What is the Software Development Life Cycle (SDLC)?
Flexible Framework: The SDLC is a versatile framework that unites various methodologies like Agile, Scrum, and DevOps, structuring the software development process from inception to launch.
Stages of SDLC: Defined stages in the SDLC, such as planning, development, and testing, align teams, manage complexities, and mitigate delivery risks, enhancing collaboration among different stakeholders.
Standardization and Safeguarding: Even with AI's rise, the SDLC is crucial for maintaining structured processes. It helps integrate AI tools into workflows efficiently, avoiding disorder and enhancing productivity.
Who Does What: The SDLC clarifies roles, facilitates better planning, and supports testing and iteration. This helps product teams stay coordinated, minimizing waste and delivering reliably.
Seven-Step Symphony: Though each team may tailor it differently, all SDLC frameworks share key stages that guide development phases, ensuring a customized yet consistent approach to building software.
What is the SDLC?
The Software Development Life Cycle (SDLC) is a framework that helps teams structure and manage the software development process from planning to deployment. It’s not a single methodology—it’s an umbrella that includes a range of approaches like Agile, Scrum, Kanban, DevOps, Waterfall, Lean, and even newer AI-augmented models.
What these frameworks have in common is their use of defined stages—like planning, development, testing, and release—to help teams stay aligned, manage complexity, and reduce delivery risk. Whether you’re running two-week sprints or managing a long-term enterprise release, SDLC provides a shared structure that helps product managers, engineers, and stakeholders speak the same language and stay focused on outcomes.
Why the SDLC Still Matters for Product Teams
Even with AI tools automating tasks like testing, planning, and code generation, the basics haven’t changed—you still need a shared structure. The SDLC acts as a system of guardrails, helping your team integrate AI capabilities without creating chaos.
Whether you're layering in AI-driven QA, leveraging predictive analytics for prioritization, or auto-generating wireframes from text prompts, SDLC gives you the checkpoints and shared context to apply those tools strategically, not reactively.
Here’s why product teams still benefit from using SDLC principles:
- Keeps roles, priorities, and expectations clear
- Supports repeatable planning and faster estimation
- Builds in space for testing, research, and iteration
Used well, the SDLC becomes a living process—not a rigid flowchart. It helps product teams stay aligned, reduce waste, and deliver consistently—even in fast-moving, feedback-heavy environments.
The 7 Phases of the Software Development Life Cycle
The SDLC process will look a little different for every team and product. However, these are the stages that most SDLC frameworks have in common:
1. Planning & Analysis
Every product cycle starts with a few core questions: What are we building? Why now? Who’s it for? This phase is about validating that the opportunity is real, surfacing key assumptions, and aligning your team on goals before moving forward.
At this stage, you're typically:
- Gathering input from users and stakeholders using user research tools and stakeholder management software to capture, organize, and prioritize insights.
- Defining business goals, technical constraints, and success metrics to ground the effort in real outcomes.
- Prioritizing the opportunity space using frameworks like RICE or MoSCoW to weigh tradeoffs and guide early decisions.
Pro Tip: Even if you’re Agile, don’t skip this step. Planning doesn’t mean locking down scope—it means creating shared clarity so your team can adapt with intent.
2. Define Requirements
This phase converts planning insights into clear, buildable requirements. Whether you're documenting user stories, edge cases, or technical constraints, the goal is to align the team on what’s being built—and why.
Some teams still produce detailed specs like a Software Requirements Specification (SRS), Use Case documents, or a Requirements Traceability Matrix—especially in regulated or enterprise environments. Others rely on lightweight alternatives like collaborative docs, user story maps and storyboarding, or acceptance criteria in Jira or Notion. If you're working on a formal spec, this guide can help clarify what to include.
You can also speed up this phase by using AI tools to summarize interviews, generate draft requirements, or even automate publishing specs to Confluence. However you structure it, the output should be consistent, accessible, and actionable for design and engineering.
3. Design
The design phase turns product ideas into real user flows, wireframes, and technical plans. PMs, designers, and engineers should work together to map out key interactions, explore edge cases, and align on what success looks like. Wireframing tools like Figma and Balsamiq help visualize the work early, keeping everyone on the same page.
“The goal of research isn’t just to get answers—it’s to help everyone on the team understand the problem the same way.”
— Laura Klein, The CPO Club Podcast
This is also where AI can accelerate output—AI design tools can generate wireframes from text prompts or highlight usability gaps. But it’s your job as PM to ensure those outputs reflect real user needs, business priorities, and technical feasibility.
Here are a few wireframing tools worth considering:
- Figma – Most popular for cross-functional design, especially for PM/designer/dev collaboration.
- Balsamiq – Great for low-fidelity, fast wireframing and stakeholder buy-in.
- Uizard – AI-powered wireframes from text prompts; good for early ideation.
- Galileo AI – Generates UI based on product descriptions; excellent for prototyping.
- Whimsical – Lightweight for flows, diagrams, and early design thinking.
This phase bridges planning and execution—it’s the foundation your team will build on in development.
4. Development
The actual development phase is where the development team members divide the project into software modules and turn the software requirements into code that makes the product. the development phase can vary significantly based on the chosen methodology, each offering distinct approaches to integrating development and testing (more on the different methodologies later).
This SDLC phase can take quite a lot of time and specialized development tools. It’s important to have a set timeline and milestones so the software developers understand the expectations and you can keep track of the progress in this stage.
Integrating AI-powered tools like GitHub Copilot into the development phase can significantly enhance productivity by suggesting code snippets, detecting bugs, and automating routine coding tasks.
In some cases, the development stage can also merge with the testing stage where continuous integration practices are run to ensure there are no critical bugs.
5. Testing
Before a feature ships to production, it needs to be tested—not just for bugs, but for performance, usability, and alignment with user expectations. Testing can happen in staging environments, with internal teams, or in production behind feature flags. Some tests are automated; others require hands-on feedback.
The types of testing most teams run at this stage include:
- Unit testing – Verifies individual components behave as expected
- Functional testing – Ensures the software meets defined requirements
- Performance testing – Assesses speed and scalability under load
- Security testing – Identifies potential vulnerabilities
- Usability testing – Evaluates the interface and user experience
- Acceptance testing – Confirms the product works as intended for end users
Modern QA teams often use tools like Selenium, Cypress, or Playwright to automate test cases and catch issues earlier. As a PM, your job is to help review acceptance criteria, flag UX gaps, and work with engineering to triage issues quickly—especially if a bug or blocker puts the release at risk.
6. Deployment
Deployment is the moment of truth—but in modern teams, it’s less about one big launch and more about controlled, continuous delivery. Whether it’s a hotfix, a minor update, or a major release, the focus here is on stability, visibility, and rollback safety.
Most teams use CI/CD pipelines (like GitHub Actions, Bitbucket Pipelines, or CircleCI) to automate build and deployment steps. Rollouts might happen gradually using feature flags, staged environments, or region-based toggles. Tools like LaunchDarkly or ConfigCat make this process safer and more flexible.
As a PM, this is when you stay close to what’s going live. Coordinate with CX, support, and marketing teams. Track adoption. And if something misfires, help the team respond quickly and with context—not panic.
If you are creating brand-new software, you can learn more about the different stages of the software release life cycle (SRLC).
Want a deeper look at rollout planning, communication, and measuring success after launch? Check out our full guide on release management.
7. Maintenance
The maintenance phase is the final stage of the SDLC if you’re following the waterfall structure of the software development process. However, the industry is moving towards a more Agile software development approach where maintenance is only a stage for further improvement.
In the maintenance stage, users may find bugs and errors that were missed in the earlier testing phase. These bugs need to be resolved through bug triage for better user experience and retention. In some cases, these can lead to going back to the first step of the software development life cycle.
Teams use tools like Sentry (for error tracking), Datadog or New Relic (for system performance), and Mixpanel or Amplitude (for user behavior). Support tickets, NPS surveys, and in-app feedback tools like Delighted or Pendo also surface recurring UX issues that weren’t obvious in testing.
Case Study: Duolingo
Problem: Popular language-learning platform, Duolingo, is renowned for its effective use of gamification to engage users. During the maintenance phase, Duolingo's product team observed that while many users were initially enthusiastic, there was a noticeable drop in engagement after the first few lessons. This decline indicated their product was not sustaining long-term user interest.
Solution: To address this, Duolingo introduced features such as 'Streaks' to reward consecutive days of learning, 'Lingots' as a virtual currency to purchase in-app items, and 'Leaderboards' to foster a sense of community and competition among users.
Outcome: These enhancements led to a significant increase in user retention and engagement, as learners now had clear incentives and a more interactive learning experience.
As a PM, this is your chance to spot patterns: Which bugs are high-friction? What feedback is surfacing across teams? Where is user behavior drifting from expectations? Maintenance isn’t the end of the cycle—it’s the signal for what to fix, what to evolve, and what to build next.
The SDLC phases can also restart for any new features you may want to add in your next release/update.
SDLC and Security
It should come as no surprise that security is an increasing concern in the software world. Building security into a software product is a project in and of itself, so these operations are typically integrated into the software development life cycle.
How can you integrate security into the SDLC?
SDLC integrates security via DevSecOps, which is not an isolated stage but a continuous process.
DevSecOps, an extension of DevOps, incorporates security checks at every SDLC phase. Activities include code review, architecture analysis, penetration testing, and automated detection. Tools are integrated into IDEs, code repositories, and build servers.
How to Integrate DevSecOps into SDLC?
1. Planning & Requirement Analysis
- Identify security requirements.
- Select security measures to counter threats and vulnerabilities.
2. Architectural Design
- Apply security design principles.
- Conduct threat modeling, access control, encryption, and risk analysis.
3. Software Development & Testing
- Perform code reviews for standard compliance.
- Run security tests like penetration testing.
4. Deployment
- Use automated DevSecOps tools.
- Configure firewalls, access controls, and security settings.
5. Maintenance
- Continuously monitor for vulnerabilities.
- Update software with security patches.
Common SDLC Models
In software development, there are various frameworks, or “models,” of the Software Development Lifecycle (SDLC), which arrange the development process in different ways. These models help organizations implement SDLC in an organized way. Here are some of the most commonly used software life cycle models.
1. Agile Model
This model arranges the SDLC phases into several development cycles, with the team delivering small, incremental software changes in each cycle. The Agile methodology is highly efficient, and rapid development cycles help teams identify issues early on, but overreliance on customer feedback and customer-centric development could lead to excessive scope changes or project termination. It's best for software development projects that require flexibility and the ability to adapt to change over time.
2. Waterfall Model
This model arranges all the phases sequentially, with each new phase depending on the outcome of the previous one. It provides structure to project management, but there is little room for changes once a phase is complete, so it's best for small, well-defined projects.
3. Iterative Model
With this model, the team begins development with a small set of requirements and iteratively enhances versions until the software is ready for production. It's easy to manage risks, but repeated cycles could lead to scope change and underestimation of resources. This model is best for projects that require high flexibility in their requirements and have the resources to handle multiple iterations.
4. Spiral Model
This model combines the iterative model's repeated cycles with the waterfall model's linear flow to prioritize risk analysis. It's best for complex projects with frequent changes but can be expensive for smaller projects.
5. Big Bang Model
The Big Bang Model is a unique approach where developers jump right into coding without much planning. This means that requirements are implemented as they come, without any kind of clear roadmap. If changes are needed, it can require a complete revamp of the software.
While this model isn't great for larger projects, it’s best for academic or practice projects, or smaller projects with only one or two developers. Essentially, it's a model that works well when requirements aren't well understood and there's no set release date in sight.
What is the best SDLC model overall?
As you can see above, the best SDLC model is highly dependant on your organization's unique circumstances. However, the most popular model today is the Agile model. The Agile model is preferred by most organizations as it emphasizes rapid and frequent iteration, which allows software development teams to adapt product features quickly according to the most current user research findings and customer feedback.
SDLC vs Other Lifecycle Management Methodologies
As you may know, SDLC is not the only lifecycle management process in the glossary of product management terms. Here are some similar terms and what distinguishes them from the SDLC:
SDLC vs. ALM (Application Lifecycle Management)
ALM is a term that describes the creation and maintenance of software applications, from ideation to design, development, testing, production, support, and eventual retirement. Sound a lot like SDLC? They might appear similar on paper, but some key differences include:
- SDLC focuses on the development phase of an application, while ALM takes a more comprehensive approach, covering the entire lifecycle of the application.
- Multiple ALM tools, processes, and teams need to work together to manage different stages of the application, including development.
- There may be multiple SDLCs within an application's lifecycle that fall under the larger ALM framework.
SDLC vs. Systems Development Lifecycle
Sometimes, people use the term SDLC to refer to the systems development lifecycle, which is the process of planning and creating an IT system. This system typically consists of multiple hardware and software components that work together to perform complex functions.
So, what’s the difference?
- SDLC only covers the development and testing of software components
- Systems development is a broader process that encompasses the setup and management of hardware, software, people, and processes needed for a complete system.
- While SDLC focuses on the software product only, systems development can include tasks like organizational training and change management that aren't necessarily part of software development.
SDLC vs STLC (Software Testing Lifecycle)
You might have also heard about the software testing lifecycle (STLC). The STLC refers to the set of activities that ensure software quality by detecting bugs and defects before the product release. It has phases similar to the SDLC but with different objectives and deliverables.
There are several key differences between SDLC and STLC, such as:
- SDLC is focused on software development, while STLC is focused on software testing.
- SDLC aims to build a software product that meets the user requirements, while STLC aims to ensure that the software is bug-free and reliable.
- SDLC consists of various phases, such as planning, design, coding, testing, and deployment, while STLC has different phases, such as test planning, test case development, test execution, and test closure.
SDLC vs DevOps
Another buzzword in the software development industry is DevOps. DevOps is a set of practices that combines software development (Dev) and IT operations (Ops) to enable faster and more frequent software delivery. It involves collaboration, automation, and monitoring throughout the software development lifecycle.
Here are the distinctions between SDLC and DevOps:
- SDLC is a methodology for managing software development, while DevOps is a cultural shift that promotes collaboration between development and operations teams.
- SDLC focuses on delivering software that meets the user requirements, while DevOps focuses on delivering software that meets the business objectives.
- SDLC involves different phases, such as planning, design, coding, testing, and deployment, while DevOps involves continuous integration, continuous delivery, and continuous monitoring.
SDLC vs PDLC (Product Development Lifecycle)
The product development lifecycle (PDLC) is a comprehensive process that covers the entire lifecycle of a product, from ideation to retirement. It includes product planning, market research, product design, development, testing, launch, marketing, and support.
Here are some key differences between SDLC and PDLC:
- SDLC is focused on software development, while PDLC is focused on product development.
- SDLC consists of various phases, such as planning, design, coding, testing, and deployment, while PDLC includes additional phases, such as market research, product planning, and marketing.
- SDLC aims to build software that meets the user requirements, while PDLC aims to build a product that meets the market needs and generates revenue.
SDLC vs SRLC (Software Release Life Cycle)
The software requirements lifecycle (SRLC) is a process that focuses on gathering, documenting, and validating software requirements. It includes eliciting requirements from stakeholders, analyzing and prioritizing them, documenting them in a requirements specification, and validating them.
Here are some key differences between SDLC and SRLC:
- SDLC is focused on software development, while SRLC is focused on software requirements management.
- SDLC consists of various phases, such as planning, design, coding, testing, and deployment, while SRLC includes additional phases, such as requirements elicitation, analysis, and validation.
- SDLC aims to build software that meets the user requirements, while SRLC aims to ensure that the software requirements are complete, correct, and unambiguous before development starts.
What’s Next?
This is just the basics of the software development life cycle (SDLC); for more information on how to develop new products and create high-quality software, check out our roundup of the best product development books on the market.
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