How to Use an AI Coding Assistant in 2026
A practical guide to getting started with AI coding assistants. Learn best practices, common pitfalls, and how to maximize productivity with terminal-based AI tools.
Getting Started with AI Coding Assistants
AI coding assistants have evolved from simple autocomplete tools into sophisticated development partners. In 2026, terminal-based AI assistants like Aurict offer multi-agent orchestration, contextual skills, and deep codebase understanding.
Choosing the Right Tool
When selecting an AI coding assistant, consider these factors:
- Provider flexibility — Can you switch between Anthropic, OpenAI, Google, and others?
- Agent architecture — Does it use specialist agents or a single model?
- Context awareness — Does it understand your codebase automatically?
- Platform support — Does it work on macOS, Linux, and Windows natively?
Installation and Setup
Installing Aurict takes less than a minute:
The first-run wizard guides you through provider selection and API key configuration.
Best Practices
To get the most out of your AI coding assistant:
- Be specific in your requests — vague prompts get vague results
- Use the right agent for the task — explore, code, review, test, etc.
- Leverage persistent memory — the AI remembers your preferences
- Review AI suggestions — trust but verify
Conclusion
AI coding assistants are no longer experimental — they're essential tools for modern development. Aurict's multi-agent approach and 218+ contextual skills make it a powerful choice for any developer.