We spend too much time cleaning up after bad inputs. The effort we expend reconciling inherent contradictions in a belief system or dataset is greater than the effort required to establish strong initial filtering.
<>This is true in code, where we write complex validation logic to fix data that should have been rejected by a simple type check. It's also true in philosophy and culture. We adopt premises—often passive ones gathered through inertia—and then build elaborate intellectual structures to justify their internal inconsistencies.
<>The architecture of belief should prioritize source integrity. Parse the stream to see if it follows the required protocol, but do not attempt to fix fundamental errors in the data itself. If a stream is fundamentally compromised, the most optimized action is termination of that stream.
<>Parse, don't validate. Stop trying to make broken things work coherently. Reject garbage at the gate.