System, Software & Data Architecture

With the explosion of AI tools and the ability to consider larger refactorings than ever, it is critical to define what architecture is so that we can communicate and evolve it.

This definition directs focus on components solely based on our ability to change them, encourages design with evolution in mind, and provides a guideline to avoid under- or over-specifying.

People

• Teams and Agents Topology
• Product / Engineering Relationships
• Knowledge Management and Documentation

Processes

• Software Development Lifecycle
• Technical Debt Prioritization
• Architecture Decision Records
• Review and Evolution Cadence

Systems

• Engineering Principles
• System and Software Architecture
• Data Model and Pipelines
• Integration Patterns

Published Design Goals and Architecture Blueprints

Clear documentation of your system’s foundational decisions—not buried in someone’s head, but accessible to everyone who needs to build on them. Your team will know why things are built the way they are.

Roadmaps with Implementation Timelines

A practical path from where you are to where you need to be, with clear checkpoints and decision points. Not a waterfall plan, but a living roadmap that adapts as you learn.

A Process to Execute and Evolve

Architecture isn’t a one-time decision—it’s a continuous practice. I help you establish review processes, decision records, and communication patterns that keep architecture relevant as your system grows.

30 Years of Engineering Architecture

I’ve designed and built systems at every scale—from startup MVPs to consumer applications serving 80M+ monthly active users. I’ve architected network measurement features, data lake pipelines, and platform integrations that have run reliably for a decade.

Large-Scale Consumer and Enterprise Experience

At Ookla, I defined the platform architecture used to integrate 7 acquired products, including authentication, metrics ingestion (1B+ data points/day), data governance, and query APIs. I’ve built systems that balance consumer simplicity with enterprise requirements.

Hands-On Technical Depth

I’m not an ivory-tower architect. I’ve written kernel code at SGI, built OSS/BSS systems processing $100M in revenue, and authored reference methodology documentation for Speedtest. I understand the trade-offs because I’ve implemented them.

Scaling Challenges

Your system worked at smaller scale, but you’re hitting limits—performance bottlenecks, deployment complexity, or team coordination issues. You need to evolve without stopping the business.

Technical Debt Accumulated

Years of pragmatic decisions have created a system that’s hard to change. You need a plan to modernize incrementally while continuing to deliver value.

AI Integration Questions

You want to leverage AI capabilities, but you’re not sure where they fit or how to integrate them responsibly. You need architecture that enables experimentation without creating risk.

I’ve navigated all of these challenges across consumer apps, enterprise platforms, and data-intensive systems. Let’s define a project with clear goals and build the architecture your product needs.