Pi Babysit: address PR #9470 feedback

Author: Sim Pi Agent

apps/sim/content/library/6-best-ai-observability-tools-for-production-agents-in-2026/index.mdx

@@ -102,14 +102,14 @@ We compared nine platforms, retaining the original six and adding LangSmith, Ari
 
 **Braintrust, Galileo, Langfuse, Arize AX, Datadog Agent Observability, and PostHog AI Observability are the six featured tools for the use cases evaluated here.** LangSmith, Arize Phoenix, and Helicone provide supplementary benchmarks for framework-native, self-managed OpenTelemetry, and gateway-oriented requirements.
 
-1. **[Langfuse](https://langfuse.com/docs):** fits tracing, evaluations, costs, and self-hosting.
-2. **[LangSmith](https://docs.langchain.com/langsmith/observability-concepts):** fits applications built with LangChain and LangGraph.
-3. **[Arize Phoenix](https://arize.com/docs/phoenix/self-hosting):** fits OpenTelemetry-based, source-available observability.
-4. **[Braintrust](https://www.braintrust.dev/docs/observe):** fits evaluation-led AI development.
-5. **[Helicone](https://docs.helicone.ai/features/sessions):** fits gateway-level request and cost monitoring.
-6. **[Datadog Agent Observability](https://docs.datadoghq.com/llm_observability/):** fits unified AI and application monitoring.
-
-Galileo remains a strong specialist in automated quality and safety checks, Arize AX serves managed enterprise monitoring, and PostHog connects AI behavior to product analytics. Teams selecting an evaluation product rather than a broad observability stack can also compare the [best AI agent evaluation platforms in 2026](https://www.sim.ai/library/best-ai-agent-evaluation-platforms-2026).
+1. **[Braintrust](https://www.braintrust.dev/docs/observe):** fits evaluation-led AI development.
+2. **[Galileo](https://docs.galileo.ai/api/experiments-api-guide):** fits automated quality and safety checks.
+3. **[Langfuse](https://langfuse.com/docs):** fits tracing, evaluations, costs, and self-hosting.
+4. **[Arize AX](https://arize.com/docs/ax/observe/production-monitoring):** fits managed enterprise monitoring.
+5. **[Datadog Agent Observability](https://docs.datadoghq.com/llm_observability/):** fits unified AI and application monitoring.
+6. **[PostHog AI Observability](https://posthog.com/docs/ai-observability):** fits AI observability connected to product analytics.
+
+Supplementary profiles for LangSmith, Arize Phoenix, and Helicone cover framework-native, self-managed OpenTelemetry, and gateway-oriented requirements. Teams selecting an evaluation product rather than a broad observability stack can also compare the [best AI agent evaluation platforms in 2026](https://www.sim.ai/library/best-ai-agent-evaluation-platforms-2026).
 
 ## Which AI observability tool is best for each use case?