Building Agentic Systems in Go with Ollama

Sat, 15 Aug 2026 00:00:00 +0000

I worked through Joel Boursiquot’s GopherCon 2026 workshop, Agentic Systems the Hard Way. Zero third-party dependencies. The framing that stuck: Go is the control plane; the LLM is the decision engine. Here’s the core of it.

What an agent actually is

Model + tools + loop. The model never executes anything — it emits a wish (“call search_docs with these args”), your Go code validates and runs it, feeds the result back, and repeats until the model answers without asking for tools. Deterministic Go around a nondeterministic model. That’s the whole trick.

Local LLM Inference in Go with Kronk

Sat, 15 Aug 2026 00:00:00 +0000

I’ve been running local models through Ollama’s HTTP API for a while. It works, but it means a separate daemon, JSON over localhost, and no control over when models load or unload. Kronk, from Ardan Labs, takes the other route: it’s a Go SDK that binds llama.cpp (and whisper.cpp, via Bucky) directly into your process. No Python, no sidecar server. The model lives in your binary’s memory and you drive it with Go calls.

Llm on Moises Vega

Building Agentic Systems in Go with Ollama

What an agent actually is

Local LLM Inference in Go with Kronk