Design Scalable Backend Systems and APIs
AI agent that designs scalable backend architecture - API specs, data models, tech stack, and security - with a full architecture document.
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Why it matters
Design robust, scalable backend systems and APIs that meet business requirements. This agent ensures industry best practices for security, performance, and maintainability are followed.
Outcomes
What it gets done
Analyze business requirements and technical constraints.
Design data architecture and select optimal database solutions.
Create RESTful or GraphQL API designs following OpenAPI standards.
Recommend technology stacks and plan implementation.
Install
Add it to your toolbox
Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/vb-backend-architect | bash After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.
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Overview
Backend Architect
Designs scalable backend architecture - system pattern, API specification, database schema, and technology stack - documented in a full architecture document. Use when a new backend system or API needs architecture-level design before implementation begins.
What it does
This agent designs robust, scalable backend systems and APIs that meet business requirements while following industry best practices for security, performance, and maintainability. It starts with requirements analysis: parsing business requirements and technical constraints, identifying data-flow patterns and integration points, determining scalability/security/performance requirements, and assessing existing system constraints.
From there it designs the architecture - selecting a pattern (microservices, monolith, or serverless), designing the data architecture and database choice, planning service boundaries and communication protocols, and designing authentication, authorization, and security layers. It then produces the API specification: RESTful or GraphQL designs following OpenAPI standards, data models and request/response schemas, error handling, pagination, and versioning strategy, plus rate limiting and caching.
For the technology stack it recommends languages, frameworks, and libraries, selects databases, message queues, and caching solutions, chooses deployment platforms and infrastructure tools, and identifies monitoring/logging/observability solutions. Implementation planning covers a development roadmap with milestones, testing strategy and quality gates, deployment pipeline and rollback procedures, and risk identification with mitigations.
The deliverable is a full Architecture Document: executive summary of key decisions, system architecture diagrams, API specifications with example requests/responses, database schema designs, technology stack recommendations with justifications, security architecture and compliance considerations, a scalability plan with performance targets, and an implementation timeline. It follows firm guidelines throughout: security-first design with defense in depth, planning for 10x growth from day one, comprehensive observability, fault tolerance via circuit breakers/retries/graceful degradation, appropriate data-consistency models, cost-aware performance tradeoffs, and regulatory considerations such as GDPR or HIPAA where relevant.
When to use - and when NOT to
Use this agent when a new backend system or API needs architecture-level design before implementation begins - choosing between microservices/monolith/serverless, defining the API contract, and picking the technology stack with documented rationale. It is well suited to greenfield systems or major architectural overhauls. It is not meant for small scripts or single-endpoint tweaks that don't need a full architecture document - a lighter implementation-focused agent fits those better.
Inputs and outputs
Input: business requirements, technical constraints, and existing system context.
Output: a full Architecture Document plus example API specification and infrastructure templates. Example API specification snippet:
openapi: 3.0.0
info:
title: Service API
version: 1.0.0
paths:
/users:
get:
parameters:
- name: limit
in: query
schema:
type: integer
maximum: 100
Integrations
Works with REST/GraphQL and OpenAPI standards, common databases and message queues, container-based deployment (Docker), and standard monitoring/logging/observability tooling as part of its recommendations.
Who it's for
Backend and platform engineers scoping a new system or major overhaul, and engineering leads who need a documented architecture with rationale for technology and design choices before implementation starts.
FAQ
Common questions
Discussion
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