AI-Native SDLC with Human Gates
An agent team takes a ticket to a tested change; engineers approve the plan and merge the result, and quality gates run in between.
Everything the team needs lives in Git as code and Markdown, so agents and people read the same source. A lead agent reads the ticket through MCP, drafts a plan and waits for an engineer to approve it. Backend, test and architecture agents make the change with its tests; a review agent comments on the pull request; CI runs the quality gates; an engineer reviews and merges. Pipelines, infrastructure and alerts are generated with the code and reviewed like it.
Point at a component to light its links; select it for what it does here and the practice that makes it right.
When to use it
- A team that wants faster delivery without giving up review and sign-off
- Short hyper-sprints of a few days instead of two to four weeks
- Work tracked in Jira, discussed in Teams and designed in Figma
How NGT delivers it
Built from code, reviewed at a gate by an NGT architect, and handed over with runbooks your team can run.
AI & Agents
