The Best LOCAL Agentic Coding Workflow (Complete Guide)
Run a 100% offline, fully agentic local coding setup on your own computer without any subscription fees or internet connection
. This guide covers hardware sizing, local model selection, setting up LM Studio, integrating custom language model endpoints into VS Code, and configuring local inline autocompletion using the Continue extension
.
⏱️ Timestamps
00:00 – Introduction to Local Agentic Coding
00:30 – How Local LLMs Work vs. Cloud APIs
01:00 – VRAM (Windows/Linux) vs. Unified Memory (Apple Silicon)
03:00 – Memory Throughput & Hardware Performance Trade-offs
04:00 – Hardware Cheat Sheet: Matching VRAM to Model Parameter Size
05:00 – The Two-Model Architecture: Autocomplete vs. Main Chat/Agent Models
06:30 – Model Selection Deep Dive: Qwen 2.5 Coder & Qwen 3 Series
07:30 – Understanding Quantization (Q4 vs. Q6) and Active Parameters (A3B)
08:30 – Sponsor Segment: Deploying Websites Instantly with here.now
09:30 – Downloading Software: LM Studio & VS Code
10:30 – Downloading Models and Configuring Context Lengths in LM Studio
12:00 – Starting the LM Studio Developer API Server
13:00 – Configuring Custom Model Endpoints in VS Code
15:00 – Testing Local Agentic Task Execution in VS Code
16:30 – Setting Up Local Autocomplete with the Continue Extension
18:00 – Final Thoughts & When to Use Local vs. Cloud Models