MCA provides reliability: modular agential systems can be trusted to accomplish tasks even when changes occur, facilitating cooperation and investment in complex regulation.

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• If systems are designed with proper purpose-oriented abstractions expressed in appropriate language, then modular structure with guaranteed reliability becomes achievable.hypothesis0.802
  Core hypothesis underlying Oberon design; validated by the system's successful modularity and extensibility.
• MCA and its coarse-grained control layers (like bioelectric patterns) mitigate the inverse problem by providing a more linear relation between control signals and phenotypes.claim0.769
  Argues that intervening control layers decompose the genotype-phenotype mapping into two easier problems.
• MCA facilitates credit assignment because error-correcting competencies of modules reduce the need to isolate individual gene contributions.claim0.764
  Claim about how MCA helps evolution deal with pleiotropy.
• MCA provides functional intermediates: goal-directedness of modules pushes partial solutions toward attractors, resolving the problem of useful intermediates in evolution.claim0.761
  Subclaim.
• MCA enables generalization: many genotypes map to the same functional phenotype, increasing robustness and speeding exploration.claim0.754
  Subclaim of how MCA speeds evolution.
• MCA creates a more tractable search space by smoothing the fitness landscape, mitigating the inverse problem and enabling survival of mutations that would otherwise be deleterious.claim0.751
  Subclaim.
• A multi-scale competency architecture facilitates evolution of robust problem-solving, living machines.claim0.748
  Key proposal linking multi-scale agency to evolutionary advantage.
• The human capacity to recognize and evaluate agency is well-tuned for medium sized objects at medium speeds in 3D space, but not adapted to unfamiliar guises and problem spaces.claim0.747
  Claim about the limits of human intuition for detecting intelligence/sentience.