evaluation loops
- team playbooks 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 first-pass quality of agent output and reduces review churn by standardizing how teams brief coding agents.
- •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