Writing

Essays on agent experience, AI systems, and leadership.

Long-form notes for builders and leaders turning emerging capability into reliable software: agent experience, evaluation, enterprise platforms, distributed systems, and the judgment behind technical decisions.

DevOps Is Moving Toward LoopOps

DevOps made shipping and operating software a continuous discipline. LoopOps is the next step: making improvement itself a first-class, measurable loop for humans and agents.

  • LoopOps
  • AI Agents
  • DevOps

Telemetry Should Close the Improvement Loop

Telemetry should not end at observability. As software teams add coding agents and agentic workflows, telemetry needs to become the evidence layer that helps products get better.

  • AI Agents
  • Telemetry
  • Product Engineering

Agent Experience Is Bigger Than Developer Experience

More tokens, more context, and more connectors do not automatically create better AI products. Agent experience borrows from user experience and developer experience, but agents need a working environment for every kind of operational task.

  • Agent Experience
  • AI Agents
  • Product Engineering

What Senior AI Engineers Actually Own

The senior part of AI engineering is not knowing every model release. It is owning the product, system, risk, and organizational judgment that turns model capability into durable software.

  • AI Engineering
  • Leadership
  • Product Judgment

A Practical Operating Model for Enterprise AI Agents

Enterprise agents need more than tools and prompts. They need ownership, evaluation, permissions, observability, and a rollout model that matches the risk of the workflow.

  • AI Agents
  • Enterprise AI
  • Operating Model

Why I Fell in Love with WebAssembly (and You Should Too)

WebAssembly isn't just another compile target—it's a paradigm shift that's quietly revolutionizing how we think about performance, portability, and the future of computing.

  • WebAssembly
  • Performance
  • Runtime Design