prompt
FreeExpert platform engineer prompt for AI infrastructure design
FreeFree tier
About prompt
A comprehensive system prompt for a Platform Engineer specializing in infrastructure-as-code, internal developer platforms, and cloud-native systems for AI workloads. The prompt defines core principles (declarative IaC, platform as a product, cost-awareness, security-first), architecture patterns for model serving, agent runtime, and data training platforms, and operational excellence standards including observability, GitOps, and disaster recovery. It instructs the AI to produce a detailed design output including an architecture diagram, IaC skeleton, SLO/SLI definitions, cost model, and security posture.
Key Features
Infrastructure as Code (IaC) always - declarative, versioned, reproducible
Platform as a Product mindset with SLOs and developer experience metrics
Cost-aware design with autoscaling, spot instances, and right-sizing
Security at the foundation - zero trust, least privilege, secrets management
Model Serving Platform: multi-model routing, rate limiting, A/B testing
Agent Runtime Platform: containerized execution, sandboxes, persistent state
Data Training Platform: feature stores, orchestration, dataset governance
Observability three pillars: metrics, logs, traces with AI-specific signals
GitOps for all deployments and infrastructure changes
Disaster recovery with multi-region failover and tested runbooks
Pros & Cons
Pros
- Comprehensive coverage of platform engineering principles for AI
- Provides specific, actionable architecture patterns and operational guidelines
- Emphasizes security, cost-awareness, and observability from the start
- Includes a structured output format for consistent design deliverables
Cons
- Requires manual implementation and adaptation to specific environments
- Focused on AI workloads, less applicable to general infrastructure
- No built-in integration with actual tools or platforms
Best For
Designing internal developer platforms for AI/ML workloadsArchitecting model serving infrastructure with multi-model supportBuilding agent execution runtimes with sandboxing and observabilityCreating data training pipelines with feature stores and governanceImplementing GitOps workflows for infrastructure and application deploymentsOptimizing cloud costs for AI infrastructure
FAQ
What is this prompt for?
This is a system prompt that defines the role and capabilities of a Platform Engineer AI assistant, specializing in infrastructure-as-code and cloud-native systems for AI workloads.
What areas does the prompt cover?
It covers core principles (IaC, platform as product, cost-awareness, security), architecture patterns for model serving, agent runtime, and data training platforms, and operational excellence including observability, GitOps, and disaster recovery.
How should this prompt be used?
The prompt is intended to be provided to an AI assistant to guide its responses as a Platform Engineer expert. It asks the AI to deliver architecture diagrams, IaC skeletons, SLO/SLI definitions, cost models, and security postures when asked to design a platform.