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Nikhil Wagh
Nikhil Wagh

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Vibe Coding Pipelines: How I Let AI Build My .NET CI/CD Workflow

#vibecoding #cicd #dotnet #ai

Introduction

Setting up a CI/CD pipeline for your .NET application used to take hours of YAML, scripting, and trial-and-error debugging. But in 2025, I built mine with just prompts.

Welcome to vibe coding for DevOps — where you don’t write pipelines line-by-line. Instead, you describe the workflow and let your AI tool (like GitHub Copilot, Cursor, or GPT-4 via Azure OpenAI) generate the pipeline for you.

In this article, I’ll show how I used vibe coding to build a complete CI/CD pipeline for a .NET 10 web app using GitHub Actions, with:

  • Build
  • Test
  • Code coverage
  • Containerization
  • Deployment to Azure

What is Vibe Coding for DevOps?

Vibe coding is more than code autocomplete. It’s using AI to interpret your intent and generate entire config flows, scripts, and integration pipelines.

For DevOps, that means:

  • Prompting: “I want to build and deploy my .NET app to Azure”
  • Getting: A full .github/workflows/main.yml with all steps included

It’s fast, shockingly accurate, and makes DevOps approachable for developers who never touched YAML.

Prompt-to-Pipeline Example

Prompt:

“Create a GitHub Actions workflow to build, test, and deploy an ASP.NET Core Web API using .NET 10. Include coverage reporting and push to Azure Web App.”

Copilot Output:

name: .NET 10 CI/CD on: push: branches: [ main ] pull_request: branches: [ main ] jobs: build: runs-on: ubuntu-latest steps: - uses: actions/checkout@v3 - name: Setup .NET 10 uses: actions/setup-dotnet@v4 with: dotnet-version: '10.x' - name: Install dependencies run: dotnet restore - name: Build run: dotnet build --no-restore - name: Test run: dotnet test --collect:"XPlat Code Coverage" - name: Publish run: dotnet publish -c Release -o output - name: Deploy to Azure Web App uses: azure/webapps-deploy@v2 with: app-name: your-app-name publish-profile: ${{ secrets.AZURE_WEBAPP_PUBLISH_PROFILE }} package: output
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One prompt. One working pipeline. No more copy-paste from outdated docs.

Things I Tweaked After the Prompt

  • Added email notifications on failure
  • Integrated SonarCloud for advanced code analysis
  • Used Matrix builds for .NET 8 and .NET 10 parallel testing
  • Added manual approval for production deployments

Best Practices for Vibe DevOps

  • Prompt iteratively — break requests into chunks: build → test → deploy
  • Double-check secrets — never auto-generate secrets in the pipeline
  • Integrate feedback loops — let Copilot review pipeline errors and improve
  • Document prompts — treat them like version-controlled infrastructure

Beyond GitHub Actions

You can vibe-code pipelines for:

  • Azure DevOps YAML (e.g., multi-stage builds)
  • Docker + Kubernetes deployments
  • Terraform or Bicep infrastructure
  • GitLab CI/CD

Prompt examples:

_“Create a Terraform script to deploy Azure SQL + App Service with Key Vault integration”
“Write a Kubernetes deployment.yaml for a containerized .NET 10 API using autoscaling”
_

Conclusion

AI has become more than a coding assistant — it’s now your DevOps engineer too.

By combining vibe coding with .NET’s modern DevOps ecosystem, you can:

  • Automate faster
  • Learn smarter
  • Ship more confidently

So next time you think “I need a CI/CD pipeline,” try prompting it into existence.

You might never write YAML by hand again.

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