How to Build an AI Agent in Go with GigaChat: A Complete Guide
Out of curiosity, a developer built an AI agent in Go using LangChainGo, tools, request chains and integration with the Russian GigaChat model. The article walks through the architecture, MCP setup, the problems the author ran into and how they solved them. It is aimed at anyone who wants to add AI to a Go application.
AI-processed from Habr AI; edited by Hamidun News
A developer decided to build an AI agent in Go with GigaChat after a talk on AI agents inspired them. It was not easy, but it worked. Now they share what they learned and break down the architecture: how to make a Go application not just generate text, but think and act.
How does an AI agent differ from an ordinary neural network?
An AI agent differs from an ordinary LLM in that it is not just a text generator but a system that makes decisions. The agent analyzes a task, picks a suitable tool (search, calculation, an API call), invokes it, gets the result, and then keeps reasoning.
- Nov 2, 2026Arca gives AI agents finance tasks lasting up to 10 days, but leaves the trades to humans
- Nov 2, 2026DeepSeek open-sources Super-agent prototype: p95 task completion time of 15.7 minutes vs. 29.5
- Nov 2, 2026Bun creator uses Claude Code to port 750K lines from Zig to Rust in 11 days
- Nov 2, 2026Microsoft releases 4B model Mage-VL-Cowork, which solves 66.0% of OSWorld-Verified tasks
Build & Ship Production AI Agents Without Boilerplate Code
Start your free 72-hour trial at Hamidun Academy (academy.hamidun.com) — interactive lessons on Claude Code & Cursor, live Tech Radar, and production agent templates.
The AI world, distilled — once a week
Seven stories that actually mattered, hand-picked. No noise, no reposts, no press releases.
Done! Check your inbox for a confirmation.