Anthropic Claude: The Complete Developer Guide

What is Claude?

Claude is a family of AI models built by Anthropic, an AI safety company founded by former OpenAI researchers. Claude is known for: •Best-in-class coding - consistently top-ranked for code generation •Strong instruction following - reliably follows complex prompts •Safety-first design - Constitutional AI approach •Large context window - 200K tokens (entire codebases)

Claude Model Lineup

Claude Opus - most capable, best for complex reasoning and analysis Claude Sonnet - best balance of capability and speed, ideal for coding Claude Haiku - fastest and cheapest, best for simple tasks and high-volume

For most developers, Sonnet is the sweet spot - it handles coding, analysis, and conversation at a great price/performance ratio.

Claude Code

Claude Code is Anthropic's agentic coding tool that runs in your terminal. It can: •Read and understand your entire codebase •Make multi-file changes autonomously •Run tests and fix failures •Create PRs with descriptions •Debug complex issues

Claude Code is what makes Claude the #1 choice for software engineers who want AI pair programming, not just code completion.

Claude API for Developers

Using the Claude API: •Messages API - conversational interface with system prompts •Tool use - function calling for agent-like behavior •Vision - analyze images and screenshots •Streaming - token-by-token response streaming •Batching - process multiple requests efficiently

Pricing is competitive: Sonnet at $3/$15 per 1M tokens (input/output).

Code Example: Claude API with Tool Use

Here's how to use Claude with function calling for an agentic workflow:

python

client = anthropic.Anthropic()

# Define tools the model can call tools = [{ "name": "get_weather", "description": "Get current weather for a city", "input_schema": { "type": "object", "properties": { "city": {"type": "string", "description": "City name"} }, "required": ["city"] } }]

response = client.messages.create( model="claude-sonnet-4-20250514", max_tokens=1024, tools=tools, messages=[{"role": "user", "content": "What's the weather in Tokyo?"}] )

# Check if Claude wants to call a tool for block in response.content: if block.type == "tool_use": print(f"Tool: {block.name}, Input: {block.input}") # Execute the tool and send results back ~~~

This pattern is the foundation of AI agents: the model decides WHEN to use tools and WHAT to pass them, while your code handles the actual execution.

Frequently Asked Questions

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