Service
Agentic Engineering
Agentic Engineering helps a software team move from manual-first development or ad hoc AI coding to a repeatable, agent-assisted workflow. Living specifications, coding agents, automated tests, security checks and human review are combined and applied to your tools and a real delivery increment, so the team learns the method on work that ships.
Scope agreed per engagement
Who it is for
- Engineering leaders who want a disciplined way to adopt coding agents across delivery
- Teams that work mostly by hand today, or use AI coding tools inconsistently
- Organizations building any kind of software: the product itself does not need to contain AI
What is included
- Workflow assessment
- Identify tasks suited to agents, the risks and bottlenecks, and the responsibilities that stay human-led.
- Spec-Driven Development
- Connect requirements, architecture decisions, acceptance criteria, implementation and tests through living specifications.
- Agent-ready repositories
- Project context, instructions, reusable skills, tool permissions and contribution rules that agents can follow.
- Quality and release gates
- Automated testing, security checks, code review, CI/CD and explicit human release approval.
- Hands-on adoption
- Apply the approach to a real feature, coach the team, and measure cycle time, rework, defects and review effort.
What you get
- A documented, repeatable workflow your team uses on real delivery work
- Repositories that agents can work in safely, with permissions and rules in version control
- A measured baseline for cycle time, rework, defects and review effort, so gains are shown rather than assumed
Scope
Agentic Engineering improves how a team builds software. Designing and delivering an AI agent as the product is Agentic AI. The engagement goes beyond a standalone training workshop: the method is applied to your own repository and delivery work.
Frequently asked questions
What does a first engagement look like?
One team, one repository and one real delivery increment. Baseline, scope, acceptance criteria and duration are agreed before work starts.
Is this the same as AI-DLC?
AWS describes the AI-Driven Development Lifecycle (AI-DLC) as a methodology spanning inception, construction and operations with human oversight. It can be used as a reference inside an engagement; the service itself is tool- and vendor-neutral.
Do coding agents replace developers?
No. The aim is better delegation, verification and delivery discipline. Humans keep architecture, acceptance and release decisions.
Interested in Agentic Engineering?
Start a conversation about your context, or take the free 5-minute AI maturity snapshot first.