Credit where it is due
AWS introduced AI-DLC, and AWS Labs publishes the open workflows. SignalsAI builds on that work but remains independent and is not affiliated with or endorsed by AWS.
What the methodology gives us
The lifecycle has five named phases: Initialization, Ideation, Inception, Construction, and Operation. SignalsAI presents the work through 33 stages so teams can see what is happening and where a decision is needed.
11 domain specialists create and review work across product, design, architecture, development, quality, security, infrastructure, delivery, and operations; two reviewers check the work, and an adaptive composer coordinates the right workflow.
What SignalsAI adds
The methodology describes what a team and its agents do at each stage. SignalsAI gives them a place to do that work together.
A shared workspace for alignment
Stakeholders, developers, and agents stay in one visible conversation with a shared record.
Private windows for execution
Focused work happens privately with the team's existing coding agent, then returns to the shared project.
Your code stays with you
Code remains in your own environment, and SignalsAI does not access it. Self-hosting is available for the SignalsAI AI-DLC application.
Conflicting artifact changes stay visible
When two people change the same artifact, SignalsAI shows the differences and asks for confirmation.
How the lifecycle shows up in SignalsAI
| Lifecycle step | What it looks like in SignalsAI |
|---|---|
| Idea | Someone brings the idea into the shared workspace. |
| Decisions | The agent asks clarifying questions, and the answers are recorded as decisions. |
| PRD | Product requirements become a shared artifact. |
| Spec | The technical specification and implementation plan become versioned shared artifacts. |
| Build with context | Approved context moves to a private window with the decisions and artifacts attached. |
| Review | The result, such as a pull request, returns to the team for review. |
| Deploy | SignalsAI hands the approved result and its decisions, specifications and build context to the customer's delivery tooling. |
| Learn | The next iteration starts from the same context. |
SignalsAI preserves and hands off the approved delivery context. Your delivery tooling and team remain responsible for deployment.
What stays attached
Project context, a summary of the conversation, tasks, artifacts, decisions, and agent activity remain connected. A team can follow the path from the original intent through the reviewed result without reconstructing it from separate tools.
Why follow a public methodology?
- The process is portable. The methodology is open and documented.
- The concepts transfer. Teams can try open workflows in a coding tool before adopting a shared workspace.
- Agents get guardrails. Stages and approval points keep execution within an agreed structure.