{
  "handle": "CapacityPressure",
  "mechanism": "A regularization pattern that forces abstraction by artificially constraining resources (bandwidth, memory, parameter count, or time). By creating a bottleneck where Capacity < Information, the agent is compelled to compress the signal, discarding noise and memorized details in favor of high-level concepts and generalizations. It artificially tightens the {{budget}}, forcing the agent to employ {{generalize}}, {{concept_blend}}, and {{context_compress}} to fit the signal within the bottleneck.",
  "gloss": "Forcing abstraction via resource starvation",
  "failure_modes": [
    "Collapse: {{constraint}} is too tight; signal is lost entirely (underfitting).",
    "Adversarial Encoding: {{agent}} finds a way to 'zip' noise rather than abstracting (violating the spirit of the constraint).",
    "False Abstraction: {{agent}} hallucinates simple rules that don't actually exist to satisfy the budget."
  ],
  "invariants": [
    "Bottleneck Existence: Available Capacity must be strictly less than Input Information Content",
    "Lossy Requirement: Output must be a simplified representation, effectively barring exact replication/memorization",
    "Utility Preservation: The compressed form must retain predictive power for the target task"
  ],
  "preconditions": [
    "A mechanism to enforce hard limits (e.g., context window, dimensions, token count)",
    "A stream of information or a learning task"
  ],
  "postconditions": [
    "A highly compressed, abstract representation of the input",
    "Loss of fine-grained detail/noise"
  ],
  "parameters": [
    {
      "name": "compression_ratio",
      "type": "Ratio",
      "range": "[0.0, 1.0]",
      "description": "Target resource utilization ratio that triggers forced abstraction"
    },
    {
      "name": "resource_type",
      "type": "Enum",
      "range": "{Compute, Memory, Attention, Budget}",
      "description": "Type of resource being constrained (compute, memory, bandwidth)"
    }
  ],
  "_meta": {
    "tier": 2,
    "ring": 1,
    "supersedes": [
      "sema:CapacityPressure#mh:SHA-256:739d57e4af53954f0cb6f880e87d85c784fea7e82643376e72777bbcd42f0d85",
      "sema:CapacityPressure#mh:SHA-256:f2895976075f2668f9459f278cee5e477da0fde0571b98bc00e8fca8d54a90f8",
      "sema:CapacityPressure#mh:SHA-256:ddfe060f9e631802ed2f7bfa256168f4f32d590f509de7afa36e1f84e8f56e07"
    ],
    "path": [
      "Mind",
      "Strategy"
    ]
  },
  "sema_id": "sema:CapacityPressure#mh:SHA-256:f06c432726ee48412ac4a49e9fa9ddc1a7272a298eaf984a9fef86e3fbcdf261",
  "sema_ref": "CapacityPressure#f06c",
  "sema_stub": "f06c",
  "dependencies": {
    "references": {
      "agent": "sema:Agent#mh:SHA-256:e127459069739fffc96a71d54ef6e8c97ca53471d5349c16aa72a092a33756cd",
      "budget": "sema:Budget#mh:SHA-256:4e3e536c9ecec8c1b0af017cfd0a26ba00e9f96047de4a690bf9d3db7f3720ef",
      "concept_blend": "sema:ConceptBlend#mh:SHA-256:4e1a8d331a266c5ff283faba9b1c0d65c943dfa3b0f96f4b7deb5a76f9a171c6",
      "constraint": "sema:Constraint#mh:SHA-256:70136d525260a10eedf156aad1fe6c50510eadb10a89d063c7a85575b15708fc",
      "context_compress": "sema:ContextCompress#mh:SHA-256:0bf5ce89d0ad9cac74bb69f253f06331989714d3c34bb0b385f9674439ce30b0",
      "generalize": "sema:Generalize#mh:SHA-256:29f133fe83dfe2cd7d2b432390f59e3a64a84866b964a2ca6199f8134ba64e7e"
    }
  },
  "sema_layer": "Mind",
  "sema_category": "Strategy",
  "used_by": {}
}