I build web and mobile products from idea to production: interfaces, backend systems, databases, cloud deployments, automations, and AI integrations that hold together beyond the demo.
Surface
Web apps · Mobile apps
Core
Frontend · Backend · Cloud
Edge
AI · Automation · Realtime
Selected outcomes
Independent product · Web + AI
An end-to-end product build spanning the application experience, authentication, AI workflow, saved validations, analytics, and deployment.
Built and shipped the application end to end, connecting idea input to an AI-assisted assessment and a saved validation plan.
See the evidence and scope ↗The useful part is not just knowing several stacks. It is knowing how the pieces should meet: UI, state, APIs, data, infrastructure, and the workflows people actually use.
Product interfaces, dashboards, portals, marketplaces, admin tools, auth flows, and data-heavy user experiences.
Flutter, iOS, Android, offline-first flows, realtime features, app-store-minded builds, and product iteration after launch.
Application APIs, database models, integrations, permissions, background jobs, payments, and the logic that keeps the product coherent.
Hosting, containers, CI/CD, environment design, observability basics, and the infrastructure decisions that keep releases boring.
AI-assisted workflows, RAG/search, tool calling, voice or call flows when needed, and internal automation that saves real operator time.
Operational dashboards, workflow apps, CRM-style tooling, reporting surfaces, and systems that replace messy spreadsheets or manual handoffs.
I am comfortable moving quickly with AI-assisted workflows, but the work does not stop at generated screens. The production questions still matter: where the state lives, how data changes, what breaks under load, how releases happen, and who can maintain it later.
AI can generate screens quickly. The product still needs the right boundaries, data model, auth shape, deployment plan, and failure handling.
The goal is not a polished demo that falls apart. It is an app that stays understandable and maintainable when hundreds or thousands of users show up.
I use modern AI workflows where they help, then review, structure, test, and ship the code with engineering judgment still in charge.
A good build has a rhythm. We keep the first version focused, avoid architecture theater, and make every technical decision serve the product.
01
We define the core workflow, user roles, must-have screens, risky integrations, and what the first usable version should actually prove.
02
I map the frontend, backend, data model, auth, infrastructure, and third-party services so the build has a clean technical spine.
03
I ship the interface, API, database, integrations, and deployment path in tight loops, keeping the product testable as it grows.
04
We test real flows, fix edge cases, tune performance, document the important pieces, and make the release something you can rely on.
04 / Engagements
I am a fit when you need someone who can own the product build end to end, or step into a messy app and make the technical path clearer.
Launch an MVPA focused product workflow, the application and backend it needs, and a usable release. We agree the first milestone before development starts.
Improve or rescue an appStart with the code and the failing user journey. Get a prioritized repair plan, then implement the agreed fixes.
Add an AI workflowConnect a specific task to your product and data, with a review step or human fallback where the workflow needs one.
Review the technical directionBring the product brief or existing system. Get a written assessment of the main risks, open questions, and recommended next steps.
05 / Start
A few lines are enough: what the product should do, who it is for, what already exists, and where you feel stuck. I will reply with questions or a proposed next step. Scope, fees, and milestones are agreed before paid work starts.
New builds · production fixes · app rescue