Laws of systems that oppose leftism/liberalism

 When you enlarge government, add taxes, and pile on regulations, you multiply failure modes, hidden couplings, and costs—the very pathologies Murphy’s Laws, Systemantics, and Augustine’s Laws warn about [1][2][3].

From Systemantics (John Gall):

• Gall’s Law: Complex systems that work evolve from simpler systems that worked; complex systems designed top‑down rarely work as intended. Big, sudden government build‑outs and sweeping regulatory schemes invite failure at scale [1][2][3].
• Systems develop goals of their own. Large bureaucracies drift toward self‑preservation, budget maximization, and process over outcomes—so expansions tend to feed the machine, not the mission [1][2][3].
• The bigger the system, the more it surprises you. Interventions in complex social/economic systems produce unanticipated side effects that are often worse than the initial problem; more rules increase the surface area for breakdowns and perverse incentives [1][2][3].
• A system produces new problems faster than it solves old ones. Regulatory accretion begets compliance burdens, workarounds, and enforcement choke points that generate demand for even more layers—runaway complexity [1][2][3].

From Murphy’s Laws:

• Anything that can go wrong, will—especially when you add moving parts. Every new program, tax rule, or regulation is another point of failure, another loophole, and another enforcement dependency that can misfire at the worst time [1][2][3].
• Nature sides with the hidden flaw. The costly edge cases you didn’t design for become the ones that dominate outcomes once the policy is live at scale—raising costs and inviting gaming or capture [1][2][3].
• If there are several ways to go wrong, the most damaging one tends to manifest. Grand, centralized fixes create single points of catastrophic failure; decentralized, simpler approaches localize mistakes and limit blast radius [1][2][3].

From Augustine’s Laws (Norman Augustine):

• Cost and complexity rise nonlinearly with added requirements. The last increments of performance or coverage (the “make it do everything for everyone” impulse) drive disproportionate cost, delay, and fragility—classic overruns in big public programs [1][2][3].
• Management layers multiply problems, not solutions. Adding bureaucratic tiers to “ensure control” slows decisions, clouds accountability, and makes failure systematic rather than local [1][2][3].
• Schedules slip linearly; costs grow exponentially. Ambitious multi‑agency initiatives with evolving mandates almost guarantee deadline misses and budget blowouts—tax hikes chase overruns rather than buy results [1][2][3].
• The optimum committee has no members. Policy made by large committees trends toward diluted goals, contradictory constraints, and compliance thickets—regulations that are hard to follow and harder to enforce [1][2][3].

Practical implications (consistent with these laws):

• Prefer simple, evolvable policies with tight feedback loops over sprawling, one‑shot “comprehensive” solutions; start small, test, iterate, then scale only what works [1][2][3].
• Sunset and simplify: pair any new rule with an automatic review/expiry and retire two old ones to keep net complexity in check [1][2][3].
• Decentralize where possible to avoid single points of failure and allow localized learning; complexity belongs at the edges, not in the core [1][2][3].

Net effect: these “laws” don’t argue left vs. right so much as small, simple, testable vs. big, complex, brittle. When you push size, taxes, and regulation upward, you move into the terrain where Murphy strikes, systems go feral, and Augustine’s curves get ugly [1][2][3].

Sources

1 Augustine's Laws by Norman R. Augustine

2 Systemantics by John Gall (not systematics)

3 Murphy's Laws by Arthur Bloch

In addition:

Here’s a deeper cut, still framed by Systemantics (Gall), Murphy’s Laws, and Augustine’s Laws, focusing on why bigger government, higher taxes, and more regulation tend to amplify failure modes and costs. [1][2][3]

Systemantics (how large systems go sideways):

• Gall’s Law: complex systems that work evolve from simpler systems that worked; top‑down “big bang” expansions of government/regulation usually underperform because they skip the evolutionary learning phase. [1][2][3]
• Bureaucratic goal drift: once created, agencies optimize for survival, budget growth, and procedural compliance over mission outcomes, so expansions mostly feed the apparatus rather than the original objective. [1][2][3]
• Unintended coupling: every added program, tax rule, or regulation creates new interdependencies; the bigger the system, the more “surprises” and perverse incentives emerge that policy designers did not anticipate. [1][2][3]
• Problem proliferation: large systems generate new problems faster than they resolve old ones, so regulatory accretion tends to require still more layers of oversight, waivers, exemptions, and enforcement—runaway complexity. [1][2][3]

Murphy’s Laws (why complexity bites at the worst time):

• Anything that can go wrong will—especially when you add moving parts; each new requirement introduces a point of failure, a loophole, or a dependency that can misfire at scale. [1][2][3]
• Nature sides with the hidden flaw; rare edge cases dominate outcomes once deployed nationwide, turning “corner cases” into cost drivers and litigation magnets. [1][2][3]
• Of all the ways to fail, systems tend toward the most damaging one; centralized, uniform rules create common‑mode failures that propagate everywhere instead of staying local and containable. [1][2][3]

Augustine’s Laws (cost, schedule, and management pathologies):

• Costs rise nonlinearly with added requirements; the last increments of coverage/precision often cost more than the first 90%, so “do everything for everyone” designs become budget traps that invite tax hikes without proportional results. [1][2][3]
• Schedules slip linearly while costs grow exponentially; sprawling multi‑agency initiatives with moving mandates almost guarantee deadline misses and overruns. [1][2][3]
• Management layers multiply problems, not solutions; added oversight tiers slow decisions, diffuse accountability, and convert local errors into systemic failures. [1][2][3]
• The optimum committee has no members; policy built by large committees accumulates contradictory constraints, yielding rules that are hard to follow and harder to enforce. [1][2][3]

Policy “smell tests” consistent with these laws:

• If success requires instant nationwide rollout, heavy cross‑agency coordination, bespoke IT, and new data pipelines, expect slippage, rework, and capture—start smaller or don’t start. [1][2][3]
• If the rulebook grows faster than the problem shrinks, you’re feeding the system rather than fixing the issue—freeze growth and prune. [1][2][3]
• If compliance depends on everyone behaving “as intended,” assume gaming and design for adversarial use from day one. [1][2][3]
• If accountability is shared by many, it effectively belongs to no one—assign a single owner with kill‑switch authority. [1][2][3]

Design patterns that oppose bloat while honoring these laws:

• Start simple and evolve: pilot narrowly, measure, iterate, scale only what actually works in the wild. [1][2][3]
• Sunset and simplify: pair any new rule with automatic expiry/review and retire at least one old rule to keep net complexity bounded. [1][2][3]
• Decentralize and modularize: push discretion to the edges to localize failures and learning; avoid single points of catastrophic failure in tax/regulatory systems. [1][2][3]
• Budget hard caps with staged gates: release funds only after verifiable outcomes at each stage; no blank checks for scope creep. [1][2][3]
• Keep rules few, clear, and testable: write for unambiguous enforcement and easy compliance; prefer bright‑line thresholds over multi‑factor mazes. [1][2][3]
• Build sandboxes: time‑limited waivers and controlled trials to learn with small blast radius before imposing system‑wide mandates. [1][2][3]

Empirical predictions you can check:

• As program/regulatory complexity rises, enforcement lag and backlogs grow superlinearly, while measurable outcomes plateau—oversight memos multiply faster than deliverables. [1][2][3]
• Centralized, complex tax/regulatory changes generate more workarounds and litigation than revenue or compliance improvements after an initial honeymoon period. [1][2][3]
• Each added coordination layer lengthens decision cycles and widens cost variance, making overruns more likely than not. [1][2][3]

When large action is unavoidable:

• Use minimum viable scope, independent red‑teaming, staged rollouts, and precommitted off‑ramps; complexity belongs at the edges where it can fail safely, not in the core where it fails catastrophically. [1][2][3]

Bottom line: Bigger government, higher taxes, and more regulation push systems into the zone where Murphy strikes hardest, Systemantics predicts drift and blowback, and Augustine’s curves make costs explode—so bias for small, simple, evolvable, and strictly accountable interventions. [1][2][3]

Sources

1 Augustine's Laws by Norman R. Augustine

2 Systemantics by John Gall (not systematics)

3 Murphy's Laws by Arthur Bloch