5 DAYS AGO • 4 MIN READ

Friday Finds — People-Centered Design, Saying "No", Death of Knowledge Work

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“If you write what you yourself sincerely think and feel and are interested in… you will interest other people.”
Rachel Carson

There's honestly nothing that fills my tank quite like face-to-face conversations, and lately I've been absolutely spoiled! From the ATD conference in DC to this week's fantastic Canadian eLearning conference in Toronto, my cup is practically overflowing with inspiration and genuine connections. And speaking of great connections, I have to shout out the incredible team at TechSmith—Matt, Emmie, Jason, and everyone else are such a joy to collaborate with, which was perfectly evident during our online event last week. These past few weeks have been a beautiful reminder of why I love what I do and the amazing people who make this industry so special.

Thanks for reading!

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📰 News & Notes

People-Centered (Not Tech-Driven) Design

Rundown: Don Norman argues design should serve people—not the other way around. He emphasizes that machines should fill in where humans struggle, not force humans to adapt to tech.

The Context:

  • He points out that true simplicity means making complexity understandable, not eliminating it
  • Effective design, he says, results from teamwork between humans and tech—where each takes on what the other can’t do well

Why It Matters:

  • For L&D pros, this translates into learning experiences shaped around the learner, not the latest platform features.
  • A people‑first lens ensures training is intuitive, engaging, and tailored—reducing friction and increasing impact.
  • And it aligns with design’s core: solve real problems with human‑centric empathy and iterative testing.

Takeaway: Think human first, tech second. Start your L&D design by deeply understanding learners’ needs and capacities. Use tech only if it enhances, not replaces, the human experience.

Are your current workshop strategies preparing learners to navigate AI—or simply use it?

Does Saying "No" Damage L&D's Reputation?

Rundown: Saying “no” to every training request can trap L&D in task mode—but always saying yes stretches resources and signals “just order-takers.” Jess Almlie suggests a smarter approach: ditch yes/no, and invite a deeper conversation instead.

The Context:

  • Requests signal pain, not always training needs—jumping straight to yes/no leaves problems unresolved.
  • A mindset shift: treat requests as invitations to partner in problem-solving. Reflect stakeholder language, ask “why,” and listen.
  • Techniques: act like detectives; facilitate reflection; add unexpected value when fulfilling necessary training.

Why it matters: This approach elevates L&D from cost center to strategic ally. You show up as problem solvers, deepen credibility, and get smarter requests—like “help our team explain this product better” versus “build a 30‑min eLearning.” Over time, partners come back for strategic help, not just training.

What to try: Next time you hear “Can you build training for this?” respond with, “Thanks for trusting us—let’s explore why this matters and what success looks like.”

How might we redesign our first conversations with stakeholders to uncover the real pain—before we even think about creating a learning solution?

Knowledge Work Is Dying—Welcome to the Age of Wisdom Work

Rundown: AI is rapidly outpacing traditional knowledge work—doing in days what took humans years. Experts in law, physics, and engineering are facing obsolescence. The future lies not in knowing more, but in applying wisdom: emotional clarity, discernment, and human connection.

The Context:

  • Knowledge—once a rare asset—was the currency of advancement. Those who amassed expertise thrived.
  • With AI capable of mastering vast domains in hours, raw talent is fast becoming commoditized
  • Even brilliant experts can be sidelined if they lack relational and emotional competence—areas where AI can’t tread

Why It Matters: For L&D professionals, this shift demands a pivot. Designing training for emotional intelligence, adaptive thinking, and relational leadership becomes critical. It’s no longer enough to build knowledge—meaningful impact comes from how humans use AI-driven outputs with empathy and insight. The pathway forward for learning design is about cultivating habits of reflection, deep listening, and ethical discernment.

If AI can generate accurate answers instantly, how might L&D shift its focus from what people know to how they show up—and what would that learning look like?

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If tools are your jam, check out my Work Smarter newsletter.

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This is the conversation that caught my ear this week. Check out previous episodes in the Friday Finds podcast playlist.

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