• LOGIC
  • DATA
  • TRENDS
  • HUMAN

How to debug LLM prompt errors with your AI

Connect Datadog AI to your agent to inspect the raw data behind every failed request. You'll stop guessing why prompts fail and start seeing the actual trace payloads.

Ask AI about this page

Short answer

How do I find why my LLM prompt is failing?

Your agent uses Datadog trace data to pull specific spans and payloads related to your LLM calls. This lets you pinpoint the exact moment a prompt logic error occurs. You'll see the specific inputs and outputs that caused the issue.

Debug outcomes

Where your debug data lands.

The AI organizes the trace information into these specific outcomes.

LOGIC

Prompt failure points

The agent identifies the specific span where the prompt logic diverged from your intent. You get a clear view of the broken instruction.

DATA

Payload inspection

The AI pulls the raw trace payloads from Datadog. You can see exactly what the model received versus what you expected.

TRENDS

Error patterns

The agent groups similar trace failures together. This helps you see if a prompt error is a one-off or a systemic issue.

HUMAN

Manual fixes

The AI flags spans that require you to manually rewrite the prompt template. You decide how to patch the logic in your code.

The workflow

What your AI does when a prompt fails.

Instead of digging through dashboards, you just ask your agent to find the problem.

  1. Locate traces

    The agent looks for specific LLM execution spans within your Datadog traces.

    search_llm_spans

  2. Extract payloads

    The agent pulls the specific input and output data from the identified spans.

    search_llm_spans

  3. Analyze logic

    The agent compares the prompt sent to the model against the resulting error or unexpected output.

    search_llm_spans

  4. Summarize errors

    The agent presents a concise breakdown of why the prompt failed to meet your requirements.

    search_llm_spans

Try it

Copy these to start.

Use these prompts to begin your debugging session.

Starting points

These are starting points. Swap out the specific service names or error types to match your actual Datadog environment.

Datadog Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_bWdhwHEHDioKsLvhV1Lvv7ec4t2gm8k5cIgCZeWx/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Datadog capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "datadog-ai-llm-observability-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_bWdhwHEHDioKsLvhV1Lvv7ec4t2gm8k5cIgCZeWx/mcp"
    }
  }
}
Copy into chat04

  • Find the last five LLM spans in Datadog where the prompt resulted in a validation error.

  • Search Datadog traces for any LLM spans in the 'production-api' service that had a high latency.

  • Show me the payload for the LLM span that failed during the user authentication flow.

  • Look through the recent LLM spans and tell me if there is a pattern in why the 'summarize_text' prompt is failing.

  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Start here

Connect Datadog AI once, then ask.

Just link your Datadog account. Your credentials stay encrypted, and you can immediately start asking your agent about your traces.

Connect Datadog AI to your AI

FAQ

How this task behaves.

  • 01

    Can the AI fix my prompt in Datadog?

    No. The AI can only read the traces and tell you what went wrong. You have to update your prompt logic in your own codebase.

  • 02

    Does the AI delete any traces?

    No. The AI only has read access to your LLM spans through the search tool. It cannot modify or delete your Datadog data.

  • 03

    Can I search for specific error messages?

    Yes. You can ask the agent to find spans that contain specific error strings or status codes found in your traces.

  • 04

    Does this work with any LLM provider?

    It works with any LLM provider as long as you are sending those traces to Datadog for observability.

  • 05

    Can the AI create new Datadog monitors?

    No. The current tools only allow the agent to search and inspect existing LLM spans.

  • More questions about Datadog AI? See everything the Datadog AI Connector can do

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