Overview
Carlos the Architect implements a multi-agent Software Development Lifecycle (SDLC) for cloud infrastructure design. The system uses 11 specialized AI agents orchestrated through LangGraph to automate the complete journey from requirements gathering to production-ready Terraform code, with historical learning from past deployment feedback.
┌───────────────────────────────────────────────────────────────────────────────────┐│ AGENTIC SDLC PIPELINE │├───────────────────────────────────────────────────────────────────────────────────┤│ ││ REQUIREMENTS ──► LEARNING ──► DESIGN ──► ANALYSIS ──► REVIEW ──► DECISION ──► CODE ││ │ │ │ │ │ │ │ ││ [Gathering] [Historical] [Carlos] [Security] [Auditor] [Recommender] [TF] ││ │ [Learning] [Ronei] [Cost] │ │ │ ││ │ │ ║ [SRE] │ │ │ ││ ▼ ▼ ▼ ▼ ▼ ▼ ▼ ││ Questions Context 2 Designs 3 Reports Approval Selection IaC ││ from feedback │└───────────────────────────────────────────────────────────────────────────────────┘SDLC Phases Mapped to Agents
| SDLC Phase | Agent(s) | Output | Purpose |
|---|---|---|---|
| 1. Requirements | Requirements Gathering | Clarifying questions | Understand user needs |
| 2. Learning | Historical Learning | Context from past designs | Learn from deployment feedback |
| 3. Design | Carlos + Ronei (parallel) | 2 architecture designs | Competitive design generation |
| 4. Analysis | Security, Cost, SRE (parallel) | 3 specialist reports | Multi-dimensional review |
| 5. Review | Chief Auditor | Approval decision | Quality gate |
| 6. Decision | Design Recommender | Final recommendation | Select best design |
| 7. Implementation | Terraform Coder | Infrastructure-as-Code | Production-ready output |
Agent Architecture
The 11 Agents
┌─────────────────────────────────────────────────────────────────┐│ AGENT HIERARCHY │├─────────────────────────────────────────────────────────────────┤│ ││ TIER 1: PRIMARY ARCHITECTS (GPT-4o) ││ ┌─────────────────┐ ┌─────────────────┐ ││ │ CARLOS │ │ RONEI │ ││ │ Conservative │ vs │ Innovative │ ││ │ AWS-native │ │ Kubernetes │ ││ │ temp: 0.7 │ │ temp: 0.9 │ ││ └─────────────────┘ └─────────────────┘ ││ ▲ ▲ ││ └───────┬─────────────┘ ││ │ ││ TIER 0.5: HISTORICAL LEARNING (No LLM - Data Query) ││ ┌─────────────────────────────────────────┐ ││ │ Historical Learning │ ││ │ (Queries Cosmos DB for past feedback) │ ││ └─────────────────────────────────────────┘ ││ ││ TIER 2: SPECIALIST ANALYSTS (GPT-4o-mini) ││ ┌──────────┐ ┌──────────┐ ┌──────────┐ ││ │ Security │ │ Cost │ │ SRE │ ││ │ Analyst │ │ Analyst │ │ Engineer │ ││ └──────────┘ └──────────┘ └──────────┘ ││ ││ TIER 3: DECISION MAKERS (GPT-4o) ││ ┌──────────┐ ┌───────────┐ ┌───────────┐ ││ │ Auditor │ │Recommender│ │ Terraform │ ││ │ Chief │ │ Design │ │ Coder │ ││ └──────────┘ └───────────┘ └───────────┘ ││ ││ TIER 0: REQUIREMENTS (GPT-4o-mini) ││ ┌───────────────────┐ ││ │ Requirements │ ││ │ Gathering │ ││ └───────────────────┘ ││ │└─────────────────────────────────────────────────────────────────┘Agent Details
1. Requirements Gathering Agent
- Model: GPT-4o-mini (cost-optimized)
- Role: Initial clarification of user needs
- Output: 3-5 clarifying questions about:
- Workload characteristics (traffic, data volume, users)
- Performance requirements (latency, throughput, SLAs)
- Security & compliance needs
- Budget constraints
- Deployment preferences
1.5 Historical Learning Node
- Model: None (data query only)
- Role: Learn from past deployment feedback
- Data Source: Azure Cosmos DB (deployment feedback)
- Process:
- Extract keywords from refined requirements
- Query similar past designs from feedback store
- Categorize feedback by success (4-5 stars) vs problems (1-2 stars)
- Extract patterns that worked well
- Extract warnings from problematic deployments
- Output: Formatted context injected into design prompts
- Graceful Degradation: Returns empty context on failure (5s timeout)
2. Carlos (Lead Cloud Architect)
- Model: GPT-4o (main pool)
- Temperature: 0.7 (balanced)
- Personality: Pragmatic, conservative, dog-themed
- Focus: AWS-native managed services, proven patterns, simplicity
- Output: Complete architecture design with Mermaid diagram
- Philosophy: “If it ain’t broke, don’t fix it”
3. Ronei (Rival Architect – “The Cat”)
- Model: GPT-4o (ronei pool)
- Temperature: 0.9 (more creative)
- Personality: Cutting-edge, competitive, cat-themed
- Focus: Kubernetes, microservices, serverless, service mesh
- Output: Alternative architecture design with Mermaid diagram
- Philosophy: “Innovation drives excellence”
4. Security Analyst
- Model: GPT-4o-mini
- Focus Areas:
- Network exposure & segmentation
- Identity & access management
- Data encryption (transit + rest)
- Logging & monitoring
- Incident response readiness
5. Cost Optimization Specialist
- Model: GPT-4o-mini
- Focus Areas:
- Major cost drivers identification
- Reserved instances / savings plans
- Spot/preemptible instance opportunities
- Storage lifecycle & archival
- FinOps best practices
6. Site Reliability Engineer (SRE
- Model: GPT-4o-mini
- Focus Areas:
- Failure scenarios & blast radius
- Capacity planning & auto-scaling
- Observability (metrics, logs, traces)
- Health checks & alerting
- Operational runbooks
7. Chief Architecture Auditor
- Model: GPT-4o (main pool)
- Role: Final quality gate
- Decision: APPROVED or NEEDS REVISION
- Output: Executive summary with strengths and required changes
8. Design Recommender
- Model: GPT-4o (main pool)
- Role: Select the winning design
- Decision: Must choose exactly one (Carlos OR Ronei)
- Output: Recommendation with justification and tradeoffs
9. Terraform Coder
- Model: GPT-4o (main pool)
- Role: Generate production-ready infrastructure-as-code
- Output:
main.tf– Resource definitionsvariables.tf– Input variablesoutputs.tf– Output valuesversions.tf– Provider configuration- Deployment instructions
Workflow Graph
LangGraph State Machine
START
│
▼
┌───────────────────────┐
│ Has User Answers? │
└───────────────────────┘
│ │
NO YES
│ │
▼ │
┌────────────────────┐ │
│ Requirements │ │
│ Gathering │ │
└────────────────────┘ │
│ │
▼ │
┌────────────────────┐ │
│ Clarification │ │
│ Needed? │ │
└────────────────────┘ │
│ │ │
YES NO │
│ │ │
▼ ▼ ▼
END ┌─────────────────┐
(wait for │ Refine │
answers) │ Requirements │
└─────────────────┘
│
▼
┌─────────────────┐
│ HISTORICAL │
│ LEARNING │
│ (query feedback)│
└─────────────────┘
│
┌─────────────┴─────────────┐
│ │
▼ ▼
┌──────────────┐ ┌──────────────┐
│ CARLOS │ │ RONEI │
│ (design) │ PARALLEL │ (design) │
│ +historical │ │ +historical │
│ context │ │ context │
└──────────────┘ └──────────────┘
│ │
└─────────────┬─────────────┘
│
┌───────────────────┼───────────────────┐
│ │ │
▼ ▼ ▼
┌────────────┐ ┌────────────┐ ┌────────────┐
│ SECURITY │ │ COST │ │ SRE │
│ ANALYST │ │ ANALYST │ │ ENGINEER │
└────────────┘ └────────────┘ └────────────┘
│ │ │
└───────────────────┼───────────────────┘
│
▼
┌──────────────┐
│ AUDITOR │
│ (review) │
└──────────────┘
│
┌─────────────┴─────────────┐
│ │
APPROVED NEEDS REVISION
│ │
▼ │
┌──────────────┐ │
│ RECOMMENDER │ │
│ (decision) │ │
└──────────────┘ │
│ │
▼ │
┌──────────────┐ │
│ TERRAFORM │◄────────────────────┘
│ CODER │ (revision loop)
└──────────────┘
│
▼
END
