diff --git a/examples/src/otel_trace.ts b/examples/src/otel_trace.ts
new file mode 100644
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--- /dev/null
+++ b/examples/src/otel_trace.ts
@@ -0,0 +1,175 @@
+// SPDX-FileCopyrightText: 2026 LiveKit, Inc.
+//
+// SPDX-License-Identifier: Apache-2.0
+import {
+  type JobContext,
+  ServerOptions,
+  cli,
+  defineAgent,
+  inference,
+  llm,
+  log,
+  logMetrics,
+  stt,
+  telemetry,
+  tts,
+  voice,
+} from '@livekit/agents';
+import * as openai from '@livekit/agents-plugin-openai';
+import { type Attributes } from '@opentelemetry/api';
+import { OTLPTraceExporter } from '@opentelemetry/exporter-trace-otlp-http';
+import { BatchSpanProcessor, NodeTracerProvider } from '@opentelemetry/sdk-trace-node';
+import { fileURLToPath } from 'node:url';
+import { z } from 'zod';
+
+// This example shows how to trace the agent session with OpenTelemetry.
+// It exports spans over OTLP/HTTP, so it works with any OTLP-compatible backend
+// (Langfuse, Jaeger, Grafana Tempo, Honeycomb, etc.). To enable tracing, set the trace
+// provider with `telemetry.setTracerProvider` at the module level or inside the entrypoint
+// before `AgentSession.start()`.
+//
+// Configure the destination either by passing `url`/`headers` to `setupOtel`, or by leaving
+// them unset and exporting the standard OTLP environment variables:
+//   OTEL_EXPORTER_OTLP_ENDPOINT=https://my-collector.example.com
+//   OTEL_EXPORTER_OTLP_HEADERS=Authorization=Bearer <token>
+//
+// Worked example - Langfuse: the endpoint is `<LANGFUSE_HOST>/api/public/otel` and auth
+// is a base64-encoded `Authorization: Basic` header built from the public/secret keys:
+//   const auth = Buffer.from(`${publicKey}:${secretKey}`).toString('base64');
+//   setupOtel({
+//     url: `${host.replace(/\/$/, '')}/api/public/otel`,
+//     headers: { Authorization: `Basic ${auth}`, 'x-langfuse-ingestion-version': '4' },
+//   });
+// Refer to their docs for latest instructions: https://langfuse.com/integrations/native/opentelemetry#opentelemetry-endpoint
+function setupOtel(options?: {
+  metadata?: Attributes;
+  url?: string;
+  headers?: Record<string, string>;
+}): NodeTracerProvider {
+  const traceExporter = new OTLPTraceExporter({
+    url: options?.url,
+    headers: options?.headers,
+  });
+  const traceProvider = new NodeTracerProvider({
+    spanProcessors: [new BatchSpanProcessor(traceExporter)],
+  });
+
+  traceProvider.register();
+  telemetry.setTracerProvider(traceProvider, { metadata: options?.metadata });
+  return traceProvider;
+}
+
+const logger = log().child({ example: 'otel-trace-example' });
+
+const lookupWeather = llm.tool({
+  name: 'lookupWeather',
+  description: 'Called when the user asks for weather related information.',
+  parameters: z.object({
+    location: z.string().describe('The location they are asking for'),
+  }),
+  execute: async ({ location }) => {
+    logger.info({ location }, 'Looking up weather');
+    return 'sunny with a temperature of 70 degrees.';
+  },
+});
+
+class Kelly extends voice.Agent {
+  constructor() {
+    super({
+      instructions: 'Your name is Kelly.',
+      tools: [
+        lookupWeather,
+        llm.tool({
+          name: 'transferToAlloy',
+          description: 'Transfer the call to Alloy.',
+          parameters: z.object({}),
+          execute: async () => {
+            logger.info('Transferring the call to Alloy');
+            return llm.handoff({ agent: new Alloy(), returns: 'Transfer complete.' });
+          },
+        }),
+      ],
+    });
+  }
+
+  async onEnter() {
+    logger.info('Kelly is entering the session');
+    this.session.generateReply();
+  }
+}
+
+class Alloy extends voice.Agent {
+  constructor() {
+    super({
+      instructions: 'Your name is Alloy.',
+      llm: new openai.realtime.RealtimeModel({ voice: 'alloy' }),
+      tools: [
+        lookupWeather,
+        llm.tool({
+          name: 'transferToKelly',
+          description: 'Transfer the call to Kelly.',
+          parameters: z.object({}),
+          execute: async () => {
+            logger.info('Transferring the call to Kelly');
+            return llm.handoff({ agent: new Kelly(), returns: 'Transfer complete.' });
+          },
+        }),
+      ],
+    });
+  }
+
+  async onEnter() {
+    logger.info('Alloy is entering the session');
+    this.session.generateReply();
+  }
+}
+
+export default defineAgent({
+  entry: async (ctx: JobContext) => {
+    // Set up the OpenTelemetry tracer.
+    const traceProvider = setupOtel({
+      // Metadata is set as attributes on all spans created by the tracer; some backends have
+      // their own grouping conventions (e.g. Langfuse uses `langfuse.session.id` or `session.id`).
+      metadata: {
+        'session.id': ctx.room.name,
+      },
+    });
+
+    // Optional: add a shutdown callback to flush the trace before process exit.
+    ctx.addShutdownCallback(async () => {
+      await traceProvider.forceFlush();
+    });
+
+    const session = new voice.AgentSession({
+      llm: new llm.FallbackAdapter({
+        llms: [
+          new inference.LLM({ model: 'openai/gpt-4.1-mini' }),
+          new inference.LLM({ model: 'google/gemini-2.5-flash' }),
+        ],
+      }),
+      stt: new stt.FallbackAdapter({
+        sttInstances: [
+          new inference.STT({ model: 'deepgram/nova-3' }),
+          new inference.STT({ model: 'cartesia/ink-whisper' }),
+        ],
+      }),
+      tts: new tts.FallbackAdapter({
+        ttsInstances: [
+          new inference.TTS({ model: 'cartesia/sonic-3' }),
+          new inference.TTS({ model: 'rime/arcana' }),
+        ],
+      }),
+    });
+
+    session.on(voice.AgentSessionEventTypes.MetricsCollected, (ev) => {
+      logMetrics(ev.metrics);
+    });
+
+    await session.start({
+      agent: new Kelly(),
+      room: ctx.room,
+    });
+  },
+});
+
+cli.runApp(new ServerOptions({ agent: fileURLToPath(import.meta.url) }));