Production Agent Design

Production Agent Design by Super Logic AI

Building AI agents that work in a lab is easy. Building agents that survive production without silently looping, leaking data, or blowing through context budgets is hard. Production Agent Design is a portable Agent Skill (SKILL.md) encoding the design decisions that make LLM agents reliable enough to ship- neurosymbolic architecture, explicit planning, plan-anchored checkpoints, schema-validated tools, verifier gates on irreversible actions, and eval-first golden tasks. Drops into Claude Code or any skill-aware runtime.

What it does

• Enforces a phased design workflow from initial architecture to pre-ship hardening.
• Standardizes tool design with strict schema validation, idempotency, and error recovery protocols.
• Implements multi-layer memory management policies to prevent context drift and state loss.
• Provides a rigorous pre-ship sanity checklist covering security, observability, and human-in-the-loop triggers.

Why this beats prompting it yourself

Generalized prompts lack the discipline required for production systems. This skill codifies specific engineering patterns like plan-anchored checkpoints and symbolic guardrails that move logic out of fragile prompts and into reliable code structures.

Use cases

• Designing a multi-step agentic workflow for complex CRM or ERP updates.
• Debugging agents that experience long-horizon drift or repetitive tool-calling loops.
• Hardening an autonomous agent against prompt injection and cross-tenant data leakage.
• Architecting MCP servers with efficient tool budgets and compressed context management.

Known limitations

Requires an existing development environment or agent framework to implement the suggested code-level guardrails. Does not provide the underlying hosting infrastructure.