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When PSL & MSD Is Overkill

When PSL & MSD Is Overkill

A clarification, not a retreat

PSL & MSD were introduced as a way to govern long-running, AI-assisted projects without losing intent, correctness, or architectural integrity.

That does not mean they should be used everywhere.

In fact, applying PSL & MSD in the wrong context is worse than not using them at all. This article exists to define those boundaries clearly — not to weaken the method, but to prevent misuse.


What PSL & MSD optimize for

Before discussing overkill, it is important to restate the objective function.

PSL & MSD optimize for:

  • long-term semantic stability
  • explicit recoverability from mistakes
  • resistance to AI-driven reinterpretation
  • auditability of decisions over time

They do not optimize for speed, novelty, or exploration.

If those are your primary goals, you are solving a different problem.


Early ideation and exploration

PSL & MSD are a poor fit for:

  • brainstorming
  • architectural exploration
  • “what if” prototyping
  • discovery-driven work

In these phases, ambiguity is not a bug — it is the point.

Locking invariants too early increases the cost of learning and encourages premature certainty. PSL & MSD deliberately resist fluid reinterpretation, which is exactly what early exploration often requires.

Use sketches, notes, throwaway code, or even unstructured AI conversations instead.


Short-lived or disposable projects

If a project is expected to:

  • live for days, not months
  • be rewritten rather than evolved
  • be abandoned without regret

…then PSL & MSD introduce unnecessary friction.

The ceremony only pays off when:

  • the cost of restarting is high, or
  • the cost of being wrong compounds over time.

Disposable work should remain disposable.


Low-stakes domains

PSL & MSD assume that mistakes matter.

If incorrect behavior:

  • is cheap to detect,
  • cheap to fix,
  • and has no downstream consequences,

then governance-first approaches are misaligned.

Examples include:

  • UI-only experiments
  • internal tooling with no external contract
  • personal scripts with no reuse expectations

In these cases, speed and convenience dominate correctness.


Multi-author teams without governance agreement

PSL & MSD implicitly assume:

  • a single authority, or
  • a clearly defined governance model.

Without that, immutability becomes contested rather than stabilizing.

In team environments, additional mechanisms are required:

  • ownership rules
  • arbitration procedures
  • merge and versioning policy

Without them, PSL & MSD can become a source of friction rather than clarity.

This is not a flaw — it is an undeclared dependency.


When restarting is cheaper than correcting

Some projects are better reset than repaired.

If:

  • errors are easy to detect,
  • history is not valuable,
  • and clean restarts are culturally acceptable,

then append-only ledgers and immutable specifications are unnecessary.

PSL & MSD exist specifically to make correction safer than restart.
If restart is already cheap, their advantage disappears.


The common misunderstanding

A frequent misreading is to treat PSL & MSD as “heavy documentation”.

They are not.

They are governance mechanisms designed to constrain evolution intentionally. When those constraints are unnecessary, they feel obstructive — correctly so.

Overkill is not a moral failing.
It is a signal of misaligned optimization.


The intended boundary

Use PSL & MSD when:

  • the project will outlive individual work sessions
  • AI is used repeatedly, not once
  • correctness is cumulative
  • you expect to discover that earlier decisions were wrong

Avoid them when:

  • exploration matters more than preservation
  • restarting is cheaper than fixing
  • ambiguity is still productive

Closing note

Every serious method is overkill somewhere.

PSL & MSD are no exception — and that is a feature, not a weakness.

They exist for projects where stability is more valuable than speed, and memory is more valuable than momentum.

Outside that boundary, simpler tools win — and should.

This post is licensed under CC BY 4.0 by the author.