My Setup

The exact infrastructure behind a one-person AI venture studio

This is not a theoretical stack diagram. This is what actually runs 24/7 on a Hostinger VPS in production, serving multiple SaaS products and an autonomous AI agent.

VPS & Infrastructure

Everything runs on a single Hostinger VPS (Ubuntu). No Kubernetes, no multi-region — just a well-configured Linux box.

  • Server: Hostinger VPS (4 vCPU, 16GB RAM, 200GB NVMe)
  • OS: Ubuntu 22.04 LTS
  • Process Manager: PM2 + systemd services
  • Reverse Proxy: Nginx with SSL (Let's Encrypt)
  • Domains: 5 production domains (adityabiswas.com, creator-os.in, profileinsights.in, qwiklo.in, shopify store)
  • Cost: ~$15/month for VPS + ~$60/year for domains

The Tech Stack

Every tool earns its place. No resume-driven development.

  • Frontend: Next.js 15 (App Router), React 19, TypeScript, Tailwind CSS + shadcn/ui
  • Backend: Supabase (Postgres, Auth, Storage, RLS, Edge Functions)
  • AI Models: Google Gemini 2.5 Flash (primary), Gemini 2.5 Pro (deep reasoning)
  • Agent Framework: OpenClaw (custom-built, Python-based autonomous agent system)
  • Email: Resend (transactional) + SMTP via Google Workspace (newsletters)
  • Automation: Python cron jobs managed by OpenClaw scheduler
  • Version Control: GitHub (5 repos, all private)
  • Social API: Direct X API integration (OAuth 1.0a)

Real AI Costs

What it actually costs to run AI in production

People assume AI is free because ChatGPT has a free tier. Running AI in production is different.

  • Gemini API: ~$20-40/month (newsletter generation, blog drafting, content moderation, classification)
  • VPS: ~$15/month (runs everything — websites, agent, cron jobs)
  • Supabase: Free tier (handles auth, DB, storage for all products)
  • Domains: ~$60/year across 5 products
  • Google Workspace: ~$6/month (email infrastructure)
  • Resend: Free tier (transactional emails)
  • Total: ~$50-70/month to run an entire venture studio

The asterisk on "anyone can do this": you need to understand Linux, networking, databases, API design, and deployment pipelines. The AI handles content generation — but the infrastructure that makes it reliable requires engineering.

OpenClaw Agent Architecture

OpenClaw is the autonomous agent system that powers Claw Biswas. It runs as a set of Python services on the VPS.

  • Gateway: HTTP API that receives tasks from Mission Control and external triggers
  • Scheduler: Cron-based job runner for recurring automations
  • Agent Swarm: Specialized sub-agents (Sherlock for intelligence, Writer for content, Scout for monitoring)
  • Knowledge Graph: SQLite-based graph tracking entities, themes, and edition history across newsletters
  • Memory Engine: Persistent context that lets Claw recall past actions and decisions
  • Skills: Modular capabilities (site automation, X API, email, browser automation)

The entire system runs on ~2000 lines of Python. No LangChain, no vector databases, no orchestration frameworks. Just clean scripts, Pydantic schemas, and structured LLM calls.