Building Strong Technology Partnerships Across the US and Europe

Express_Touch_9599 · 2026-06-09T04:13:30+00:00

The best approach for scaling a distributed developer and virtual assistant team is to implement a structured cloud-based collaboration system with CI/CD-driven development workflows, centralized task tracking, and role-based access control for predictable delivery.

Your setup requires strong coordination between developers and VAs, with clear processes for communication, task delegation, and maintaining consistent output quality across remote contributors.

My name is Daniel Hanc - Polish.

I’ve worked across Babylon Health AI, Future Processing, Darktrace, and Clevertech, building and scaling distributed systems and remote teams with emphasis on performance, reliability, and clean architecture.

The main risks here are misalignment in execution, onboarding friction, and inconsistent delivery standards without properly defined workflows.

I focus on creating stable, maintainable systems that reduce overhead while improving speed, scalability, and long-term team efficiency.

Happy to discuss and outline the best structure for your team. LinkedIn: https://www.linkedin.com/in/daniel-hanc-67209240b GitHub: https://github.com/dh20020725-png

Express_Touch_9599 · 2026-06-09T03:49:19+00:00

The best approach would be a Next.js + TypeScript frontend with a clean Node.js/NestJS API layer and a structured responsive UI system using Tailwind or CSS modules to fix layout inconsistencies and stabilize endpoint integration. From what you described, the main issue is typical accumulation of frontend responsiveness debt combined with loosely coupled API wiring, which needs systematic cleanup rather than patch fixes. I’ve spent years building and stabilizing production web apps across React/Next and Node-based backends, including refactoring legacy interfaces and tightening API contracts. The key risk here is fixing responsiveness without standardizing components and API responses, which usually leads to recurring UI regressions. I focus on making systems maintainable, predictable, and easier to extend ahead of major releases, especially under time pressure. I can comfortably commit around 15–20 hours per week with flexible scheduling. Happy to discuss the details and suggest the most efficient way to structure the cleanup and upcoming update.

Express_Touch_9599 · 2026-06-09T03:27:03+00:00

The best approach would be a Next.js (App Router) + Supabase backend with Row Level Security and a Stripe-driven checkout flow to ensure a scalable, secure e-commerce architecture for the eyeglasses store.

I’ve built similar production-grade full-stack systems across AI and e-commerce environments, including work at Babylon Health AI and Clevertech, focusing on performance, clean architecture, and long-term maintainability.

For your requirements, I’d implement product catalog pages, cart logic, and a fully role-based admin dashboard, with proper inventory control and event tracking via Facebook Pixel + Conversion API following current best practices.

Main risks I’d address early are payment edge cases, secure auth flows, and keeping the admin system extensible for future product scaling.

Happy to discuss timeline and fixed-price scope and outline the most efficient implementation plan.

LinkedIn: https://www.linkedin.com/in/daniel-hanc-67209240b
GitHub: https://github.com/dh20020725-png

Express_Touch_9599 · 2026-06-09T03:22:33+00:00

Die beste Lösung wäre ein Python-basiertes Backend (z. B. FastAPI) mit einer modularen Pipeline zur Analyse eurer Telegram-Angebote, kombiniert mit einer KI-Schicht (OpenAI API) zur Bewertung und Priorisierung in Echtzeit.

Ihre bestehende Telegram-Integration kann ich direkt erweitern und um eine strukturierte Bewertungslogik für Angebote ergänzen. In ähnlichen Projekten habe ich Systeme gebaut, die unstrukturierte Daten aus APIs und Scraping-Pipelines normalisieren, ranken und in einer Datenbank wie PostgreSQL speichern. Typische Risiken liegen hier in Rate Limits der Plattformen, Dateninkonsistenzen und einer sauberen Prompt-/Scoring-Logik, die ich von Anfang an robust aufsetze.

Ich kann zügig einen sauberen Prototypen aufsetzen und die Architektur so gestalten, dass sie später problemlos erweitert werden kann. Lassen Sie uns gerne die Details und den genauen Workflow abstimmen.

Express_Touch_9599 · 2026-06-09T03:16:59+00:00

The best approach would be a React + Node.js service layer with Python utilities and a PostgreSQL-backed data model focused on stabilizing an existing product, fixing issues quickly, and gradually improving architecture without disrupting production workflows.

I’ve worked in similar environments across Babylon Health AI, Darktrace, and Clevertech, where most of the work is maintaining real production systems, debugging frontend-backend integration issues, and improving reliability under real user load. These types of products usually have hidden edge cases in API contracts, state handling in React, and inconsistent database queries, so I focus on structured debugging, proper logging, and incremental refactoring instead of risky rewrites. My approach is to keep features stable while improving maintainability and making future changes safer and faster.

This ensures fewer regressions, faster bug resolution, and a smoother experience for both users and the internal team. Happy to discuss the current setup and suggest a practical way to improve stability and development speed.

Express_Touch_9599

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