To get superior results from AI coding agents, treat them like human developers by providing a detailed plan. Creating a Product Requirements Document (PRD) upfront leads to a more focused and accurate MVP, saving significant time on debugging and revisions later on.

When using AI development tools, first leverage their "planning" mode. The AI may correctly identify code to change but misinterpret the strategic goal. Correct the AI's plan (e.g., from a global change to a user-specific one) before implementation to avoid rework.

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.

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.

Instead of immediately asking an AI to perform a complex task, first prompt it to create a functional spec or a sequential plan. Go back and forth to align on this plan before instructing it to execute, which significantly improves the final output's quality and relevance.

Instead of manually reviewing an AI agent's detailed execution plan, increase velocity by trusting the process and asking targeted, high-level questions to confirm its strategic approach. This is faster and builds confidence in the agent's capabilities.

Instead of basic prompting, use an AI agent's "plan mode" to collaboratively outline a complex task, like writing a strategy doc. This lets you align on structure, sources, and verification steps before generation, yielding far superior results. It's like briefing a junior employee.

To get better results from AI, don't ask for the final output immediately. Instead, prompt the AI to first provide a detailed process. This allows you to review and debug its logic, then instruct it to execute each step for a more accurate outcome.

AI can get hyper-focused on a specific task and lose sight of the overall user flow. A dedicated "Spec Flow Analyzer" agent can simulate a user persona and review the entire plan, ensuring all necessary steps are connected and the feature is cohesive from a user's perspective.