Capabilities
Two things, really: a governed agentic delivery system I'm building, and the platform engineering background it's built on. Here's what each one covers.
Agentic delivery, under governance
The agentic system is a set of capabilities, not a single product. Which ones come into play depends on the objective and its stakes.
Requirements and gap analysis
Pulling apart what's being asked for and finding the holes before anything gets built — the contradictions, the missing cases, the assumptions nobody wrote down. This is the part that saves projects, and it's where I spend most of my attention.
Quality as code
Acceptance criteria, security constraints, and review standards written as checks the work has to pass. The same rules that gate the work produce the record of it, so verification happens continuously instead of in a scramble at the end.
Agentic execution
Specialized agents doing the construction inside those rules — coordinated when the work is complex, kept simple when it isn't. Gap analysis, code analysis, BDD, and TDD run as the work proceeds, not after.
Human-in-the-loop and accountability
The system handles what it can and stops when it can't — escalating for a decision, or for review when its own checks disagree. A person stays accountable for what ships. Review happens at the level of the test plan and the method, not every line.
Audit trail and lineage
A record of which decision was made where, which check it satisfied, and how the result traces back to the requirement that asked for it. Built for work that has to answer to a regulator later.
Platform and delivery engineering
The discipline behind the agentic system comes from two decades of this — Microsoft and Azure-centric, automation-first.
CI/CD pipelines
Build, test, and deployment automation on GitHub Actions or Azure DevOps, with quality gates that mean something and a rollback path that's been tested.
Infrastructure as Code
Terraform for Azure — reusable modules, remote state, environment patterns, and a plan that shows no surprises on a re-run.
Azure automation
PowerShell and Python for the operational work — resource management, cost and compliance checks, scheduled maintenance — written to be idempotent and to fail loudly when something's wrong.
Observability
Logging, metrics, and alerting that tell you what's actually happening in production, with dashboards and queries built around the things worth watching.
DevSecOps guardrails
Policy-as-code and controls-as-code — security scanning, infrastructure checks, and secret-leak prevention wired into the pipeline so misconfigurations don't reach production.
A note on availability
SmoothSDLC is pre-revenue and I'm not taking on customers yet — the agentic system is still being proven on a build of my own. This page describes what the practice covers, not a menu to order from. If you want the detail on how the agentic side works, it's written up here.