SaaS Architecture
Full-stack SaaS design — multi-tenant backends, subscription billing, API gateways, and scalable cloud infrastructure built for growth.
I turn ideas into systems that print revenue
so you grow while you sleep.
Expertise
Full-stack SaaS design — multi-tenant backends, subscription billing, API gateways, and scalable cloud infrastructure built for growth.
White-label service fulfillment platforms with automated order routing, vendor management, and margin-optimized pricing engines.
High-conversion Shopify and headless storefronts with supplier sync, inventory automation, and CRO-driven funnels.
Intelligent workflow pipelines — LLM agents, RAG systems, and predictive models that eliminate manual operations and scale decision-making.
Automated bookkeeping, expense tracking, invoicing, and real-time P&L dashboards that turn financial chaos into clarity.
End-to-end operational automation — order processing, fulfillment routing, customer lifecycle, and performance analytics on autopilot.
Process
Audit systems architecture, operational bottlenecks, and revenue leaks before touching a single line of code.
Design the stack — APIs, databases, automation flows, and integration layer — optimized for scale and resilience.
Ship production-grade systems, instrument performance signals, and continuously refine through data-driven iteration.
Field Notes
solo-founder-ai / Sep 9, 2026 / 8 min read
If you run high-volume automation pipelines, your biggest recurring software expense is not hosting. It is raw API token consumption. When an autonomous pipeline triggers dozens of times per transaction to extract structured intent, normalize messy customer addresses, and confirm deliveries, frontier models like Claude 3.5 Sonnet or GPT-4o will drain your margins before you scale. The release of lightweight, sub-second inference models has turned speed and token pricing into a pure utility war.
AI Agents / Jun 21, 2026 / 7 min read
The landscape of software development is undergoing a seismic shift, driven by the relentless pace of AI innovation. What began as simple code completion tools has rapidly evolved into sophisticated AI coding agents, capable of understanding context, generating complex logic, and even autonomously fixing bugs. This isn't just about making developers faster; it's about fundamentally reshaping how software is built, tested, and deployed. At the forefront of this evolution, a new contender, OpenCod
AI Development / Jun 11, 2026 / 7 min read
For years, the tech giants have largely operated within their own walled gardens, particularly when it comes to foundational technologies like AI. Apple has its ecosystem, Google has its own, and developers often had to choose sides or build complex bridges. This week, however, saw a significant strategic pivot that signals a new era of cross-platform AI integration: Google announced it's bringing its latest Gemini models directly to Apple developers, with native support in Xcode and a new Swift