AI-assisted delivery · Faster, safer, documented

AI-SDLC Consultant
NZ & ANZ

Practical AI-assisted delivery for cloud and database teams: better requirements, test plans, runbooks, incident/RCA summaries, migration checklists and documentation workflows. The goal is faster delivery with clearer governance — not replacing engineering judgement.

Available immediately for contract & partner subcontracting · Auckland / Remote ANZ

Send the database problem →View case studies →

NZ-based senior specialistAuckland presence, ANZ remote delivery.

Oracle + PostgreSQL depthOCM background with AWS database focus.

Production-first deliveryAssessment, change control, rollback and runbooks.

Partner friendlyContracting, subcontracting and advisory support.

When to call me

Delivery drag

Too much manual documentation and rework

Teams lose time rewriting requirements, test notes, RCA summaries, migration checklists and runbooks by hand.

Spec-driven workflow
Reusable templates
Review checkpoints

Incident learning

RCA and runbooks are inconsistent

Production incidents happen, but lessons are not converted into repeatable playbooks quickly enough.

RCA drafting
Runbook generation
Operational handover

Cloud/database teams

AI needs practical guardrails

You want AI assistance for real delivery work while keeping human review, privacy, change control and auditability visible.

Human-in-the-loop
Governance-first
Database-aware prompts

AI-SDLC delivery focus

Requirements

From vague request to usable spec

Convert stakeholder notes into structured requirements, acceptance criteria, risks, dependencies and testable outcomes.

Spec templates
Acceptance criteria
Risk capture

Runbooks

Operational knowledge that teams can reuse

Generate and refine incident playbooks, migration checklists, validation steps and support handover documentation.

RCA support
Runbook drafts
Validation steps

Engineering flow

Faster without losing control

AI-assisted review of SQL, logs, test plans and documentation while retaining senior human judgement for production changes.

Review workflow
Testing support
Governance notes

Typical deliverables

Workflow assets

AI-SDLC playbook
Prompt templates for cloud/database teams
Runbook and RCA templates
Review and approval checkpoints

Pilot outputs

One practical use-case implemented
Before/after workflow comparison
Team enablement session
Risks and guardrails documented

Best-fit uses

Migration documentation
Incident RCA drafting
Database support runbooks
Test planning and release notes

Engagement model

Best delivered as a focused pilot with one real workflow, then expanded only after the team can see measurable value and acceptable governance.

The AI-SDLC guardrail

AI assists, engineers decide

AI can accelerate drafting, checking and structuring work, but production changes still need human review, test evidence and change control.

Start with one workflow

The safest pilot is narrow: one incident RCA path, one migration checklist, one runbook workflow or one requirements-to-test flow with measurable benefit.

Governance from day one

Prompts, outputs, review steps, privacy boundaries and approval points should be documented so the workflow can be trusted and reused by the team.