Services · Agentic SDLC
Implement Agentic SDLC for enterprise engineering teams.
We help software teams redesign how work is planned, built, tested, reviewed and deployed through human-AI collaboration.
What Is Agentic SDLC?
Humans and AI agents, collaborating across the lifecycle.
Instead of treating AI as a standalone coding assistant, Agentic SDLC introduces agents into planning, architecture, task breakdown, development, testing, review, deployment and continuous improvement.
Tools alone are not enough. Teams need a new operating model: agents assist with work, humans retain ownership, and delivery is structured through clear workflows, context, testing, approval gates and monitoring.
The Lifecycle
Eight phases. Human + agent at every one.
Click a phase to see the human role and the agent role.
Humans define goals, business context and constraints.
Agents summarize context, propose structure and ask clarifying questions.
Requirements: Human Role — Humans define goals, business context and constraints. Agent Role — Agents summarize context, propose structure and ask clarifying questions.
Planning: Human Role — Humans validate priorities and scope. Agent Role — Agents decompose work into executable tasks.
Architecture: Human Role — Architects review tradeoffs, decisions and constraints. Agent Role — Agents suggest implementation paths and approaches.
Development: Human Role — Engineers guide, review and refine every change. Agent Role — Coding agents draft changes and generate implementations.
Testing: Human Role — Humans approve critical quality decisions and validate core logic. Agent Role — Testing agents run checks, identify regressions and summarize failures.
Review: Human Role — Human reviewers approve quality and risk. Agent Role — Review agents prepare pull-request summaries and documentation.
Deployment: Human Role — Humans approve production changes where required. Agent Role — Workflows move approved changes forward with release controls.
Monitoring: Human Role — Teams iterate and improve the system over time. Agent Role — Agents analyze logs, usage and feedback signals.
Human + Agent Collaboration
Controlled collaboration. Not autonomous chaos.
Agentic SDLC does not remove human accountability. The value comes from structured collaboration through an orchestration layer.
Example
One feature through an agentic workflow.
- 01Requirement createdSYSTEM
A requirement enters Jira or another work system.
- 02Planning agent decomposes the taskAGENT
Analyzes the requirement and proposes a task breakdown.
- 03Architecture agent proposes a pathAGENT
Suggests implementation options with tradeoffs.
- 04Human lead approves the planHUMAN GATE
Reviews scope, priorities and approach before work begins.
- 05Coding agent drafts the implementationAGENT
Creates an initial implementation for engineer review.
- 06Testing agent runs checksAGENT
Runs tests and identifies issues.
- 07Review agent summarizes the PRAGENT
Prepares a pull-request summary for the reviewer.
- 08Human reviewer approvesHUMAN GATE
Approves or sends back changes.
- 09Deployment workflow runsSYSTEM
The release process moves the approved change forward.
- 10Monitoring agent tracks behaviorAGENT
Tracks post-release behavior and summarizes findings.
Why A New Operating Model