I Build What Actually Works.

Cross-platform apps that handle real usage

• →Native-quality iOS and Android apps from a shared codebase, with proper state management and navigation
• →Offline-first architecture that handles sync conflicts, partial updates, and network failures gracefully
• →Payment flows, authentication, push notifications, and production deployment with real error tracking
• →Focus on edge cases users actually hit, not just happy-path demos

Fast frontends that work with backend constraints

• →Server-side rendering, static generation, and edge deployment that balance performance with complexity
• →Component architecture, state management, and API integration shaped by actual backend limitations
• →SEO, performance tuning, and observability in production environments with real users
• →Build systems that adapt to changing requirements without full rewrites

Deploy and scale based on actual usage

• →Edge functions and CDN strategies chosen based on cost, latency, and traffic patterns
• →RESTful APIs, webhooks, and third-party integrations that handle failures and retries properly
• →CI/CD pipelines, automated testing, and error tracking that catch issues before users do
• →Make infrastructure decisions based on what the system actually needs, not what is trendy

Interfaces that communicate clearly

• →Design tokens and component patterns that scale across teams and features
• →Responsive layouts, accessibility basics, and interactions that feel intentional
• →Design-to-code workflows that maintain consistency without slowing down iteration
• →Focus on clarity and usability over visual novelty

From problem to shipped outcome

• →Translate vague business goals into concrete technical decisions and system architecture
• →Make informed tradeoffs between shipping fast, maintaining quality, and preserving long-term flexibility
• →Own features end to end, from initial scoping through production deployment and monitoring
• →Ship working solutions under real constraints instead of waiting for perfect requirements

Practical AI for real workflows

• →OCR pipelines that extract structured data from receipts, invoices, and unstructured documents
• →LLM-powered workflows that reduce manual operations and improve response times
• →Integrate AI into existing production systems, not standalone demos or prototypes
• →Balance accuracy, cost, and reliability based on actual usage patterns and business value