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+++ b/docs/index.rst
@@ -73,6 +73,7 @@ see detailed information about the various classes, methods, and APIs.
    :name: resources
 
    core_concepts.md
+   prompts.md
    glossary.md
    Discord <https://discord.gg/6adMQxSpJS>
 
diff --git a/docs/prompts.md b/docs/prompts.md
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+# Prompts
+
+Prompts and all the tooling around them are integral to working with language models, and therefor
+really important to get right, from both and interface and naming perspective. This is a "design doc"
+of sorts explaining how we think about prompts and the related concepts, and why the interfaces
+for working with are the way they are in LangChain
+
+## Prompt
+
+### Concept
+A prompt is the final string that gets fed into the language model.
+
+### LangChain Implementation
+In LangChain a prompt is represented as just a string.
+
+## Input Variables
+
+### Concept
+Input variables are parts of a prompt that are not known until runtime, eg could be user provided.
+
+### LangChain Implementation
+In LangChain input variables are just represented as a dictionary of key-value pairs, with the key
+being the variable name and the value being the variable value.
+
+## Examples
+
+### Concept
+Examples are basically datapoints that can be used to teach the model what to do. These can be included
+in prompts to better instruct the model on what to do.
+
+### LangChain Implementation
+In LangChain examples are represented as a dictionary of key-value pairs, with the key being the feature
+(or label) name, and the value being the feature (or label) value.
+
+## Example Selector
+
+### Concept
+If you have a large number of examples, you may need to select which ones to include in the prompt. The
+Example Selector is the class responsible for doing so.
+
+### LangChain Implementation
+
+#### BaseExampleSelector
+In LangChain there is a BaseExampleSelector that exposes the following interface
+
+```python
+class BaseExampleSelector:
+    
+    def select_examples(self, examples: List[dict], input_variables: dict):
+```
+
+#### LengthExampleSelector
+The LengthExampleSelector selects examples based on the length of the input variables. 
+This is useful when you are worried about constructing a prompt that will go over the length
+of the context window. For longer inputs, it will select fewer examples to include, while for
+shorter inputs it will select more.
+
+#### SemanticSimilarityExampleSelector
+The SemanticSimilarityExampleSelector selects examples based on which examples are most similar
+to the inputs. It does this by finding the examples with the embeddings that have the greatest 
+cosine similarity with the inputs.
+
+
+## Prompt Template
+
+### Concept
+The prompts that get fed into the language model are nearly always not hardcoded, but rather a combination
+of parts, including Examples and Input Variables. A prompt template is responsible
+for taking those parts and constructing a prompt.
+
+### LangChain Implementation
+
+#### BasePromptTemplate
+In LangChain there is a BasePromptTemplate that exposes the following interface
+
+```python
+class BasePromptTemplate:
+    
+    @property
+    def input_variables(self) -> List[str]:
+        
+    def format(self, **kwargs) -> str:
+```
+The input variables property is used to provide introspection of the PromptTemplate and know
+what inputs it expects. The format method takes in input variables and returns the prompt.
+
+#### PromptTemplate
+The PromptTemplate implementation is the most simple form of a prompt template. It consists of three parts:
+- input variables: which variables this prompt template expects
+- template: the template into which these variables will be formatted
+- template format: the format of the template (eg mustache, python f-strings, etc)
+
+For example, if I was making an application that took a user inputted concept and asked a language model
+to make a joke about that concept, I might use this specification for the PromptTemplate
+- input variables = "thing"
+- template = "Tell me a joke about {thing}"
+- template format = "f-string"
+
+#### FewShotPromptTemplate
+A FewShotPromptTemplate is a Prompt Template that includes some examples. It consists of:
+- examples: a list of examples to use
+- example prompt template: a Prompt Template responsible for taking an individual example (a dictionary) and turning it into a string to be used in the prompt.
+- example selector: an Example Selector to select which examples to use
+- prefix: the template put in the prompt before listing any examples
+- suffix: the template put in the prompt after listing any examples
+- example separator: a string separator which is used to join the prefix, the examples, and the suffix together