For experienced users of Claude Code, the most critical step is collaborating with the AI on its plan. Once the plan is solid, the subsequent code generation by a model like Opus 4.5 is so reliable that it can be auto-accepted. The developer's job becomes plan architect, not code monkey.

An effective AI development workflow involves treating models as a team of specialists. Use Claude as the reliable 'workhorse' for building an application from the ground up, while leveraging models like Gemini or GPT-4 as 'advisory models' for creative input and alternative problem-solving perspectives.

Agentic coding tools like Claude Code represent a new, distinct modality of AI interaction, as significant as the advent of image generation or chatbots. This shift is creating a new category of power users who integrate AI into their daily workflows not just for queries, but for proactive, complex task execution.

LLMs often get stuck or pursue incorrect paths on complex tasks. "Plan mode" forces Claude Code to present its step-by-step checklist for your approval before it starts editing files. This allows you to correct its logic and assumptions upfront, ensuring the final output aligns with your intent and saving time.

For large projects, use a high-level AI (like Claude's Mac app) as a strategic partner to break down the work and write prompts for a code-execution AI (like Conductor). This 'CTO' AI can then evaluate the generated code, creating a powerful, multi-layered workflow for complex development.

Claude Code can take a high-level goal, ask clarifying questions, and then independently work for over an hour to generate code and deploy a working website. This signals a shift from AI as a simple tool to AI as an autonomous agent capable of complex, multi-step projects.

Use the Claude chat application for deep research on technical architecture and best practices *before* coding. It can research topics for over 10 minutes, providing a well-summarized plan that you can then feed into a dedicated coding tool like Cursor or Claude Code for implementation.

Use Claude's "Artifacts" feature to generate interactive, LLM-powered application prototypes directly from a prompt. This allows product managers to test the feel and flow of a conversational AI, including latency and response length, without needing API keys or engineering support, bridging the gap between a static mock and a coded MVP.

AI is moving beyond text generation. Using Claude's 'Artifact Builder' skill, it can create and deploy functional web applications directly in the chat window. A user can prompt it to build a tool, like a UTM link generator, and receive a usable app, not just code snippets.