AI tools are commoditizing the act of writing code (software development). The durable skill and key differentiator is now software engineering: architecting systems, creating great user experiences, and applying taste. Building something people want to use is the new challenge.
AI models like Claude Code can experience a decline in output quality as their context window fills. It is recommended to start a new session once the context usage exceeds 50% to avoid this degradation, which can manifest as the model 'forgetting' earlier instructions.
Automation tools like "Ralph" loops are only as effective as the plan they execute. Running them with a poorly defined plan will burn through tokens without producing a useful result, effectively wasting money on API calls. A detailed plan is a prerequisite for successful automation.
Don't ask an AI agent to build an entire product at once. Structure your plan as a series of features. For each step, have the AI build the feature, then immediately write a test for it. The AI should only proceed to the next feature once the current one passes its test.
Beginners using Claude Code should resist automation loops like "Ralph." Instead, they should build feature-by-feature, testing each one manually. This process develops crucial product sense and debugging skills, similar to learning to drive before using self-driving features.
Instead of accepting a generic plan, prompt Claude Code to use its "Ask User Question Tool." This invokes an interview process, forcing you to consider minute details like technical implementation, UI/UX, and trade-offs, leading to a much stronger and more actionable plan.