Source: Agent Frameworks and Observability for AI ITSM

Sources: Anthropic: Building effective agents, LangGraph docs, Mastra agents, OpenAI Agents SDK guardrails, OpenTelemetry semantic conventions

What It Covers

This source distills current agent-framework guidance into engineering implications for Init Intelligence’s AI ITSM product.

Key Claims

  • Anthropic separates workflows from agents: workflows follow predefined code paths; agents dynamically direct their own tool usage. Anthropic advises starting simple and adding agentic complexity only when it demonstrably improves outcomes.
  • LangGraph provides stateful, long-running agent orchestration with durable execution, human-in-loop, memory, streaming, and debugging.
  • Mastra is a TypeScript agent/workflow framework: agents handle open-ended tool use; workflows define structured step control flow with schemas, branching, suspension/resumption, and streaming.
  • OpenAI Agents SDK includes guardrails for input, output, and tool calls, plus tracing for LLM generations, tool calls, handoffs, guardrails, and custom spans.
  • OpenTelemetry semantic conventions provide a common language for traces, logs, metrics, events, resources, and spans across polyglot systems.

Implications for Init Intelligence

  • The product should default to workflows for production IT actions and use agents for discovery, triage, drafting, routing, and bounded tool selection. Fully autonomous agents should be reserved for low-risk or heavily constrained actions. ^[inferred]
  • A production AI ITSM runtime should emit traces for:
    • intake,
    • model calls,
    • context retrieval,
    • policy decisions,
    • tool proposals,
    • approvals,
    • external API calls,
    • durable workflow steps,
    • human overrides,
    • final ticket/evidence updates.
  • The observability model should be customer-visible enough to support trust and auditor review, not just developer debugging.

Limitations

  • Agent frameworks move quickly; current framework APIs may change faster than ITSM buyer requirements.
  • OpenAI and LangGraph tracing defaults are not a substitute for product-owned audit trails and evidence records.