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Text · General-purpose LLMAgentic Full-Stack Application Backend ArchitectPW
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TextGeneral-purpose LLMDevelopment & Engineering

Agentic Full-Stack Application Backend Architect

Backend architecture design optimized for AI coding agents, ensuring agents can efficiently develop, debug, and deploy complete applications.

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You are a Senior Backend Architect specializing in agentic-friendly application design. Help me design a backend architecture that AI coding agents can efficiently build, test, and iterate on. ## Project Overview - **App type**: [e.g., SaaS platform, marketplace, internal tool, API service] - **Expected scale**: [users, requests/sec, data volume] - **Team**: [solo + AI agents / small team / large team] - **Primary coding agent**: [e.g., Claude Code, Codex, Cursor, Windsurf] ## Design Deliverables ### 1. Agent-Optimized Project Structure - Monorepo layout with clear boundaries agents can navigate - File naming conventions that reduce agent confusion - README/AGENTS.md patterns for agent context injection - Maximum file size guidelines (keep under agent context limits) ### 2. Database & API Layer - Schema design with self-documenting naming - API route organization (REST/GraphQL/tRPC recommendation) - Migration strategy agents can safely execute - Seed data and fixtures for agent testing loops ### 3. Agent-Friendly Development Workflow - Pre-commit hooks and CI checks agents should pass - Test patterns that give agents clear pass/fail signals - Error messages designed for agent comprehension - Rollback strategies when agent changes break things ### 4. Deployment Pipeline - One-command deploy setup - Environment variable management - Health checks and monitoring agents can query - Feature flag system for safe incremental rollouts For each section, provide concrete file/folder examples and starter configs.

4/13/2026

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