This paper formalizes the Law of Alignment as a domain-independent structural constraint that governs the coherence, adaptability, and sustainability of complex systems. Drawing on systems theory, cybernetics, and ontological analysis, it demonstrates that systems remain viable only when accumulation is continuously balanced by release, in proportion to environmental conditions. Rather than treating contemporary instability as a collection of isolated psychological, cultural, economic, or technological crises, the paper identifies misalignment as a unifying structural condition underlying these phenomena. The same pattern recurs across biological regulation, identity formation, ecological cycles, technological architectures, institutional design, and economic systems: accumulation without proportional release generates internal pressure, perceptual distortion, inflationary compensation, and eventual corrective collapse. The analysis positions identity as a functional storage architecture subject to capacity constraints, illustrating how technologically mediated validation systems amplify identity accumulation while suppressing regulatory feedback. This dynamic results in identity inflation, performance dependence, and increased fragility at both individual and collective levels. Similar mechanisms are demonstrated in ecological saturation, institutional overaccumulation, financial inflation, and bureaucratic rigidity. Collapse is reframed not as an anomaly or failure but as a regulatory recalibration that restores proportionality when voluntary release mechanisms are deferred or suppressed. The Law of Alignment is presented as descriptive rather than prescriptive; it does not advocate for ideological, moral, or policy positions, nor does it predict specific events. Instead, it delineates the structural conditions under which systems remain coherent over time and the predictable consequences of violating those conditions. This work provides a systems-theoretic and ontological synthesis of the Law of Alignment developed in prior publications, offering a unified explanatory framework applicable across disciplines without replacing domain-specific empirical models.