Update constitution [ci fast]

Signed-off-by: Paolo Di Tommaso <paolo.ditommaso@gmail.com>

Author: pditommaso

.specify/memory/constitution.md

@@ -54,15 +54,17 @@ Testing MUST be comprehensive and multi-layered before any code is merged:
 
 ### III. Dataflow Programming Model
 
-Nextflow's core abstraction MUST adhere to the dataflow programming model:
+Nextflow's core abstraction MUST adhere to following principles and guidelines:
 
-- Workflows are defined as dataflow graphs where data flows between processes
-- Processes MUST be stateless, side-effect-free transformations that communicate via channels
-- The DSL MUST prioritize expressiveness for concurrent and parallel pipeline definition
-- Changes to the language parser (ANTLR grammars in `nf-lang`) MUST preserve backward compatibility with existing pipelines unless explicitly versioned (DSL1 vs DSL2)
-- Concurrency primitives (GPars actors/dataflow) MUST be used correctly to maintain the dataflow semantics
+- The dataflow programming model is the fundamental abstraction in the Nextflow programming model.
+- Workflows are defined as dataflow graphs where data flows between processes.
+- Processes MUST be stateless, side-effect-free transformations that communicate via channels.
+- Workflows should be defined in a platform agnostic manner to enable portability across clusters and clouds.
+- The DSL MUST prioritize expressiveness for concurrent and parallel pipeline definition.
+- Changes to the language parser (ANTLR grammars in `nf-lang`) MUST preserve backward compatibility with existing pipelines unless explicitly versioned (DSL1 vs DSL2).
+- Concurrency primitives (GPars actors/dataflow) MUST be used correctly to maintain the dataflow semantics.
 
-**Rationale**: The dataflow paradigm is Nextflow's fundamental programming model, enabling automatic parallelization and distribution. Preserving this model ensures existing scientific pipelines continue to work and users can reason about workflow behavior.
+**Rationale**: The dataflow model is Nextflow's fundamental abstraction, enabling automatic parallelization and distribution. Preserving this model ensures existing scientific pipelines continue to work and users can reason about workflow behavior.
 
 ### IV. Apache 2.0 License Compliance