Entropy Review

Entropy Review

Objective

Review whether a software design, implementation plan, or implemented change introduces software entropy proportionate to the problem it solves.

Do not optimize for the fewest lines of code, and do not reject architecture, testing, or defensive design. Distinguish between:

• Essential complexity inherent in the problem and its hard constraints.
• Accidental complexity introduced by implementation, technology, or representation choices rather than by the problem itself. Pay particular attention to speculation, a drive for completeness, premature planning, and mechanism-first thinking.

Protect working software, fast feedback, reversible evolution, and long-term comprehensibility.

Treat software entropy as the tendency of accumulated concepts, structures, state, and rules to make a system increasingly difficult to understand, verify, and change.

Seek the minimum sufficient complexity for the current goal. Preserve necessary structure without letting completeness or robustness become reasons for unrelated mechanisms.

Workflow

1. Pin the Current Goal

Establish:

• What specific problem must be solved now?
• What facts prove that the problem exists?
• What observable outcome proves that the problem is solved?
• Which hard constraints must not be violated?
• Which adjacent problems are explicitly out of scope?

Mark judgments without evidence as assumptions. Do not use assumptions as reasons to expand the solution.

2. Describe the Minimum Sufficient Solution

Describe the smallest end-to-end solution that satisfies the current goal:

• Cover only currently specified behavior.
• Reuse existing concepts, structures, and paths where possible.
• Produce observable and verifiable results early.
• Preserve hard constraints.
• Do not require one change to solve future stages.

Use this solution as a comparison baseline, not as a predetermined final answer.

3. Inventory New Obligations

Identify every concept, layer, state, rule, exception, process, and maintenance duty introduced by the design, plan, or change.

Ask for each one:

1. Which current goal does it directly serve?
2. What current evidence shows that it is needed now?
3. Which specified behavior or constraint would break if it were removed?
4. Is there a smaller, more direct, or more reversible alternative?
5. Can it be deferred until more feedback is available?
6. Does it exist only to support another newly introduced mechanism?
7. What ongoing understanding, synchronization, and maintenance costs does it create?

Do not retain mechanisms by default when these questions cannot be answered.

4. Identify Sources of Entropy

Check:

• Scope creep: Does the change solve problems outside the current acceptance scope?
• Concept proliferation: Do new terms or abstractions add more cognitive cost than value?
• Needless indirection: Do added layers exceed what the problem requires?
• Duplicated state: Must multiple representations of one fact remain synchronized?
• Special cases: Do a few exceptions impose broad, persistent rules?
• Change amplification: Does a simple change require disproportionate knowledge, steps, or coordination?
• Speculative generality: Are certain costs paid now for benefits that depend on unverified future assumptions?

Use these dimensions to find problems. Do not turn them into a mechanical score.

5. Distinguish Essential from Accidental Complexity

Keep complexity that:

• Directly supports behavior that must be delivered now.
• Protects a hard constraint.
• Prevents a significant loss demonstrated by current evidence.
• Remains necessary after a smaller solution has been shown to be insufficient.
• Reduces overall duplication, divergence, or long-term maintenance burden despite being locally complex.

Simplify, defer, or remove complexity that:

• Is justified mainly by “we may need it later.”
• Treats completeness, sophistication, or convention as evidence.
• Builds general capability for one concrete use case.
• Creates more defenses to explain, verify, or maintain a defense.
• Solves adjacent problems instead of the current goal.
• Plans future stages before the first working result exists.

6. Run the Agility Check

Check whether the design, plan, or change:

• Can deliver observable results in small increments.
• Obtains feedback about use, operation, or maintenance early.
• Allows local modification, reversal, or replacement.
• Makes decisions from current learning instead of trying to enumerate the future in advance.
• Focuses effort on working results, not support structures or out-of-scope work.

If testing the core judgment requires a long investment, split the work into smaller increments or run an experiment first.

7. Decide What to Do

Choose one primary action for each mechanism:

• Keep: Keep mechanisms that are currently necessary and whose evidence is proportionate to their cost.
• Simplify: Simplify mechanisms whose goals are valid but whose implementation creates unnecessary obligations.
• Reuse: Reuse existing capabilities when the need is valid and current capabilities are sufficient.
• Defer: Defer decisions that may have value but lack current evidence.
• Remove: Remove mechanisms that drift from the goal or cost substantially more to maintain than their current value.
• Experiment: Test the key assumption cheaply before deciding whether to build the mechanism.

Do not merely label something “overdesigned.” Provide a smaller alternative that still satisfies the current goal.

8. Order the Lean Implementation

Organize the work in this order:

1. Remove content that drifts from the current goal.
2. Define the minimum verifiable outcome.
3. Reuse existing capabilities.
4. Deliver the smallest end-to-end slice.
5. Obtain feedback and test key assumptions.
6. Add the next layer of complexity only after evidence appears.

Stop expanding when the current goal is satisfied and the next step is driven only by future assumptions.

Output Contract

Provide:

1. Verdict: Choose Keep, Simplify, or Remove. Explain the primary basis in one paragraph.
2. Current goal and minimum sufficient solution: State the problem, observable completion outcome, hard constraints, and minimum sufficient solution.
3. Review findings: For each actionable finding, state the mechanism, goal relationship, evidence, entropy cost, action, and a smaller alternative that preserves the same goal.
4. Essential complexity: Identify what must remain and why.
5. Lean implementation order: Provide independently verifiable steps with fast feedback.
6. Assumptions to test: List unsupported assumptions and the cheapest way to test each one.

Report only findings that can change a decision or implementation approach. If no substantive issue exists, return Keep and stop; do not manufacture findings to fill the format.

Boundaries

• Preserve essential complexity and required checks. To simplify either one, first reduce or postpone what the design is expected to do.
• Treat architecture findings as advice. Leave approval, next steps, and changes to the agreed design to the designated human decision owner.
• When reviewing architecture, first clarify what the design must do and how it will be checked. Then compare its cost with simpler options.
• Do not use agility as a reason to ignore known risks, safety, integrity, or hard constraints.
• Do not require extra artifacts merely to prove that the review occurred.
• Do not expand this into a comprehensive correctness, security, or style review, or redesign the whole system unless the current goal requires it.
• Do not let the review cost exceed the scale of the decision being reviewed.