ai sdlc
AI in the SDLC
AI belongs at every stage of delivery — with human judgment at the gates.
We integrate AI from design through epics, stories, and tasks to agent-assisted code — with eval criteria, review standards, and governance that survive audit.
In simple terms
We show you where AI can safely help write specs, break down work, and draft code — and where a human must still approve before anything ships.
From product intent to merged code: each stage can use AI assistance, but human review stays at the gates before anything reaches production.
At implementation: human intent, agent draft, automated eval, human merge — in that order.
When to engage
- Copilot licenses purchased but design documents still written entirely by hand
- No standard for decomposing features into epics, stories, and tasks
- Agents writing code without acceptance criteria or review rubrics
- Compliance asking what AI touches in your SDLC
What we find
- AI tools bolted onto a process that was never designed for them
- Epic-to-story decomposition inconsistent across teams
- Generated code merged without eval harnesses or quality gates
What we do
- 01Map the SDLC stage by stage — where AI earns a seat, where a human must sign
- 02Define decomposition templates: design → feature → epic → story → task
- 03Build eval rubrics and review gates for agent-assisted implementation
- 04Establish governance: data classification, access tiers, audit trail
What you receive
How we measure success
We do not sell tool licenses or vendor selection decks. We integrate AI into how your team already works.
Example engagement
A platform team bought Copilot for 200 engineers but saw no cycle-time change. We added decomposition standards and an eval rubric; active adoption doubled and review rejection on agent PRs dropped within 60 days.
Bring your current epic breakdown
Share one feature decomposed from design to tasks. We will show you where AI fits — and where it does not.