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title: The AI observability race will be won on interoperability
description: Standardizing AI telemetry with OpenTelemetry's GenAI conventions lets teams compare models, providers and agents. Shared conventions describe conversation and...
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# The AI observability race will be won on interoperability

**[The New Stack](https://daily.dev/sources/newstack)** · 6 min read · 0 upvotes · 0 comments

## Summary

Standardizing AI telemetry with OpenTelemetry's GenAI conventions lets teams compare models, providers and agents. Shared conventions describe conversation and message data while letting large content be stored externally with references kept in telemetry. Splunk's Agent Observability uses OpenTelemetry and AGNTCY standards for vendor-neutral agent monitoring. The piece argues cost per outcome beats cost per token, since a cheaper model can need more retries. Tools like Observability Studio let teams validate telemetry conventions before production, and the OpenInference proposal aims to upstream instrumentation code into OpenTelemetry.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://thenewstack.io/ai-observability-through-interoperability>

## Questions this post answers

### Why should I measure cost per outcome instead of cost per token for my AI application?

Token counts only explain spend, not whether that spend produced useful work. A cheaper model can need more tokens or retries to finish a task, while a pricier model that succeeds on the first attempt can be more efficient overall. Cost per outcome, such as a completed workflow or an accurate answer meeting a quality bar, is a better business measure.

_Teams comparing model costs track these observability and evaluation debates on daily.dev._

### What do OpenTelemetry's GenAI semantic conventions actually standardize for AI telemetry?

They describe common conversation and message concepts so different AI stacks can be compared without every system storing data identically. The conventions account for the limits of representing complex data in telemetry and allow large content to be stored externally, with references retained in the telemetry itself, reducing duplicate integration work across providers.

_Developers standardizing AI instrumentation follow OpenTelemetry convention updates on daily.dev._

### How does Splunk's Agent Observability achieve vendor-neutral monitoring of AI agents?

It is built on OpenTelemetry and AGNTCY standards, which lets it correlate agent behavior with performance, quality, cost, and risk even as the underlying model, provider, or tool stack changes, instead of requiring a separate monitoring integration per vendor.

_Engineers evaluating agent observability tools compare vendor-neutral approaches on daily.dev._

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---

Tags: [#ai-agents](https://daily.dev/tags/ai-agents), [#llm](https://daily.dev/tags/llm), [#observability](https://daily.dev/tags/observability), [#opentelemetry](https://daily.dev/tags/opentelemetry), [#cncf](https://daily.dev/tags/cncf)

[View this post on daily.dev](https://daily.dev/posts/the-ai-observability-race-will-be-won-on-interoperability-bhlqq3vjj)

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