Intro

What if the biggest barrier to learning AI isn’t the tools—it’s how we approach learning itself?

In this episode of Supra Insider, Marc Baselga and Ben Erez sit down with Gagan Biyani, CEO and co-founder of Maven, to unpack why this moment is critical for mid-career professionals to prioritize self-learning. Gagan shares lessons from running a cohort-based learning platform and conducting 30-50 interviews with companies struggling to adopt AI. He explains why AI is like witnessing the internet as a child—you can’t afford not to learn it—and why building the learning habit matters more than what you learn first.

They explore the five problems companies face with AI education: trying to generalize training when every role needs different tools, listening to tinkerers instead of bridge adopters, and delegating to chiefs of staff instead of having C-level sponsors run the trainings. Gagan shares Maven’s own journey—why their design team needed to rebuild the design system before AI could be useful, how they’re changing team ratios from 3-4 engineers per designer to just 2, and why social media is terrible for learning anything that requires weeks of dedication.

If you’re a mid-career professional feeling overwhelmed by AI, a leader trying to build a culture of self-learning at your company, or wondering how to actually integrate AI into your workflows—this episode is for you.

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Want company-specific PM interview intel?

If you’re a PM preparing for interviews at Uber, Figma, Stripe, DoorDash and OpenAI… we think you’re going to love Insider Loops. You can read about it in Ben’s LI post, Marc’s LI post or check out the site directly below.

In this episode, we covered the following topics:

* (01:35) The AI era creates a velocity of change that people absolutely need to keep up with

* (05:28) The fundamental skill of learning new things applies to everything—soccer, AI, anything

* (09:40) Create false accountability before you build a habit—some people always need it, others use it as an on-ramp

* (12:00) Social media is terrible for learning AI—you can’t learn it in 30 minutes or an hour

* (16:30) Every type of work requires a different type of learning about AI tools

* (24:40) Problem #1: Every role requires a different set of AI tools depending on what you’re building

* (28:40) Problem #2: Companies try to generalize AI education when it needs to be role-specific

* (29:10) Problem #3: AI requires system-level changes at the company level—AI consulting is booming

* (31:10) Problem #4: Companies listen to tinkerers (top 1-10%) who aren’t the right people to listen to

* (34:20) Problem #5: L&D specialists are good at teaching known things, but with AI they need to learn it first

* (40:30) Design-to-engineer ratio needs to change because both are more productive with AI

* (53:30) Why mid-career folks are least motivated but need learning most (vs early and late career)

* (57:40) Best approach: interview through their resume, ask what they learned and accomplished at each step

* (01:12:05) Gratitude Corner: Michelle Whitman (first boss), and early Udemy believers—Adeo Ressi, Bubba Murarka, Keith Rabois, Mark Sugarman, Russ Fradin

* And more!

Links:

* Gagan Biyani X: https://x.com/gaganbiyani

* Gagan Biyani: https://www.linkedin.com/in/gaganbiyani/

* How to Become a Supermanager with AI by Hilary Gridley: https://maven.com/hilary-gridley/ai-powered-people-management

* Yuan Wang (Head of Design at Maven): https://www.linkedin.com/in/theyuanstudio/

* Michelle Whitman: https://www.linkedin.com/in/michelle-whitman/

* Adeo Ressi: https://www.linkedin.com/in/adeoressi/

* Bubba Murarka: https://www.linkedin.com/in/bubba/

* Keith Rabois: https://www.linkedin.com/in/keith/

* Mark Sugarman: https://www.linkedin.com/in/msugarman/

* Russ Fradin: https://www.linkedin.com/in/rfradin/

* Maven: https://maven.com/

* Marc: https://www.linkedin.com/in/marcbaselga/

* Ben: https://www.linkedin.com/in/benerez/

If you’re a new subscriber, we encourage you to check out some of the recent episodes you might have missed:

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