Field Notes
Learning to build with AI, and writing it down as I go.
I'm a technical architect with 20 years building system level and cloud native products. I now lead AI strategy and applied systems in sport and entertainment, building the teams and agentic systems behind it, and I'm the founder of AgenticGoKit, an open source Go framework for AI agents. I write here about what I'm figuring out along the way.
Recent Writing
AI-Native Companies Will Outlearn Everyone Else
The real advantage was never automation. It is compounding learning.
ReadThe Hidden LLM Call: Why AgenticGoKit Was 2x Slower
How a hidden continuation loop, a leaky network stack, and pprof helped Go reclaim the fast path. go slower 2x Situation: “Why is Go slower than Python?” I …
ReadAnnouncing v1beta: Production-Ready AI Agents in Go
We’re excited to announce v1beta, our next-generation API for building AI agents in Go. With streaming-first architecture, multimodal support, and powerful workflow orchestration, building production-ready AI systems has never been easier.
ReadBuilding a Local Document Reader with Streaming TTS
KittenTTS demo Ever wished you could just press play on a long document and have it read to you without uploading anything to the cloud? That’s exactly what …
ReadReal-Time AI Editorial Workflows in Go: Loop, Revise, Publish with AgenticGoKit
Build real-time AI editorial workflows in Go with AgenticGoKit — loop revisions, stream progress to a live UI, and publish polished stories.
ReadAgenticGoKit ❤️ HuggingFace and OpenRouter
AgenticGoKit Loves HuggingFace and OpenRouter We’re excited to announce the release of AgenticGoKit v0.4.6 — a major update that expands how Go developers can …
ReadBuilding AI Agents That Actually Do Things: Tools and MCP Made Simple in Go
agentic workflow with tools If you’re new to building AI agents in Go, you might think integrating tools and external services is complex. It’s not. …
ReadBuilding Context-Aware AI Agents with Memory in AgenticGoKit
Simple streaming (terminal) One of the biggest challenges in building AI agents is making them remember. Users expect conversational agents to recall previous …
ReadStreaming AI Responses in Go with AgenticGoKit
Streaming makes AI feel alive—tokens show up instantly, long tasks feel responsive, and multi‑step workflows become explainable as they run. In this post, we’ll …
ReadBuilding Multi-Agent Workflows in Go: Simpler Than You Think
TL;DR: Create a professional research-to-report pipeline with two AI agents in under 60 lines of Go code. The Challenge You want to build an AI system that: …
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