Build a Local AI Dev Environment · 30 min · Continue.dev · VS Code · Ollama

Local Code Assistant in VS Code

The same Ollama server you've been curling since Lesson 2 is what powers autocomplete in your editor -- there's no separate 'AI coding' infrastructure, just another client of the same local API.

Hiring signal: Wiring a local model into your actual editor -- not just a chat window -- is what makes a local AI stack part of your real daily workflow instead of a separate tool you occasionally open.

What you will learn

Connect a VS Code AI assistant extension to your local Ollama models
Configure the coding-focused model for completions, distinct from the general chat model
Test both inline completion and the chat panel on a real project

What You're Building

The exact same Ollama server from Lesson 2, now feeding autocomplete and a chat panel directly inside VS Code — the point where this stops being "a local AI project" and starts being part of how you actually write code.

Continue.dev configuration

{
  "models": [
    {
      "title": "Local Chat (Qwen3)",
      "provider": "ollama",
      "model": "qwen3:8b"
    }
  ],
  "tabAutocompleteModel": {
    "title": "Local Autocomplete (Qwen3 Coder)",
    "provider": "ollama",
    "model": "qwen3-coder:7b"
  }
}

Two separate model entries, deliberately: tabAutocompleteModel is the fast inline-completion path (fires constantly as you type, so latency matters more than raw capability), models is the chat-panel path (fires on-demand for real questions, where you'd rather have Qwen3-Coder or even the general model's stronger reasoning than raw speed). This mirrors the exact "different models for different jobs" principle from Course 07's Planner/Specialist model split -- coding assistants aren't one model doing everything.

Verify Continue.dev is still the right choice when you read this
Local coding-assistant tooling moves fast -- Continue.dev is a solid, actively maintained choice as of when this course was written, but check the current landscape (Continue.dev, Cursor with an Ollama backend, aider as a terminal-based alternative) before assuming this is still the best option. The actual skill transferring here is "connect an editor tool to your local Ollama server," which applies regardless of which specific extension wins next year.

Unlock the full lesson

You've read the first 2 sections. The rest of this lesson covers Test it for real, not with "hello world", What you're building today — plus a hands-on lab, quiz, and project artifact.

Create a free account to unlock Phase 0 and Phase 1 of every course — no credit card.