AI-native systems builder & technical operator

I build systems that run without babysitting.

I turn messy operational workflows into reliable software — across infrastructure, APIs, internal tools, data platforms, automation, and AI.

Try it yourself About me

See the work in action

Don’t take my word for it. Use the system.

Good software earns trust by making the next step obvious. Explore the live demo and see how an AI-native workflow turns a rough idea into something you can actually run.

Try it yourself

How I work

Understand → Model → Build → Operate

The correct action should be the easiest action.

Understand

Map the actual business process before writing code.

Model

Define authoritative data, workflows, failure states, and human responsibilities.

Build

Use the simplest appropriate tool: application code, automation, AI, or infrastructure.

Operate

Deploy, monitor, recover, document, and improve.

AI should assist judgment, not replace authority where mistakes are expensive.

Architecture philosophy

Practical by design.

Good systems clarify what happens next — including when something fails.

01Deterministic core, probabilistic edge.

02Business state belongs in proper software, not prompt memory.

03Use AI where reasoning adds value.

04Use automation where the workflow is deterministic.

05Humans approve consequential decisions.

06Make failures visible and recoverable.

07Keep systems boring where boring is safer.

08Do not add another SaaS tool unless it solves a real problem.

Foundation

I came to AI from production systems, not the other way around.

I’ve spent 17+ years building and operating web and infrastructure systems: hosting, Linux, cPanel / WHM / WHMCS, migrations, and hundreds of production environments. That operational history shapes how I build AI-native platforms now.

View experience

17+years building and operating systems

100swebsites and production environments

NowAI and internal-platform work, grounded in operations

Technical range

Enough range to make good trade-offs.

I work across the seams where most internal systems become difficult.

Systems

Linux, Docker, networking, hosting, monitoring, deployment

Backend

Python, FastAPI, Go, Node.js, TypeScript

Data

PostgreSQL, Redis, ClickHouse, pgvector, SQL

AI

LLM APIs, tool calling, RAG, structured outputs, agents, human-in-the-loop systems

Operations

Queues, retries, idempotency, auditability, observability, failure recovery

Integration

REST APIs, webhooks, Gmail, Google Workspace, payments, CRM, third-party SaaS