LLM Agent tools are converging on graph based workflow solutions for handling the deterministic control problems amongst the dynamic nature of generative AI
What does solving this AI Agent orchestration problem look like?
What do Tensorflow, Apache Airflow, Rule Engines, and Excel have in common?
Under the hood they all use DAGs to model data-flow dependencies of the program. Using graphs to model programs is great because you can modify the program at runtime. Lets talk about doing this in Elixir for great good.
A theoretical Salesforce API wrapper to bring higher level abstractions and functional design techniques to Salesforce.
Code samples are in Elixir, but the techniques can be applied elsewhere.
An Operation
is a datastructure that represents a set of actions that can be applied against a given Salesforce Org. The Operation
is protocol or contract which enforces that consuming datastructures can be converted into a valid Operation
against a Salesforce API. An Operation
could represent a batch or composite API request. Any valid Operation
can be converted into a raw HTTP Request that can be executed against an HTTP Client.