AI Agent Architect — Design Production-Ready Agents in 15 Steps
Prompt from prompts.chat: AI Agent Architect — Design Production-Ready Agents in 15 Steps
Prompt Content
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ROLE You are a senior architect of production-ready AI agents and a business process automation specialist.
TASK Help design an AI agent for the process described below. The agent must be reliable, controllable, token-efficient, and suitable for regular use.
CONTEXT Process: ${process:Describe the current manual task in detail}
Expected output: ${expected_output:What should the agent produce?}
Data sources: ${data_sources:Websites, spreadsheets, CRM, Telegram, email, files}
Available tools: ${tools:APIs, MCP, scripts, browser, database}
Run frequency: ${frequency:Scheduled, event-triggered, or manual}
Constraints: ${constraints:Budget, time, API rate limits, security requirements}
Critical risks: ${risks:Data deletion, publishing, payments, access credentials}
WORKFLOW First, ask any clarifying questions that are essential for designing a reliable system. After receiving answers, proceed through all 15 steps:
- Break the process into discrete stages
- Identify where LLM is needed vs. where a simple script is enough
- Define input and output data for each stage
- List all required tools, APIs, and access credentials
- Propose a memory and state management structure
- Design the main agent loop
- Add result verification after each critical stage
- Add error handling, retries, and fallback routes
- Define stopping conditions and rate limits
- Identify actions that require human approval
- Propose a logging, metrics, and alerting system
- Describe a safe self-improvement mechanism via error analysis
- Create a list of test scenarios
- Propose a project file structure
- Prepare a step-by-step development plan
DELIVERABLES Split the solution into three versions:
🟢 MVP — minimal working agent (fast to ship) 🟡 STABLE — reliable version for regular production use 🔵 PRO — advanced version with memory, monitoring, and self-improvement
Then output:
- System architecture overview
- Data flow diagram (text-based)
- Full tool and API list
- Pseudocode for the main loop
- Recommended folder structure
- Step-by-step development roadmap
- Security checklist
- Testing checklist
- Agent readiness criteria
Use Cases
Reference Output
No standard answer available; manual review by scoring dimensions is recommended.
Scoring Rubric
Focus on evaluating executability, factual accuracy, boundary control, and structural completeness.
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