We architect systems that scale

We turn ideas into real products that actually work. In the age of AI, we orchestrate multiple agents to ship faster — without cutting corners.

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Selected Work

THINGS WE'VE SHIPPED

Real projects, real architecture decisions, real results

01

Stakimo

Tech Lead

Led the frontend and API architecture for a SaaS platform digitizing the entire commercialization process for real estate developers (promoteurs immobiliers) — property sales, buyer financing, and activity dashboards with AI automation. Built a modular Nuxt.js frontend with tRPC for end-to-end type-safe API communication, deployed on Vercel's serverless infrastructure. Designed communication with AWS Lambda functions running in VPC for heavy processing workloads. Integrated SonarQube for continuous code quality analysis and Sentry for real-time error monitoring across the platform.

Vercel serverless + AWS Lambda VPC architectureEnd-to-end type-safe API with tRPCSonarQube + Sentry quality pipeline
Nuxt.jstRPCTypeScriptVercelAWS LambdaPostgreSQLSonarQubeSentry
02

TalentYou

Fullstack Developer

Built the AI tutoring system and course generation engine for an AI-powered education platform using Python Django backend. Designed the RAG pipeline for adaptive learning recommendations with vector embeddings. Developed Django REST framework APIs consumed by a Vue.js frontend. Integrated AI models for personalized tutoring sessions and automated course content generation. The architecture supported rapid iteration that helped secure seed investment.

Django + AI architecture with RAG pipelineSSR-first with async AI worker queuesSeed investment secured
PythonDjangoVue.jsPostgreSQLAI/MLDockerREST API
03

Custyle

Lead Fullstack Architect

Architected a full-stack AI-powered e-commerce platform for custom clothing design. Built with Nuxt.js frontend and Nest.js backend, backed by PostgreSQL and deployed on AWS with ECS containers orchestrated by ASG behind an ALB. ElastiCache (Redis) handles session and product cache for sub-100ms response times. The platform features a WYSIWYG web-based image editor for clothing customization, powered by an AI agent architecture that generates design suggestions and handles automated production workflows. Low barrier-to-entry design lets users create custom products in minutes.

AWS ECS + ASG + ALB + ElastiCache architectureAI agent-driven design suggestions + WYSIWYG editorLow-barrier custom product creation in minutes
Nuxt.jsNest.jsPostgreSQLDockerAWS ECSASGElastiCacheAI Agents
Under the Hood

HOW WE BUILD

It's not about picking trendy tools — it's about knowing why each piece is there

Cloud Infrastructure

Auto-scaling ECS behind ALB, managed databases, and cache layers that don't fall over at 3 AM.

Rendering Strategies

SSR, SSG, CSR — we don't pick the coolest one, we pick the right one for your use case.

Data & Caching

Cache-aside patterns, query tuning, and multi-layer data architecture. Fast where it matters, reliable everywhere.

SEO & Performance

Pre-rendered HTML, CDN delivery, all Core Web Vitals green. Making search engines and users equally happy.

AI / RAG Pipeline

From vector search to agent orchestration — turning AI from a toy demo into a tool that actually gets work done.

Tech Stack

Frontend

Vue.jsNuxt.jsReactNext.jsAngularTypeScriptTailwind CSS

Backend

Node.jsNest.jsExpressPythonPostgreSQLMongoDBREST API

DevOps & Cloud

DockerAWSAzureCI/CDNginxLinuxGit

AI & Data

RAGVector DBLLM IntegrationAIoT
How We Work

HOW WE DELIVER

No cowboy coding — a clear process that gets the right thing built, on time

Delivery Process

From Concept to Production

Our structured delivery process combines agile sprints with waterfall milestones. We use GitHub Projects for sprint planning, automated CI/CD pipelines for continuous deployment, and structured code review gates to ensure quality at every stage.

  1. 1Discovery & Spec
  2. 2Architecture Design
  3. 3Sprint Planning
  4. 4Development & Review
  5. 5CI/CD & Testing
  6. 6Production Deploy
GitHub ProjectsLinearCI/CDDockerVercel

AI-Powered Development

Multi-Agent Orchestration

We leverage multi-agent AI systems to parallelize development workflows. Specialized agents handle code review, testing, documentation, and security scanning simultaneously — reducing delivery time by 60% while maintaining quality through automated skill configurations.

  1. 1Spec → Plan → Tasks
  2. 2Parallel Agent Dispatch
  3. 3Code + Review + Test
  4. 4Security Scan
  5. 5Auto-Deploy
Claude CodeSpec-KitGitHub ActionsESLintPlaywright

Agent-Driven Scale

One person, a fleet of agents

Forget hiring 10 developers. We use a fleet of specialized AI agents that work in parallel — a coder agent writes features, a reviewer agent catches bugs, a tester agent runs E2E flows, a security agent scans vulnerabilities, and a docs agent keeps everything up to date. All orchestrated by a single architect. The result? Enterprise-grade output at solo-operator cost. Every agent config is version-controlled, reproducible, and can be handed off to any team if you scale later.

  1. 1Define Agent Roles & Skills
  2. 2Configure Parallel Pipelines
  3. 3Orchestrate: Code → Review → Test → Scan
  4. 4Version-Control All Agent Configs
  5. 5Handoff-Ready for Future Teams
Agent OrchestratorSub-Agent RolesSkill ConfigsParallel PipelinesGit-Versioned Agents
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