Claude Code Clearly Explained (and how to use it)

What It Covers

Ross Mike provides a practical crash course on mastering Claude Code, emphasizing that quality outputs depend entirely on quality inputs. He demonstrates the ask user question tool for detailed planning, explains when to avoid using RALF automation loops, and shares a testing-based workflow that builds features incrementally while validating each step works before proceeding.

Key Questions Answered

• •Ask User Question Tool: Invoke this specific Claude Code feature during planning to trigger detailed interviews about technical implementation, UI/UX decisions, and trade-offs. The tool asks progressively granular questions across multiple rounds, forcing you to specify details like database choices, cost handling, and workflow preferences that basic planning overlooks, resulting in comprehensive PRD documents that prevent costly token-wasting revisions later.
• •Feature-Based Planning with Tests: Structure plans around discrete features rather than describing entire products. After building each feature, write a test to verify it works before moving to the next one. This approach prevents building feature two on top of broken feature one, saves tokens by avoiding backtracking, and creates a systematic development process where passing tests gate progress through your feature list.
• •Avoid RALF Until Experienced: Beginners should not use RALF automation loops despite the hype. Building manually first develops product intuition, teaches proper prompting, and creates understanding of how features connect. RALF only amplifies your plan quality - a poor plan with RALF just burns tokens faster. Only use automation after successfully deploying at least one working application with a public URL that others can access.
• •Context Management at 50%: Monitor your context window usage and start fresh sessions when reaching 50% of the 200,000 token limit (around 100,000 tokens used). Beyond this threshold, model performance deteriorates as context overload causes the AI to forget earlier instructions or make inconsistent decisions, similar to human cognitive overload. This prevents the common experience where sessions start strong but quality degrades over time.
• •Planning Investment Prevents Slop: Spend significant time on PRD creation rather than rushing to build. Specify UI presentation (dashboard, modal, separate page), user workflows (linear, batch, conversational), storage approaches, and cost constraints. Models now execute plans precisely, so vague instructions produce vague results. The planning phase feels tedious but directly determines whether you build production-ready software or AI-generated slop requiring expensive rework.