architecture section done

architecture.md

@@ -1,14 +1,67 @@
 # Elements
+These are the main elements of this system. 
 ![Architecture Elements](./assets/Architecture_elements.png "Architecture Elements")
 
-talk through the pieces
+## Workflow 
+This is a [Temporal Workflow](https://docs.temporal.io/workflows) - a durable straightforward description of the process to be executed. For our example see [agent_goal_workflow.py](./workflows/agent_goal_workflow.py).
+Temporal is used to make the process scalable, durable, reliable, secure, and visible.
+
+### Workflow Responsibilities:
+- Orchestrates interactive loop
+- Prompts LLM, Users
+- Keeps record of all interactions ([Signals, Queries, Updates](https://docs.temporal.io/develop/python/message-passing))
+- Executes LLM durably
+- Executes Tools durably
+- Handles failures gracefully
+- Human, LLM and tool interaction history stored for debugging and analysis
+
+## Activities
+These are [Temporal Activities](https://docs.temporal.io/activities). Defined as simple functions, they are auto-retried async/event driven behind the scenes. Activities durably execute Tools and the LLM. See [a sample activity](./activities/tool_activities.py).
+
+## Tools 
+Tools define the capabilities of the system. They are simple Python functions (could be in any language).
+They are executed by Temporal Activities. They are “just code” - can connect to any API or system. They also are where the "hard" business logic is: you can validate and retry actions using code you write.
+Failures are handled gracefully by Temporal.
+
+Activities + Tools turn the probabalistic input from the user and LLM into deterministic action.
+
+## Prompts
+Prompts are where the instructions to the LLM & users is. Prompts are made up of initial instructions, goal instructions, and tool instructions. 
+See [agent prompts](./prompts/agent_prompt_generators.py) and [goal & tool prompts](./tools/goal_registry.py). 
+
+This is where you can add probabalistic business logic, to control process flow, describe what to do, and give instruction and validation for the LLM.
+
+## LLM
+Probabalistic execution: it will _probably_ do what you tell it to do.
+Turns the guidance from the prompts (see [agent prompts](./prompts/agent_prompt_generators.py) and [goal prompts](./tools/goal_registry.py)) into 
+You have a choice of providers - see [setup](./setup.md). 
+The LLM:
+- Validates user input for tools
+- Drives toward goal selected by user
+- Decides when to execute tools
+- Formats input and interprets output for tools
+- is executed by Temporal Activities
+    - API failures and logical failures are handled transparently
+
+## Interaction
+Interaction is managed with Temporal Signals and Queries. These are durably stored in Workflow History. 
+Can be used for analysis and debugging. It's all “just code” so it's easy to add new Signals and Queries. 
+Input can be very dynamic, just needs to be serializable.
+
+The workflow executes in a loop: gathering input, validating input, executing tools, managing prompts, and then waiting for input.
+
+![Interaction Loop](./assets/interaction_loop.png)
+
+Here's a more detailed example for gathering parameters for tools:
+
+![Tool Gathering](./assets/argument_gathering_cycle.png)
 
 # Architecture Model
+Now that we have the pieces and what they do, here is a more complete diagram of how the pieces work together: 
+
+
 ![Architecture](./assets/ai_agent_architecture_model.png "Architecture Model")
 
-explain elements
-
-tools do determinism
 
 # Adding features
-link to how to LLM interactions/how to change
+Want to add more tools, See [adding goals and tools](./adding-goals-and-tools.md).