Organizations have started using AI to write code at a speed unthinkable one year ago, yet the processes around the code haven't changed at the same pace.
The software development lifecycle (SDLC) is the process that takes software from idea to production. Most organizations run some version of the same six stages, covering planning, design, building, testing, deploying, and maintaining software.
The shifts
The table below highlights the ends of the spectrum between traditional SDLC and AI-native SDLC, supported by Claude. Most organizations sit somewhere between the two columns.
| Stage | Traditional SDLC | AI-native SDLC |
|---|---|---|
| Plan | Requirements gathered by committee, distilled through workshops and sign-offs, written up by hand | Claude synthesizes pain points straight from the sources and captures them within intent.md, which is human readable and machine actionable |
| Design | Spec written by analysts, parsed by designers | Requirements and design compressed into one working session with an agent, guided by standards encoded as skills, versioned in Git |
| Build | Tests and code are handwritten, and documentation is written after the main development happens | Tests and code are generated by AI, and institutional knowledge is maintained as versioned machine-readable CLAUDE.md files and skills |
| Test | QA gates at stage boundaries | Continuous evals woven through implementation |
| Deploy | Humans review every line of code, and governance occurs in review cycles, often inconsistently | Layers of agentic review with human review reserved for regulated and critical code. Governance is enforced as the AI acts, with hooks as approval gates |
| Maintain | Humans watch production for bugs | Agents monitor live deployments. Any breached control band is diagnosed and written back into the loop as a new intent.md |
Humans remain accountable for every decision that requires judgment.
How the plays work
The plays are the core of the playbook and are grouped into six non-linear stages (Plan, Design, Build, Test, Deploy, Maintain), which together cover the complete lifecycle.
Each play covers:
- What changes
- Getting started
- Concrete steps for implementation
- Governance considerations
- How you measure whether it worked
Each play names its dependencies under "Prerequisites," which the dependency graph further illustrates.
The play dependency graph. Plays in the top row have no prerequisites; a solid arrow points to the plays that build on it, a dotted arrow means it helps but is not required.
Pick your first play
The plays are modular, and organizations may choose to prioritize transforming different stages at different times based on their unique needs.
The six plays in the top row of the graph above have no prerequisites:
- Plan: Capture as intent.md
- Build: Claude Code plan mode as the default starting point
- Build: The CLAUDE.md
- Build: Skills as institutional knowledge
- Test: Give Claude a feedback loop
- Deploy: Hooks as approval gates