Skip to Content
Solution PlaysSolution Plays Overview

Solution Plays Overview

Solution Plays are pre-built, tested, production-ready AI solution blueprints. Each play provides everything you need to go from zero to deployed: Copilot agents, configuration files, infrastructure-as-code, evaluation pipelines, and documentation β€” all wired together by the FAI Protocol.

ℹ️

Not Boilerplate

Plays aren’t starter templates. They’re opinionated, WAF-aligned implementations that encode the lessons from hundreds of enterprise AI deployments. You customize the config/ files; the architecture and safety patterns are built in.

What’s in a Play?

Every solution play follows the 4-kit structure:

solution-play-NN/ β”œβ”€β”€ .github/ ← DevKit: Copilot brain β”‚ β”œβ”€β”€ copilot-instructions.md ← under 150 lines, domain knowledge β”‚ β”œβ”€β”€ agents/ ← builder / reviewer / tuner β”‚ β”‚ β”œβ”€β”€ builder.agent.md β”‚ β”‚ β”œβ”€β”€ reviewer.agent.md β”‚ β”‚ └── tuner.agent.md β”‚ β”œβ”€β”€ instructions/ ← WAF-aligned guidance β”‚ β”œβ”€β”€ skills/ ← 150+ line action skills β”‚ └── hooks/ ← SessionStart guardrails β”œβ”€β”€ config/ ← TuneKit: customer-tunable params β”‚ β”œβ”€β”€ openai.json ← model, temperature, max_tokens β”‚ └── guardrails.json ← safety thresholds β”œβ”€β”€ infra/ ← Infra: Azure Bicep (AVM modules) β”‚ β”œβ”€β”€ main.bicep β”‚ └── modules/ β”œβ”€β”€ evaluation/ ← Eval: quality pipeline β”‚ └── eval-config.json └── spec/ ← SpecKit: metadata + docs └── fai-manifest.json ← FAI Protocol wiring
KitPurposeWho Edits
DevKitCopilot agents, instructions, skills, hooksPlatform team
TuneKitAI parameters, guardrails, thresholdsAI team / customer
SpecKitPlay metadata, documentation, wiringAuto-generated
InfraAzure infrastructure (Bicep + AVM)Platform / DevOps

Categories

CategoryPlaysDescription
RAG01, 09, 21Retrieval-Augmented Generation patterns
Agents03, 07, 22, 23Single-agent to swarm orchestration
Infrastructure02, 11, 14Landing zones, gateways, platforms
Security10Content moderation, safety pipelines
Voice04Speech-to-text, LLM, text-to-speech
Document06, 15OCR, extraction, multi-modal processing
Copilot08, 16Copilot Studio bots, Teams extensions
Observability17AI monitoring, metrics, dashboards
Fine-Tuning13LoRA/QLoRA workflows
Edge19On-device AI, ONNX, edge deployment
Real-Time20Streaming analytics, event-driven AI
#NameCategoryComplexityKey Azure Services
01Enterprise RAGRAGIntermediateOpenAI, AI Search, Blob Storage
02AI Landing ZoneInfrastructureIntermediateVNet, Private Endpoints, Key Vault
03Deterministic AgentAgentsIntermediateOpenAI (temp=0), Structured Output
04Call Center Voice AIVoiceAdvancedSpeech Services, OpenAI, Event Hub
05IT Ticket ResolutionAgentsIntermediateOpenAI, ServiceNow, Logic Apps
06Document IntelligenceDocumentIntermediateDocument Intelligence, OpenAI
07Multi-Agent ServiceAgentsAdvancedOpenAI, Semantic Kernel
08Copilot Studio BotCopilotBeginnerCopilot Studio, Dataverse
09AI Search PortalRAGIntermediateAI Search, OpenAI, App Service
10Content ModerationSecurityIntermediateContent Safety, OpenAI

See the full Play Catalog for all 23+ plays.

How to Browse

MethodCommand / Link
Websitefrootai.dev/solution-playsΒ 
VS CodeInstall FrootAI extension β†’ Solution Plays panel
CLInpx frootai list plays
MCP Servernpx frootai-mcp@latest β†’ list_community_plays tool

How to Initialize

# Scaffold any play by number + name npx frootai scaffold 01-enterprise-rag # Scaffold with specific options npx frootai scaffold 02-ai-landing-zone --region eastus2 # List available plays npx frootai list plays

After scaffolding:

  1. Review .github/copilot-instructions.md for domain context
  2. Customize config/openai.json and config/guardrails.json
  3. Deploy infrastructure with az deployment group create --template-file infra/main.bicep
  4. Use @builder agent in Copilot Chat to implement

The Agent Triad

Every play includes three specialized agents that follow the Build β†’ Review β†’ Tune workflow:

AgentRoleModelFocus
BuilderImplements the solutionGPT-4oCode generation, architecture
ReviewerReviews for quality and securityGPT-4o-miniOWASP, WAF compliance, bugs
TunerOptimizes for productionGPT-4o-miniConfig validation, cost, performance
@builder β†’ implements code and architecture ↓ @reviewer β†’ checks security, quality, WAF alignment ↓ @tuner β†’ validates config, thresholds, production readiness

WAF Alignment

All plays are aligned to the 6 Well-Architected Framework pillars:

  • Reliability β€” retry, circuit breaker, health checks, fallbacks
  • Security β€” Managed Identity, Key Vault, RBAC, private endpoints
  • Cost Optimization β€” model routing, token budgets, right-sizing
  • Operational Excellence β€” CI/CD, IaC, observability, incident response
  • Performance Efficiency β€” caching, streaming, async, model routing
  • Responsible AI β€” content safety, groundedness, fairness, transparency

For detailed WAF patterns, see T3: Production Patterns and T2: Responsible AI.

Next Steps

Last updated on