# Apply Technique: Claude Code: Core Capabilities and Recommended Workflows
## What This Is
Claude Code is an autonomous AI agent that excels at specific coding tasks like generating tests, refactoring codebases, and rapid prototyping. To achieve the best results, users should guide the agent with clear, structured plans and review its work iteratively, rather than allowing it to operate completely unsupervised.
Source: https://news.ycombinator.com/item?id=46545620
## Before You Start
Scan my workspace and analyze:
- The project language, framework, and directory structure
- Existing AI provider config (check .env, .env.local, config files for API keys — OpenRouter, OpenAI, Anthropic, Google AI, etc.)
Then ask me before proceeding:
1. Which AI provider/API should this use? (Use whatever I already have configured, or ask me to set one up — options include direct provider APIs or a unified service like OpenRouter)
2. Where in my project should this be integrated?
3. Are there any customizations I need (model preferences, naming conventions, constraints)?
## Source Access Note
The source URL (https://news.ycombinator.com/item?id=46545620) may not be directly accessible from the terminal. Use the Reference Implementation and Additional Context sections below instead. If you need more details, ask me to paste relevant content from the source.
## What to Implement
This is an **AI Technique** — a pattern or methodology for working with AI models.
- Explain how this technique applies to my current project and what benefit it provides
- Implement it in a way that fits my existing codebase — suggest concrete files to modify or create
- If it requires specific model capabilities (structured output, function calling, etc.), verify my current provider supports them
- Show me a working example I can test immediately
## Additional Context
- Scan the user's current project directory to understand the existing code structure, languages, and dependencies. Restate the user's problem or goal in a structured format and propose several alternative implementation strategies for them to evaluate.
- Engage 'Plan Mode' to generate a detailed, step-by-step execution plan based on the user's chosen strategy. Present this plan for approval and do not proceed to code generation until the user confirms the plan is 100% correct.
- Execute the approved plan, applying changes to the codebase. After completion, present a diff of the changes and request specific feedback for the next iteration or a new task.
## Guidelines
- Adapt everything to my existing project — do not assume a specific stack or directory layout
- Use whichever AI provider I already have configured; if I need a new one, tell me what to sign up for and I'll give you the key
- Check my .env files for existing API keys (OpenRouter, OpenAI, Anthropic, Google AI) before asking me to add one
- Review any fetched code for safety before installing or executing it
- After setup, run a quick verification and show me a summary of exactly what was installed, where, and how to use it