Agentic SDLC Rollout

The engagement

The operating layer on top of the context layer — the systems that let a team run coding agents at scale without losing control. MCP and tool integrations, an eval and regression suite, CI validation, permissions and approval gates, multi-agent workflows, observability, and the team training and workflow redesign that makes it stick. This is how an engineering org redesigns its SDLC around agents.

What this engagement covers

• MCP + tool integrations

• Evals + regression tests

• CI validation

• Permissions + approval gates

• Multi-agent workflows

• Observability

• Team training + workflow redesign

What you actually get

• MCP servers + tool integrations

• Eval harness + regression suite

• CI validation gates

• Approval + permission gates

• Multi-agent workflow design

• Observability + run history

• Team training

• Runbook

Who buys this

• Teams scaling agents past a single repo or engineer

• Engineering orgs redesigning the SDLC around agents

• Platform teams that need agents observable and gated

Common questions