4.0 AI-Accelerated DevOps & Platform Engineering
Overview
This module shifts focus from feature development to the software delivery pipeline and platform. You'll apply AI to DevOps and infrastructure, addressing friction removal and acceleration of flow in the engineering process itself.
Core Themes:
- Infrastructure as Code with AI assistance
- CI/CD pipeline creation and automation
- Eliminating toil and friction in delivery
- Building automation and tooling with AI
What You'll Do
You'll build automation and tooling that drastically reduces the "time to deliver" — one-click deployments, CI/CD pipelines, or internal developer tools — with AI doing most of the heavy lifting.
This module emphasizes Liatrio's ethos of removing toil and enabling flow in systems.
Primary Capabilities You'll Develop
Infrastructure as Code & Environment Automation
Use AI to generate infrastructure-as-code scripts:
- Terraform, CloudFormation, or similar IaC
- Cloud resource configuration
- CI/CD pipeline definitions
- Monitoring and observability setup
Treat environment setup as another code generation task.
CI/CD Pipeline Creation with AI
Design and implement automated pipelines:
- Pipeline definitions (GitHub Actions, Jenkins, etc.)
- Build, test, and deployment automation
- AI-generated test scripts and deployment logic
- Optimization for faster feedback loops
Focus on accelerating flow through automation.
Lean Process Improvement & Tooling
Identify and eliminate friction points:
- Environment setup delays
- Manual testing bottlenecks
- Slow approval processes
- Knowledge sharing gaps
Build small tools or bots to address these — with AI doing the implementation.
Environment Access
You'll need a cloud environment to deploy to. You are not restricted to any particular provider — if you'd prefer to use GCP, Cloudflare, Vercel, or any other platform, go for it.
That said, Liatrio has accounts on the following environments available for participants who want to use them:
Liatrio-Provided Environments
| Environment | Access |
|---|---|
| AWS (liatrio-forge account) | Log in to the AWS SSO Portal with your Liatrio Google account. Select the liatrio-forge account. |
| Azure (sandbox account) | Ask in #liatrio-forge for sandbox access. |
| Liatrioku (Liatrio's internal platform) | See the Liatrioku docs to get started. |
Use AI to help you install and configure whichever CLI tools your chosen provider requires.
These are shared environments. Tear down any infrastructure you create when you're done. If you're using Terraform, a terraform destroy at the end of your work keeps things tidy for everyone.
If you need help getting access to any of these environments, reach out in #liatrio-forge.
Exercises
Pipeline from Scratch Challenge
Take your application and get it from zero to deployed automatically:
- Write a Deployment Spec describing the target architecture
- Use AI to generate Dockerfiles, Kubernetes manifests, or Terraform scripts
- Create CI/CD workflow files with AI assistance
- Deploy to a test environment
- Debug any issues using AI
Friction Hunt & Automation Sprint
- Identify top sources of friction in your development workflow
- Choose one issue to solve
- Build a solution using AI:
- Automation script for environment setup
- Test data generator
- Internal chatbot for documentation search
- Self-healing infrastructure script
- Present your solution to the wave
Demo Your Pipeline
Record a demo (5-10 minutes) showing:
- Your automated pipeline in action
- The infrastructure code you generated
- How AI helped you build it
- Any friction you eliminated
Deliverables
By the end of the DevOps & Platform Module, you must produce:
| Artifact | Description |
|---|---|
| Spec docs | Specifications for pipeline/infrastructure |
| Task breakdowns | How you decomposed the work |
| PR links | Infrastructure code (Terraform, CI/CD config, etc.) |
| Test output | Proof of successful build/deployment runs |
| DevEx tooling demo | Presentation of your friction elimination solution |
| Demo recording | Walkthrough of your pipeline and approach |
| Short retro | What changed — focus on friction removal and flow acceleration |
Exit Criteria
You can move to the Capstone Module when you have:
Built a working pipeline or Infrastructure-as-Code deployment slice.
Your pipeline should automatically build, test, and deploy your application. You should have eliminated at least one source of friction and be able to demonstrate the improvement.
What You'll Learn
By completing this module, you'll have experienced:
- Compressing weeks of infrastructure work into hours
- Friction removal — eliminating toil through automation
- Acceleration of flow — faster feedback, faster delivery
- Using AI for operations, not just development
You've essentially created an internal developer platform prototype where the software lifecycle is automated with AI.