I isolate architectural decisions by building real systems that share APIs, data, and constraints. The work sits where AI-assisted development meets production behavior.
After 30+ years building software, I use public systems to study what changes when specifications, implementation, validation, and evolution stay connected.
Spec-driven development is the foundation. Adaptive System Life Cycle Development (ASLCD) is the complete operating model.
These systems are built to expose the trade-offs behind AI workflows, frontend architecture, documentation, and lifecycle governance.
Spec, build, validate, evolve
DevSpark is an implementation of Adaptive System Life Cycle Development (ASLCD), a full lifecycle model for building software with AI collaborators. It carries intent from specification through implementation, validation, and evolution.
Operational prompt workflows for real applications
PromptSpark.Chat explores how prompt systems behave when they become part of an application workflow. It focuses on structured conversations, reusable prompt assets, and practical integration patterns.
Documentation that becomes implementation context
DocSpecSpark frames documentation as a working system asset instead of a static afterthought. It supports the bridge from architectural intent to implementation-ready specifications.
A controlled frontend architecture comparison
TailwindSpark is a React and Tailwind implementation that consumes shared service patterns while emphasizing composition and utility-first design. Its value is clearest when compared with BootstrapSpark against the same architectural constraints.
TailwindSpark, BootstrapSpark, PromptSpark, and supporting services make architecture visible by holding some constraints constant and changing others. The point is not to crown a framework; it is to see how complexity moves.
The shared service layer connects WebSpark, PromptSpark, GitHub Repository Spark, and markhazleton.com content. That connection turns portfolio work into a living architecture study.
Explore the ArchitectureA curated entry point into AI in application development, architecture trade-offs, spec-driven development, and observability.
From EDS mainframes to AI coding agents—introducing the Adaptive System Lifecycle Development Toolkit that bridges rigorous enterprise methodology with modern AI-assisted development. Learn how to balance structure with innovation, maintain quality without rigidity, and make your project constitution valuable throughout the entire development lifecycle.
An exploration of why I built DevSpark — driven by the personal struggle of keeping existing codebases aligned with architectural standards long after the initial specification phase.
Creating git-spark, my first npm package, from frustration to published tool. Learn Git analytics limits and the value of honest metrics.
I am Mark Hazleton, a Technical Solutions Architect focused on practical system design, .NET and Azure architecture, and AI-assisted development that remains grounded in measurable behavior.