Build your personal AI copilot

A guide to using AI as a long-term thinking partner (including prompts to get you started)

2025-07-226,180 words6 claims2 podcast connections

Consensus3+ guests independently agreeSynthesisLenny combined multiple guest insightsCurationAmplified one guest's ideaOriginalLenny's own addition

Most tech workers are missing out on AI's potential because they are not providing enough context; LLMs feel like blunt, generic instruments when they lack the background knowledge a human colleague would need.

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An AI copilot built with ongoing context about your goals, role, projects, team, and org becomes a real thinking partner for long-term complex work, not just a document generator.

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Building an AI copilot follows a four-step process analogous to onboarding a teammate: hire it with instructions, onboard it with company knowledge, kick off initiatives in chat threads, and put it to work with simple prompts.

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The habit of 'gossiping' to your AI copilot -- casually updating it about conversations, stakeholder changes, and new information via speech-to-text -- is critical for keeping context fresh and effective.

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Even when AI is wrong it can be valuable because it spurs you to crystallize what you actually think; the goal is not perfect answers but getting the most out of yourself as a thinking partner.

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AI copilot investment earns compound interest: uploading retrospectives and lessons learned from completed initiatives makes the copilot increasingly effective across all future work.

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