Before ending a complex session or hitting a context window limit, instruct your AI to summarize key themes, decisions, and open questions into a "handoff document." This tactic treats each session like a work shift, ensuring you can seamlessly resume progress later without losing valuable accumulated context.
When working with multiple AI tools (e.g., an LLM for strategy, another for code, a third for images), delegate the task of writing prompts to your main AI partner. Explain your goal, and have it generate the precise instructions for the other tools. This saves time and ensures greater precision in your communications across a complex AI stack.
Instead of solely relying on AI for net-new ideas, articulate your own thoughts and have the AI play them back to you. This process helps clarify your thinking, reveal gaps in your logic, and validate your intuition, demonstrating that much of the AI's value lies in refining your existing knowledge.
Shift away from the traditional model of drafting content yourself and asking AI for edits. Instead, leverage the AI's near-infinite output capacity to generate a wide range of initial ideas or drafts. This allows you to quickly identify patterns, discard unworkable concepts, and focus your energy on high-level refinement rather than initial creation.
Unlike human collaborators, an AI lacks feelings or an ego. This means you should be direct, critical, and push back hard when its output isn't right. Frame the interaction as a demanding dialogue, not a polite request. You can also explicitly ask the AI to critique your own ideas from first principles to ensure a rigorous, two-way exchange.