"That is why we need to rethink what we need from an Agent and what an Agent really represents. Hence, we come up with the abstraction: F → Runtime: How and where the agent runs (sync, async, streaming...). E → Error: What could go wrong, defined upfront. I → Input: What the agent consumes. O → Output: What the agent produces. By separating these concerns, we get Clean, Testable and Extensible Agents"
"2. Testability: No Surprises, Easy to Test Because Agent explicitly declares inputs, outputs, and errors, writing tests becomes much simpler. You can run everything in a synchronous, side-effect-free environment (Id) for predictable tests. No need for real servers or network calls in unit tests. val testAgent: Agent[Id, String, String, Int] = Agent.make(input => if (input.isEmpty) Left("Empty Input") else Right(input.length) )assert(testAgent.process("") == Left("Empty Input"))asser"
Agents power core logic across applications. The abstraction Agent[F, E, I, O] separates runtime (F), error types (E), input (I), and output (O). Runtime becomes pluggable, allowing identical business logic to run synchronously, asynchronously, or as streams by swapping effect types like Id, IO, or Future. Explicit error typing forces upfront error definitions and simplifies handling. Declared inputs and outputs enable side-effect-free, synchronous test runs and eliminate the need for external servers in unit tests. The separation yields clean, testable, and extensible agents that can be designed once and deployed across varied runtime environments.
Read at Medium
Unable to calculate read time
Collection
[
|
...
]