RAG, fine-tuning, and prompting are not competing techniques — they solve different problems. RAG handles dynamic knowledge. Fine-tuning improves style and format. Prompting shapes behavior. Here is when to use each for developer tools.

Cursor, Copilot, and Claude Code each win on different tasks. Cursor dominates codebase-aware editing. Copilot wins for inline completions in VS Code. Claude Code excels at autonomous multi-file tasks. This comparison uses real benchmarks.

Multi-agent systems assign each task to the model best suited for it — Claude for long-context reasoning, GPT-4o for vision, fine-tuned models for domain tasks. Routing logic, handoff protocols, and cost optimization strategies.

Vibe coding is not letting Cursor write your entire app while you describe vibes. Senior developers use AI as a force multiplier for specific tasks — scaffolding, tests, boilerplate, and documentation — while retaining ownership of architecture.

Claude generates production-ready code when you give it the right system prompt, structured output format, and quality constraints. These patterns turn Claude into a reliable code generation engine for real projects.

Most AI agent tutorials stop at a simple tool-calling loop. Production agents need planning/execution separation, persistent memory, error recovery, and observability. This is the real architecture.

Retrieval-Augmented Generation for code makes your AI assistant aware of your actual APIs, patterns, and conventions — instead of hallucinating methods that do not exist in your version of the library.

AI code review as a GitHub Action catches security vulnerabilities, N+1 queries, missing error handling, and architecture violations on every PR — before human review, not instead of it.

Most developers prompt AI coding tools the same way they write a ticket — describe the goal and hope for the best. These prompting patterns — chain-of-thought, few-shot, role, constraint — are what multiply AI coding output quality.

GitHub Copilot, Cursor, Claude Code, and Codeium each dominate different developer workflows. This 2025 comparison covers real benchmarks, pricing, context window sizes, and which tool wins for each task type.