Welcome to AI Dev Me: Power Platform Development with AI Tools

Estimated reading time: 3 minutes

Where Microsoft Technology Meets Intelligent Coding

I’m Zsolt Zombik, a senior Power Platform developer at ELCA Informatik AG, working at the intersection of Microsoft Power Platform and AI-assisted software development.

This blog is not about shortcuts, hype, or “10x developer” promises.
It is about building real, enterprise-grade Power Platform solutions—applications that implement complex business logic, enforce strict security models, scale to large datasets, and run reliably in production.

Everything shared here is based on hands-on, production experience, not theory.

What Is Power Platform AI Development?

Power Platform AI development combines:

Microsoft Power Platform (Power Apps, Dataverse, PCF, Power Automate)
Modern AI coding assistants such as GitHub Copilot and Claude

The goal is not to replace developers, but to enhance professional development workflows—improving speed, quality, and maintainability while preserving architectural discipline.

When used correctly, AI tools can help you:

Build PCF controls faster using TypeScript and React
Generate type-safe Dataverse queries
Apply proven Fluent UI patterns
Detect performance bottlenecks
Improve test coverage and code quality

When used incorrectly, they introduce risk.
This blog focuses on using AI effectively and responsibly.

The Reality of Enterprise Power Platform Development

If this sounds familiar, you are not alone:

You are building a custom PCF control for a Dynamics 365 solution.
It queries multiple Dataverse tables, applies complex permission checks, renders a sophisticated Fluent UI interface, and must perform well with thousands of records.

The traditional approach:

Weeks of development
Extensive manual boilerplate
Trial-and-error debugging
Fragmented documentation

The AI-assisted approach:

Still requires expertise and judgment
Reduces boilerplate and repetition
Improves consistency and review quality
Enables faster iteration without lowering standards

The difference is not the tool, but how it is used.

What You Will Learn on This Blog

1. Enterprise Power Platform Development with AI

Deep technical content focused on production-grade solutions, including:

PowerApps Component Framework (PCF) development
TypeScript and React architecture for model-driven apps
Advanced Dataverse Web API patterns
Multi-entity security and permission models
Performance optimization for large datasets

All examples are based on real production implementations.

2. AI Tools in Real Power Platform Projects

Practical guidance on using AI coding assistants where they genuinely help:

GitHub Copilot for PCF and Dataverse development
Claude for complex problem-solving and architecture design
Prompt engineering tailored to Power Platform contexts
Context management for accurate code generation
When to trust AI output—and when to verify manually

This includes honest assessments, not marketing claims.

3. UI Development with Fluent UI and AI Assistance

Topics include:

React component architecture for Power Platform
Fluent UI customization and optimization
Bundle size reduction and tree-shaking strategies
Responsive design and accessibility compliance

Measured results are shared, including real performance metrics.

4. DevOps and Automation for Power Platform

End-to-end delivery topics:

CI/CD pipelines with Azure DevOps and GitHub Actions
Automated testing (Jest, React Testing Library, Playwright)
PowerShell and infrastructure automation
Environment management and deployment strategies

All approaches are tested in enterprise environments.

Who This Blog Is For

This blog is designed for developers who:

Build enterprise Power Platform applications
Use PCF, Dataverse, and custom integrations
Care about architecture, security, and performance
Want to apply AI tools practically, not blindly
Prefer deep technical content over surface-level tutorials

If you work in complex Power Platform environments and want real-world guidance, this content is for you.

What Makes This Blog Different

Production-tested patterns only
Complete implementations, not snippets
Measured results (performance, bundle size, productivity)
Balanced view of AI tools—strengths and limitations
Low-code and pro-code treated as complementary

Modern Power Platform development requires knowing when to use each approach. This blog reflects that reality.

Final Thought

AI is changing how we build software—but expertise still matters.

This blog explores how experienced Power Platform developers can use AI tools to build better systems, faster, without compromising quality or responsibility.

If this resonates with you, welcome.