Michael Janzen

Bridging Art, Design, and Technology with a Maker's Mindset

Tag: Leadership

  • 3 Rules for Getting Better AI Outputs by Improving How You Prompt and Iterate

    3 Rules for Getting Better AI Outputs by Improving How You Prompt and Iterate

    As we integrate AI into our workflows, I’m seeing a gap between users who get mediocre results and those who achieve stronger outcomes. The difference isn’t the tool—it’s the mindset.

    I operate with three “AI Golden Rules” that reframe the human-AI relationship from a simple transaction to a working collaboration.

    1. Treat AI Answers as Hypotheses Never take an AI’s output as gospel. Think of it as a highly capable but context-blind collaborator. It can generate a wonderfully articulate plan, draft a compelling email, or write flawless code that completely misses the strategic point. The output is a hypothesis to be tested, not a conclusion to be accepted. Your job is to be the senior strategist who validates, questions, and applies real-world wisdom.

    Rule 2 Iterate Through a Feedback Loop

    2. Exercise Human Agency Iteratively The most common mistake — what I call the AI vending machine mistake — is treating AI like a vending machine: one quality AI prompt in, one answer out, with no refinement in between. The best work comes from a feedback loop. Think of it as a conversation: you lead with a prompt, the AI responds, and you refine together., the AI follows with a response, and you refine the steps together. This iterative AI feedback loop sharpens the output with every cycle, aligns it closer to your vision, and ultimately ensures the final product is yours, augmented by the machine.

    3. Provide Context, Context, Context The principle of “Output quality tends to reflect input quality — a vague prompt returns a generic answer.” has never been more relevant. If you give a vague prompt, you’ll get a generic, surface-level answer. Mastering AI briefing techniques — structuring your prompts with clear intent and detail — tends to produce far more specific, usable results. at briefing your AI.

    • Background: What’s the history of this project?
    • Goal: What specific outcome are we driving toward?
    • Constraints: What are the non-negotiables, limitations, or style guides?
    • Persona: Who is the AI supposed to be, and who is the audience?

    The richer the context you provide, the more nuanced and valuable the output will be.

    At their core, these rules are a reminder that the thinking applied to the tool determines whether you get ordinary outputs or transformative AI results.. for augmenting human intelligence, not replacing it.

  • Vertical knowledge is acquired; horizontal excellence is accumulated.

    Vertical knowledge is acquired; horizontal excellence is accumulated.

    TL;DR: Industry knowledge can be learned quickly, but the ability to ship successful products takes years of experience across multiple domains. The best PMs bring battle-tested expertise that adapts to any vertical, making diverse experience an advantage, not a limitation.

    In product management, there’s a myth that industry experience trumps all. But after years of watching PMs transition between sectors, I’ve observed something crucial: the best ones don’t start from scratch—they bring their entire playbook, ready to adapt it to new challenges.

    Learning a new vertical’s language takes weeks. Understanding its unique challenges takes months. But knowing how to ship complex software? That takes years of accumulated battle scars and a proven track record of delivering results.

    Workflows vary by context, but the core principles of shipping successful software remain consistent. So no matter what you’re building, the fundamentals remain constant: deeply understanding user needs, championing stakeholder priorities, prioritizing for maximum impact, and—most critically—delivering on-time results.

    Great product managers aren’t defined by the verticals they’ve worked in, but by the horizontal expertise they’ve built across every launch, every pivot, and every hard-won success. In fact, diverse vertical experience may be more valuable than narrow specialization because it proves you can adapt your expertise to every new challenge.

    My journey reinforces this truth. I began building CMS-powered websites, then navigated through commercial financial services, marketing platforms, and enterprise social collaboration systems that united thousands of users. Each vertical demanded new vocabulary and developing domain expertise, but the principles of shipping great software remained constant.

    When I moved into idea management—helping organizations identify patentable innovations and transform their culture—I realized that whether you’re routing breakthrough ideas or managing any workflow, excellence comes from accumulated experience, not acquired knowledge.

    You can always teach someone your industry or niche. You can’t teach people decades of shipping excellence. As a lifelong learner, I’m excited to take on the next challenge.

    Visual concept developed in collaboration with ChatGPT and DALL·E by OpenAI.

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