10+ years at SAP designing enterprise systems. Now building AI tools founders can actually use.
A mix of systems I've built and systems I helped bring to life — from founding an AI-native product to shaping early-stage platforms across different domains.
SyncoPro helps product teams make structured AI decisions without losing speed. It's where my work comes together in one system: decision architecture, AI workflows, language design, and product execution. An active AI-native product build — shipping, evolving, and used as the primary test environment for every system on this site.
View case study → Read the Founder Perspective →A local service marketplace platform — designing the merchant decision layer, offer schema, and discovery mechanics that structure how businesses acquire customers and how consumers evaluate and book services.
View case study →A referral-based hiring platform — designing the trust mechanics and matching authority structures in a peer-to-peer professional referral system.
View case study →How I use AI-assisted vibe coding to turn product thinking into live demos, reusable workflows, and shared execution infrastructure — collapsing the gap between design, engineering, and product.
I build working prototypes directly from product thinking — no hand-off lag, no translation loss. What's in the design spec becomes a live, interactive demo in the same session.
I build reusable AI skills — design guides, icon systems, component references — that compress repeated work into single commands. The skill is the workflow, not the prompt.
The output isn't just demos — it's shared infrastructure that PM, design, and engineering can all run from. Faster execution, fewer meetings about what we're building.
A system I use to design how decisions actually become execution — across product workflows, organizational governance, and AI autonomy.
The three case studies below show how this plays out in real systems.
Each case starts with a breakdown in how decisions were made — unclear ownership, invisible work, or unstructured AI output — and how I turned that into systems that teams can actually execute on.
I design product structures that turn ambiguous ideas into aligned execution — from workflow logic and prioritization models to scalable decision frameworks inside complex enterprise products.
View case study →I build planning and governance systems that make cross-functional work visible, model capacity earlier, and reduce misalignment before execution begins.
View case study →I'm building reusable AI systems, decision infrastructure, and human-in-the-loop workflows that make AI outputs more structured, usable, and executable in real product contexts.
View case study →Decision Engine · Evolution Engine · Language System — three components that work as one.
From raw idea → structured plan → evolving system that improves with use.
Pre-2025 design work across enterprise, UX, visual, and product systems.
My background is in enterprise product design, but my current work focuses on building AI product systems — combining decision architecture, AI infrastructure, and rapid execution.
I'm focused on how decision architecture and vibe coding can dramatically shorten the distance between idea and working product.
Based in the San Francisco Bay Area. Available for Staff / Principal roles in AI product design, enterprise systems architecture, and AI governance design.
