Ever wondered which AI model you should actually pick for your coding project? In this episode, Zareef breaks down why there's no single best answer and walks through how to think about model choice based on where you are in your project's life cycle.

• The answer to "best model for code generation" is always it depends
• Your choice depends on project complexity, size, and current stage in the life cycle
• It also depends on what you're trying to achieve next in your project
• Anthropic's Sonnet 4.5 is recommended for planning purposes
• Anthropic suggests using Opus for day to day coding work
• Large context projects can take advantage of the one million token context window
• OpenAI's Codex with GPT-5 and related models are solid options too
• For open source, Qwen is a personal favorite, with GLM models as another option
• Availability and your specific use case matter just as much as raw model quality
• Avoid the trap of always reaching for the flashiest model for every task
• Decide based on what you're actually doing at that moment, then choose accordingly