Isn't SpecOps Just Waterfall? (Spolier alert: No)

[mheadd]

The Observation

"SpecOps seems to require documenting everything upfront before you can start building. Isn't that just waterfall methodology with a new name? We've moved past that for good reasons."

This is a fair and important concern. On the surface, SpecOps' emphasis on specifications before implementation might look like waterfall's "requirements before development" approach. But the resemblance is superficial. Here's why they're fundamentally different.

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The Critical Distinctions

1. Source of Requirements: Discovery vs. Creation

Waterfall Assumption:

• Requirements don't exist yet and must be invented
• Stakeholders must imagine and articulate everything they want
• "Tell me everything you need before we start building"
• Creates pressure to get requirements "perfect" upfront
• Assumes we can predict all needs in advance

SpecOps Reality:

• Requirements already exist—they're embedded in the legacy system
• The legacy system IS the requirement (it's what people use and depend on)
• "Let's document what this already does"
• Focus is on accurate discovery, not perfect prediction
• We're capturing what exists, not inventing what should exist

Key Difference: Waterfall asks stakeholders to be prophets. SpecOps asks domain experts to be witnesses to what already works.

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2. What "Complete" Means: Perfection vs. Working Knowledge

Waterfall Trap:

• Must define 100% of requirements before any coding
• Changes to requirements are failures
• Requirements documents must be comprehensive and final
• Fear of missing something prevents starting

SpecOps Approach:

• Begin with specifications for prioritized components (not everything)
• Specifications are living documents that evolve
• Explicitly document uncertainties and gaps
• Start modernizing components as their specifications are verified
• Learn and refine specifications through implementation

Key Difference: Waterfall demands perfection upfront. SpecOps embraces incremental understanding and iterative refinement.

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3. Timing: Sequential vs. Iterative

Waterfall Sequence:

Requirements (100%) → Design (100%) → Implementation (100%) → Testing

Everything complete before moving to next phase. No overlap. No iteration.

SpecOps Flow:

Component A: Spec → Verify → Implement → Deploy
Component B: Spec → Verify → Implement → Deploy
Component C: Spec → Verify → Implement → Deploy
(Happening in parallel and iteratively)

Plus continuous refinement:

Component A Spec v1 → Implement → Learn → Spec v2 → Refine Implementation

Key Difference: Waterfall is sequential and phase-gated. SpecOps is iterative and continuous.

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4. Scope of Initial Work: Everything vs. Valuable Slices

Waterfall:

• Document all requirements for entire system before starting
• Big bang approach—everything planned upfront
• Years of requirements gathering before first line of code
• Massive risk if requirements are wrong

SpecOps:

• Start with highest-priority component or functional area
• Generate and verify specification for that component
• Implement and deploy that component
• Learn from experience
• Move to next component
• Repeat

Example Comparison:

Waterfall Benefits System:

• Year 1: Document all requirements (eligibility, calculations, appeals, reporting, interfaces)
• Year 2: Design entire new system
• Year 3-4: Build everything
• Year 5: Test and deploy (hope you got requirements right in Year 1!)

SpecOps Benefits System:

• Month 1-3: Specification for income verification component
• Month 4-6: Implement and deploy income verification
• Month 7-9: Specification for benefit calculation component
• Month 10-12: Implement and deploy calculations
• Continue incrementally...

Key Difference: Waterfall is all-or-nothing. SpecOps is incremental value delivery.

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5. Relationship to Existing System: Abstract vs. Concrete

Waterfall Challenge:

• Requirements often written abstractly
• May not reflect how current system actually works
• Gap between documented requirements and actual system behavior
• "The requirements say X but the system does Y"

SpecOps Advantage:

• Specifications describe actual legacy system behavior
• Can test specifications against running legacy system
• Concrete, verifiable, grounded in reality
• "The specification says X and we verified the legacy system does X"

Key Difference: Waterfall requirements are aspirational. SpecOps specifications are observational (at least initially).

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6. Handling Change: Failure vs. Expected

Waterfall Philosophy:

• Changing requirements is a project failure
• "Requirements were wrong" or "stakeholders didn't know what they wanted"
• Change control processes add friction
• Changes threaten timeline and budget

SpecOps Philosophy:

• Specifications will evolve as understanding deepens
• Initial AI-generated specs are drafts, not final
• Domain expert verification improves specifications
• Implementation learnings refine specifications
• Changes are expected and managed through version control

Key Difference: Waterfall treats change as failure. SpecOps treats change as learning.

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7. Risk Profile: Back-Loaded vs. Distributed

Waterfall Risk:

• All risk concentrated at the end
• Don't know if requirements were right until testing/deployment
• Years of work before validation
• Catastrophic if fundamentally wrong
• "Big bang" integration risk

SpecOps Risk:

• Risk distributed across iterations
• Validate each component before moving to next
• Quick feedback on specification accuracy
• Small failures that inform next iteration
• Incremental deployment reduces integration risk

Key Difference: Waterfall puts all eggs in one basket. SpecOps hedges risk through iteration.

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8. Feedback Loops: Delayed vs. Immediate

Waterfall:

• Feedback on requirements comes years later during testing
• "We built what you asked for, but it's not what you needed"
• Too late to course-correct without major rework
• Stakeholders don't see working software until near the end

SpecOps:

• Feedback on specifications comes during verification (before coding)
• Feedback on implementation comes during component deployment
• Early course correction is cheap and expected
• Stakeholders see working components within months
• Can compare new implementation to legacy system immediately

Key Difference: Waterfall's feedback comes too late. SpecOps' feedback comes continuously.

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9. Relationship to Agile: Opposed vs. Compatible

Waterfall vs. Agile:

• Generally incompatible
• Waterfall's rigid phases conflict with agile iteration
• Waterfall's upfront planning contradicts agile's adaptive planning

SpecOps and Agile:

• Highly compatible
• SpecOps enables agile by making specifications lightweight and iterative
• Specifications support sprints focused on specific components
• Continuous verification fits agile feedback loops
• Strangler Fig pattern is inherently incremental

Key Difference: Waterfall opposes agile principles. SpecOps embraces them.

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What SpecOps Actually Resembles

If not waterfall, what methodology does SpecOps resemble?

Most Similar To: Specification by Example (SBE) + Strangler Fig

Specification by Example (SBE):

• Uses concrete examples to specify behavior
• Specifications evolve through conversation
• Examples are executable
• Collaborative refinement
• SpecOps adapts this for legacy systems with AI assistance

Strangler Fig Pattern:

• Incremental replacement of legacy systems
• Old and new coexist during transition
• Component-by-component modernization
• Continuous value delivery
• SpecOps provides the specification layer for Strangler Fig

Also Related To: Domain-Driven Design (DDD)

Domain-Driven Design:

• Emphasis on understanding the domain deeply
• Ubiquitous language shared by technical and domain experts
• Iterative refinement of domain understanding
• SpecOps specifications capture domain knowledge in ubiquitous language

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The "Yes, And..." Response

When someone says "SpecOps sounds like waterfall," here's the thoughtful response:

"Yes, SpecOps emphasizes specifications before implementation. AND:

• It's iterative, not sequential - We specify and implement incrementally, not all at once
• Specifications come from existing systems - We're discovering what works, not predicting the future
• We expect specifications to evolve - Refinement through learning is built into the process
• Value is delivered continuously - Not a big bang at the end
• It embraces agile principles - Short cycles, feedback loops, adaptive planning
• Risk is distributed - Each component is validated before the next begins
• It's fully compatible with Strangler Fig - The industry standard for incremental modernization

Think of it as 'specification-guided agile' not 'waterfall with AI.'"

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Why the Confusion Happens

The confusion is understandable:

Waterfall's Bad Reputation:

• We've learned that "document everything before coding" fails
• Requirements are never complete upfront
• Big design upfront leads to wasted effort
• Change is constant and must be embraced

SpecOps' Surface Similarity:

• Also emphasizes specifications
• Also wants documentation before implementation
• Could look like "requirements first" thinking

But Context Matters:

• Waterfall: Inventing requirements for systems that don't exist
• SpecOps: Documenting systems that already exist and must be preserved

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Real-World SpecOps Flow (Not Waterfall)

Month 1:

• Identify high-priority legacy component
• Generate draft specification with AI
• Begin domain expert verification

Month 2:

• Complete verification of component specification
• Start implementation while refining specification
• Identify next component to specify

Month 3:

• Deploy first component to production
• Refine specification based on implementation learnings
• Complete specification of second component
• Begin verification of third component

Month 4:

• Deploy second component
• Implement third component
• Generate specification for fourth component
• Refine earlier specifications as needed

This is clearly not waterfall.

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The Specification-First Principle Without Waterfall Problems

SpecOps maintains "specification-first" without waterfall's problems by:

1. Limiting Initial Scope:
Not "specify everything," but "specify this component before implementing this component"

2. Enabling Parallelism:
Different components at different stages simultaneously

3. Embracing Change:
Version-controlled specifications that evolve

4. Validating Continuously:
Verify specifications with experts, test implementations against legacy system

5. Delivering Incrementally:
Production deployments happen regularly, not at project end

6. Learning from Experience:
Each iteration informs the next

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Common Anti-Patterns to Avoid (That Would Make It Waterfall)

SpecOps can become waterfall-like if you:

❌ Wait to specify every component before implementing any
✅ Instead: Specify and implement incrementally

❌ Treat initial specifications as unchangeable requirements
✅ Instead: Expect and embrace specification refinement

❌ Require 100% specification completeness before starting
✅ Instead: Document uncertainties and proceed with working knowledge

❌ Do all verification before any implementation
✅ Instead: Overlap verification and implementation phases

❌ Aim for perfect specifications on first try
✅ Instead: Use implementation learnings to improve specifications

❌ Resist changes to specifications once implementation starts
✅ Instead: Manage changes through version control and proper process

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The Test: Is Your SpecOps Actually Waterfall?

Ask yourself:

If SpecOps, you can answer "yes" to most of these:

• ☑ Are we deploying components to production within 3-6 months?
• ☑ Are specifications being refined based on implementation experience?
• ☑ Can we start implementing one component while specifying another?
• ☑ Are we explicitly documenting uncertainties rather than pretending we know everything?
• ☑ Is it easy to update specifications when we learn something new?
• ☑ Are we comparing new implementations to legacy systems continuously?
• ☑ Can we change priorities and work on different components?

If waterfall, you're likely answering "no":

• ☒ Must we specify everything before implementing anything?
• ☒ Are changes to specifications treated as failures?
• ☒ Is there a "requirements phase" that must be 100% complete?
• ☒ Do we have rigid phase gates between specification and implementation?
• ☒ Are we going years without deployments?
• ☒ Can't we start implementing until all verification is done?

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Conclusion: Specifications ≠ Waterfall

The lesson from waterfall's failure wasn't "never write specifications."

It was:

• Don't try to predict everything upfront
• Embrace change and iteration
• Deliver value continuously
• Get feedback early and often
• Keep scope manageable

SpecOps follows all these lessons.

The presence of specifications doesn't make something waterfall, just like the presence of planning doesn't make something waterfall. It's about:

• How specifications are created (iteratively or all at once?)
• When they're refined (continuously or never?)
• What they enable (incremental delivery or big bang?)
• Why they exist (learning and preservation or prediction and control?)

SpecOps is specification-guided agile modernization, not waterfall rebranded.

The specifications are the tool, not the trap. They enable agility, preserve knowledge, and support incremental delivery—all things waterfall could never do.