docs: Consolidate experiment content for LS nav

Author: katmayb

src/docs.json

@@ -50,5 +50,5 @@ def perform_eval(run, example):
 
 ## Next steps
 
-* Analyze your experiment results in the [experiments tab](/langsmith/analyze-single-experiment)
+* Analyze your experiment results in the [experiments tab](/langsmith/work-with-experiments)
 * Compare your experiment results in the [comparison view](/langsmith/compare-experiment-results)

src/langsmith/analyze-single-experiment.mdx

@@ -78,7 +78,7 @@ Note that you should choose a feedback key that is distinct from standard feedba
 The following example uses [a prompt](https://smith.langchain.com/hub/langchain-ai/pairwise-evaluation-2) which asks the LLM to decide which is better between two AI assistant responses. It uses structured output to parse the AI's response: 0, 1, or 2.
 
 <Info>
-  In the Python example below, we are pulling [this structured prompt](https://smith.langchain.com/hub/langchain-ai/pairwise-evaluation-2) from the [LangChain Hub](/langsmith/langchain-hub) and using it with a LangChain chat model wrapper.
+  In the Python example below, we are pulling [this structured prompt](https://smith.langchain.com/hub/langchain-ai/pairwise-evaluation-2) from the [LangChain Hub](/langsmith/manage-prompts) and using it with a LangChain chat model wrapper.
 
   **Usage of LangChain is totally optional.** To illustrate this point, the TypeScript example uses the OpenAI SDK directly.
 </Info>

src/langsmith/bind-evaluator-to-dataset.mdx

@@ -122,7 +122,7 @@ Learn [how run pairwise evaluations](/langsmith/evaluate-pairwise).
 
 ## Experiment
 
-Each time we evaluate an application on a dataset, we are conducting an experiment. An experiment contains the results of running a specific version of your application on the dataset. To understand how to use the LangSmith experiment view, see [how to analyze experiment results](/langsmith/analyze-single-experiment).
+Each time we evaluate an application on a dataset, we are conducting an experiment. An experiment contains the results of running a specific version of your application on the dataset. To understand how to use the LangSmith experiment view, see [how to analyze experiment results](/langsmith/work-with-experiments).
 
 ![Experiment view](/langsmith/images/experiment-view.png)
 

src/langsmith/download-experiment-results-as-csv.mdx

@@ -40,7 +40,7 @@ The quality and development speed of AI applications depends on high-quality eva
 
 * Get started by [creating your first evaluation](/langsmith/run-evaluation-from-prompt-playground).
 * Quickly assess the performance of your application using our [off-the-shelf evaluators](https://docs.smith.langchain.com/langsmith/prebuilt-evaluators) as a starting point.
-* [Analyze results](/langsmith/analyze-single-experiment) of evaluations in the LangSmith UI and [compare results](https://docs.smith.langchain.com/langsmith/compare-experiment-results) over time.
+* [Analyze results](/langsmith/work-with-experiments) of evaluations in the LangSmith UI and [compare results](https://docs.smith.langchain.com/langsmith/compare-experiment-results) over time.
 * Easily collect [human feedback](/langsmith/annotation-queues) on your data to improve your application.
 
 ## Prompt Engineering

src/langsmith/evaluate-pairwise.mdx

@@ -121,7 +121,7 @@ In order to create and manage splits in the app, you can select some examples in
 
 ### Edit example metadata
 
-You can add metadata to your examples by clicking on an example and then clicking "Edit" on the top righthand side of the popover. From this page, you can update/delete existing metadata, or add new metadata. You may use this to store information about your examples, such as tags or version info, which you can then [group by](/langsmith/analyze-single-experiment#group-results-by-metadata) when analyzing experiment results or [filter by](/langsmith/manage-datasets-programmatically#list-examples-by-metadata) when you call `list_examples` in the SDK.
+You can add metadata to your examples by clicking on an example and then clicking "Edit" on the top righthand side of the popover. From this page, you can update/delete existing metadata, or add new metadata. You may use this to store information about your examples, such as tags or version info, which you can then [group by](/langsmith/work-with-experiments#group-results-by-metadata) when analyzing experiment results or [filter by](/langsmith/manage-datasets-programmatically#list-examples-by-metadata) when you call `list_examples` in the SDK.
 
 ![Add Metadata](/langsmith/images/add-metadata.gif)
 

src/langsmith/evaluation-overview.mdx

@@ -214,7 +214,7 @@ Similar to pushing a prompt, you can also pull a prompt as a RunnableSequence of
   </Tab>
 </Tabs>
 
-When pulling a prompt, you can also specify a specific commit hash or [commit tag](/langsmith/prompt-tags) to pull a specific version of the prompt.
+When pulling a prompt, you can also specify a specific commit hash or [commit tag](/langsmith/manage-prompts) to pull a specific version of the prompt.
 
 <Tabs>
   <Tab title="Python">