I build real-world application systems that integrate AI using structured, repeatable approaches.
My focus is not on demos or isolated features—it's on:
- Spec-driven development over prompt-driven experimentation
- Systems that scale, not just code that works
- AI as workflow, not novelty
Most examples online show:
- Static data
- Isolated frontends
- Simplified workflows
I build systems that:
- Consume real APIs
- Support multiple frontend architectures
- Demonstrate trade-offs in production scenarios
🔹 DevSpark
Spec-driven software development system for building structured, AI-assisted applications.
Utility-first UI system focused on flexibility and rapid iteration.
Component-driven UI system focused on consistency and predictability.
Both TailwindSpark and BootstrapSpark implement the same features and consume the same backend services—demonstrating how UI architecture impacts real-world application development.
Conversational application system using AI-driven workflows and real-time streaming.
Exploring documentation as executable specification—part of a broader spec-driven ecosystem.
- Closing the Loop: Automating Feedback with Suggest-Improvement
- Designing the DevSpark CLI UX: Commands vs Prompts
- The Alias Layer: Masking Complexity in Agent Invocations
- Dave's Top Ten: Git Stats You Should Never Track
- Dogfooding DevSpark: Building the Plane While Flying It
- Workflows as First-Class Artifacts: Defining Operations for AI
- Observability in AI Workflows: Exposing the Black Box
- Autonomy Guardrails: Bounding Agent Action Safely
