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Agile vs Waterfall

Target audience: Readers choosing a project delivery method, or those who want a practical understanding of agile and waterfall
Prerequisites: Read Development Methods Basics first

Agile and waterfall are not strictly the same kind of term. Agile is an umbrella development approach based on values and principles, while waterfall is a common name for a predictive life cycle that moves through phases in sequence. This page compares them on a practical shared axis: learning through short iterations versus progressing through agreed phases according to a plan.

A Note Before Comparing Them

Agile builds working software in short cycles and improves it through feedback from users and stakeholders. The Agile Manifesto emphasizes individuals and interactions over processes and tools, working software over comprehensive documentation, customer collaboration over contract negotiation, and responding to change over following a plan.[1]

Waterfall is a predictive approach that moves through phases such as requirements, design, implementation, testing, and release. It tends to fit when requirements are relatively stable and deliverables or approval conditions can be defined for each phase.[5]

Royce’s 1970 paper is frequently cited as the origin of waterfall, but it did not simply recommend a one-way process. It also discussed feedback to earlier phases, prototyping, test planning, and other risk-reduction measures.[4] This page uses “waterfall” in its common modern sense of a predictive, phase-based life cycle.

Comparison

ViewpointAgileWaterfall
FlowBuild in short iterationsMove through phases in order
Change handlingAdjust with change as an expectationManage change through impact analysis
DeliverablesShow working software earlyProduce requirements, designs, and test artifacts by phase
Good fitChanging requirements, high uncertainty, user feedbackRelatively stable requirements, phase approvals, contractual deliverables
RiskIterations can drift without directionProblems may appear late
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Agile Basics

Agile does not try to decide everything upfront. It builds small slices, reviews them, and adjusts. For example, a two-week sprint might implement a login screen, a search feature, or part of an admin UI, then use the review to choose the next priority.

Agile principles include delivering value early and continuously, welcoming changing requirements, and delivering working software frequently.[2] Scrum is one common agile framework that defines sprints, product backlogs, reviews, retrospectives, and related artifacts.[3]

graph LR
    A["Plan"] --> B["Build"]
    B --> C["Review"]
    C --> D["Retrospective"]
    D --> A

Waterfall Basics

Waterfall makes each phase’s completion conditions explicit before moving to the next phase. Requirements define what to build, design decides how to build it, implementation creates it, and testing verifies quality.

graph TD
    A["Requirements"] --> B["Design"]
    B --> C["Implementation"]
    C --> D["Testing"]
    D --> E["Release"]
    E --> F["Maintenance"]

This approach is easy to explain when stakeholders can agree on deliverables and completion conditions in advance. The tradeoff is that mistakes found late can create large rework. Predictive life cycles can still include reviews and feedback; “waterfall” does not have to mean that a team never revisits an earlier phase.

How to Choose

In practice, many teams combine the two instead of choosing a pure version.

SituationPractical approach
New product with user feedback neededUse agile as the main method
Stable requirements and explicit contractual deliverables or phase approvalsAdd stronger waterfall-style phase control
Budget must be set early, but features need discoveryManage the overall frame by phase and implementation by iteration
AI model quality is hard to predict upfrontPut evaluation, experiments, and improvement into short cycles
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AI Service Considerations

AI services change through more than application code. Prompts, models, evaluation data, and log analysis also become part of the product. That makes it difficult to freeze quality only through a specification document; teams need to inspect real inputs, failure examples, and evaluation results.

At the same time, enterprise adoption has continuing constraints such as security, permissions, and data protection. A practical pattern is to improve screens and model behavior iteratively while defining acceptance criteria for authentication, logging, and data protection early and verifying them in every iteration.

Frequently Asked Questions

Does agile mean there is no planning or documentation?

No. The Agile Manifesto does not say planning or documentation has no value. It says working software and responding to change are valued more in the respective comparisons.[1]

Can one project use both approaches?

Yes. A project can manage its budget, external contracts, and overall approval points by phase while designing, implementing, and evaluating individual features in short iterations.

Summary

  • Agile is a development approach based on values and principles; waterfall is a common name for a predictive, phase-based life cycle
  • They can be compared on a shared axis, but they are not exact opposites or mutually exclusive choices
  • Agile tends to fit learning and change; waterfall elements tend to fit stable requirements and explicit phase approvals
  • AI service plans should include model, data, prompt, and evaluation changes

References

  1. Kent Beck et al., Manifesto for Agile Software Development, 2001
  2. Kent Beck et al., Principles behind the Agile Manifesto, 2001
  3. Scrum.org, The Scrum Guide, November 2020
  4. Winston W. Royce, Managing the Development of Large Software Systems, IEEE WESCON, 1970
  5. Douglas H. Desaulniers and Robert J. Anderson, Project Management Institute, Matching software development life cycles to the project environment, November 1, 2001
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