In the first post of this series, I introduced the Agent Storybook Project (ASP), an open-source multi-agent system on GKE that adapts public-domain classics into illustrated …

In case you missed it, in the first post of this series, I introduced the Agent Storybook Project (ASP)—an open-source multi-agent system running on GKE that adapts classic public-domain literature into illustrated …

A couple months ago I had an idea for a novel (hehe 😏) project: I wanted to build an agent that would adapt a classic Russian book into a children’s book for my friend. …

“Agent” is doing some heroic heavy lifting as a word right now.

Depending on who you ask, an agent might be:

• A python script firing off 10,000 parallel …

Two weeks ago, Model Context Protocol shipped its 2026-07-28 specification revision.

The biggest updates in this release are: no more stateful initialize handshake, Mcp-Session-Id headers have been retired, and every request …

Have you heard the classic story about a county fair where people were guessing the weight of an ox? Nobody was exactly right, but somehow the average of all the guesses was remarkably accurate! Francis Galton wrote an …

I created a skill to save users 40-60% on token costs when migrating AI inference workloads from a serverless platform (like Cloud Run or Gemini Enterprise Agent Platform) to GKE. So what is it? What isn’t it? Why a …

Introduction to Distributed RL Sandboxing on GKE

Reinforcement Learning (RL) is the cornerstone of modern AI training. Rather than train a model to produce an expected output, we verify if it has achieved a particular outcome. This is …

Ok, so you’re writing an AI agent to automate some task (who isn’t these days?). But where does it live? That largely depends on what you want it to do.