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LLM Observability for Agent Fleets

LLM observability means you can see what ran, what it cost, whether it finished, and why it failed—plus model token usage for BYOK fleets.

LLM observability is the difference between a demo that "looked good in the room" and a company that can answer:

  • What ran?
  • What did it cost?
  • Did it finish?
  • Why did it fail?

Without those answers you are not operating agents. You are hoping.

The four-field minimum

For every production agent run:

  1. What ran — agent, tools, model
  2. What it cost — tokens / time
  3. Whether it finished — success, partial, fail
  4. Why it failed — trace, not a shrug

Market language also includes agent tracing and ai agent observability. Same job: accountable fleets.

Token usage is cost observability

When founders say "cost spiked," they usually mean model tokens, not the VM line.

You need fleet rollups (session vs week), breakdowns by provider/model/harness/VM, and a per-agent panel. Spreadsheets after a scare are not monitoring.

On jurniti the token usage meter is advisory and BYOK-native—keys stay yours; jurniti does not resell tokens. Dashboard, CLI, MCP: Token usage docs.

Plugin-class lenses

Treat quality traces as a plugin-class concern next to the product agent—not a sticky note per project. Attach the lens to the fleet; do not rebuild monitoring every time you hire a new persona.

Full OS, not only traces

Observability is one pillar of an AI-native company: fleets, memory, channels, plugins. The free course paces all five.

Get the free AI-native company course

Host shape

Traces without isolation still leave shared blast radius. Managed microVMs with BYOK and always-on shape keep observability meaningful. No free trial; 30-day money-back on first purchase.

Enroll in the 7-day course

Frequently asked questions

What is llm observability?
A practical building block of an AI-native company operating system—how you run agents that create value with ownership, isolation, and cost honesty—not a chat widget alone.
How does this relate to building an AI-native company?
Fleets, observability, memory, channels, and plugins are the OS. This topic is one pillar; the free 7-day course walks all five and soft-introduces managed microVM hosts.
What is the free AI-native company course?
A 7-day email series on fleets, observability (including token usage), memory, communication, and plugins—with optional soft jurniti CTA and no free trial of compute.
Does jurniti charge for model tokens?
No. jurniti is BYOK: you bring keys. Token usage is an advisory meter for spend transparency, not a token resale or free tier.
Is there a free trial?
No free trial or free tier. The email course is free. First paid purchase has a 30-day money-back guarantee.
Where do I start?
Read this post, then enroll in the AI-native company course for a paced OS checklist that CTAs from every cluster post.