Update docs/platforms/javascript/common/tracing/span-metrics/examples.mdx

Co-authored-by: Alex Krawiec <[email protected]>

Author: codyde

docs/platforms/javascript/common/tracing/span-metrics/examples.mdx

@@ -549,7 +549,7 @@ app.get('/api/search', async (req: Request, res: Response) => {
 
 Example Repository: [Customer Service Bot](https://github.com/getsentry/llm-manual-agent-monitoring-example)
 
-**Challenge:** You're building a custom AI agent that uses a proprietary LLM API (not OpenAI/Anthropic), performs multi-step reasoning with tool calls, and needs comprehensive monitoring to track token usage, tool performance, and agent effectiveness across the entire conversation flow.
+**The Challenge:** You're building a custom AI agent that uses a proprietary LLM API (not OpenAI/Anthropic), performs multi-step reasoning with tool calls, and needs comprehensive monitoring to track token usage, tool performance, and agent effectiveness across the entire conversation flow.
 
 **Solution:** Manually instrument each component of the AI pipeline using Sentry's AI agent span conventions. Create spans for agent invocation, LLM calls, tool executions, and handoffs between agents, with rich attributes for monitoring costs, performance, and business metrics.