I build systems with a function-first mindset and a strong focus on architecture.
I'm a fullstack developer focused on solving complex problems and designing systems with thoughtful architecture. I primarily work with TypeScript, React, and Next.js, building applications where performance and maintainability are equally important.
I'm particularly interested in data modeling and designing flexible, scalable systems. I enjoy breaking problems down into their core components and finding solutions that not only work, but also evolve well over time.
In my projects, I follow a function-first approach — prioritizing core functionality, domain logic, and architecture before refining the UI. This allows me to iterate faster and make more informed technical decisions.
Beyond implementation, I care about understanding why certain solutions work. I often analyze trade-offs and document technical decisions as part of my development process.
Domain logic, APIs, graph modeling, and relational/document data layers.
Node.jsExpress.jsNeo4jCypherPostgreSQLMongoDB
Cloud & Delivery
Release workflows, deployment pipelines, and environment management.
DockerAWSAzure DevOpsGitLab CI/CD
Product & Collaboration
Tooling for design collaboration, planning, documentation, and code reviews.
FigmaJiraConfluenceGitGitHubGitLab
Projects
Product ideas shaped through domain logic, architecture, and iteration.
A growing set of projects where the core focus is flexible system design, clear boundaries, and validating the model before polishing the interface.
Featured Product
Graph Hub
A visual workspace for modeling, exploring, and analyzing connected data without forcing every use case into a fixed structure. Graph Hub turns one graph model into a complete workflow: teams can define node and relationship schemas, import or edit data, investigate connections in an interactive workspace, assemble joined data views, build dashboards, and publish report snapshots. The product is designed for domains where relationships carry the real meaning, from technology architecture and operational dependencies to investigations, research datasets, supply chains, and knowledge maps. Public and private graphs, organization ownership, role-based access, MFA, audit history, bilingual navigation, guided onboarding, and realistic demo datasets make the platform useful both as an individual modeling tool and as a controlled collaborative environment.
A training intelligence system designed to capture workout data with low friction, model complex training structures, and connect daily context with long-term progress analysis. Built from a real personal need, the project combines mobile-first data entry with desktop-first exploration and analytics. Its core strength is a flexible domain model that supports blocks, single exercises, supersets, circuits, dropsets, and sets with different performance metrics, while also capturing variables such as sleep, hydration, macros, body weight, wellbeing, and supplementation. The MVP was shaped with a function-first approach, prioritizing domain logic, data modeling, and system architecture before visual refinement, resulting in a modular feature-based application built for consistent data collection, experimentation, and deeper analysis.
A typed graph query DSL for JavaScript and TypeScript that separates query authoring from database-specific execution. The library lets developers describe graph operations through a fluent API, emits a portable AST, and compiles that AST to graph backends such as Cypher for Neo4j and a Ladybug-compatible Cypher subset. The MVP also includes an in-memory executor for tests and mocks, runtime JSON schema mappers for nodes and edges, traversal support, aggregations, scoped properties for multi-tenant data isolation, and driver-neutral batching helpers for bulk operations.
Jun 2021 - Sep 20214 mos · InternshipStockholm, Sweden · Remote
Built user interfaces for applications developed for Redmind's clients, using technologies such as React Native to create modern, efficient, and intuitive experiences.