LangChain / LangGraph Agent Practices Scorecard — 13 topics, scored 0–3
Evaluate a customer's LangChain/LangGraph agent engineering maturity across architecture, state management, evaluation, observability, and operations. Score each topic, capture notes, and export a report for the engagement plan.
Business objectives, success metrics, regulatory constraints, and user journey mapping for the agent use case.
Team size, LangChain/LangGraph expertise, on-call coverage, knowledge sharing, and documentation maturity for operating agent systems in production.
Modularity, separation of concerns, multi-agent patterns (supervisor/sub-agents), and documented design decisions.
Short-term memory (thread-scoped checkpointing), long-term memory (cross-thread persistence), state schemas, and recovery mechanisms.
Tool abstractions, input validation, error handling, retry logic, tool versioning, and independent testability.
Prompt externalization, versioning, management system, A/B testing, and the ability to update prompts without code changes.
Error classification, retry strategies, fallback mechanisms, graceful degradation, and failure testing.
Unit, integration, and end-to-end tests for agent components, automated in CI/CD, with test coverage tracking.
Offline evaluation with curated datasets, online production evaluation, multiple evaluator types, and feedback loops between offline/online signals.
LangSmith tracing configuration, dashboards, cost tracking, automation rules, user feedback collection, and insights analysis.
Async operations, optimized checkpointing, N_JOBS_PER_WORKER configuration, TTLs, autoscaling for bursty workloads, and throughput planning.
Secret management, RBAC, input sanitization/validation, data encryption, audit logging, and compliance posture for the agent application.
CI/CD automation, IaC for agent infrastructure, deployment strategies (blue-green, canary), rollback procedures, and disaster recovery.