About
I'm Jonathan Govednik. I started SmoothSDLC to build software the way I always wished it were built, with the quality baked into the process instead of bolted on at the end.
Where this comes from
I've been around software quality and verification for as long as I can remember. It was dinner-table talk before it was my job. I spent the next two decades in high-stakes, Microsoft and Azure-centric environments: reliability, release and platform engineering, the operational end where things break and someone has to have built it so it doesn't. That work teaches you early that the cost of a problem depends on how far it traveled before you found it.
I've always leaned toward proceduralizing quality, making it a property of the system rather than an act of heroism by whoever's on call. Agents finally make that affordable to do properly, on a normal budget and a normal-sized project.
What "smooth" means to me
A serious software lifecycle has a lot of machinery in it. Most of that machinery needs to be done right and done consistently, and that doesn't take a person. When you let a system carry that load, the friction drops, and the people are freed up for the parts that need them: getting the idea and the requirements right, refining the method, and judging whether the result is good. Taking the human out of the constructed middle is what makes it smooth.
What I work with
The foundation is Azure and the Microsoft stack: infrastructure-as-code with Terraform, automation in PowerShell and Python, application work in C#/.NET, and CI/CD on GitHub Actions and Azure DevOps. The agentic system builds on that with the current tooling for governed AI work: graph-based orchestration with LangGraph, retrieval-grounded reasoning, and MCP for coordination.
Microsoft Azure Developer Associate
HashiCorp Terraform Associate
SAFe Program Consultant (SPC)
Where this is
SmoothSDLC is early and pre-revenue. I'm proving the system on a build of my own before I run anyone else's work through it, and I'm not taking on customers yet. I'd rather show the thinking and let it stand on its own. The clearest look at it is the write-up of how the agent teams work.