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Lenny's Podcast: Product | Career | Growth

The grief, loneliness, and burnout sweeping through the tech industry right now | Molly Graham

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Original episode
PodcastLenny's Podcast: Product | Career | Growth
Publisher/creatorLenny Rachitsky
Published
Shortcast updated

About this episode

Molly Graham is back for round two, and this one is even more powerful. Molly has spent more than 20 years helping organizations and the humans inside them navigate growth and change. She’s held leadership roles at Google, Facebook, Quip, and the Chan Zuckerberg Initiative and is the host of TED’s WorkLife podcast (which she took over from Adam Grant). She also runs Glue Club, a leadership community for senior operators, and writes a popular newsletter called Lessons.

In our in-depth conversation, we discuss:

1. Why Molly’s famous “give away your Legos” career advice no longer holds true in an AI world

2. The grief, loneliness, and burnout sweeping through the tech industry right now

3. Why delegating to AI is fundamentally different from delegating to a human

4. The fear narrative around AI job displacement, and why it’s overblown

5. Which Legos you should never give to AI

6. What the best managers are doing right now

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Brought to you by:

WorkOS—Make your app enterprise-ready, with SSO, SCIM, RBAC, and more

DX—Engineering intelligence for the AI era

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Episode transcript: https://www.lennysnewsletter.com/p/the-grief-loneliness-and-burnout

Archive of all Lenny's Podcast transcripts: https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0

Highlights: https://lennyspodcast.com/mostreplayedmoments

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Where to find Molly Graham

• X: https://x.com/molly_g

• LinkedIn: https://www.linkedin.com/in/mograham

• Substack: https://mollyg.substack.com

• Website: https://glueclub.com

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Where to find Lenny:

• Newsletter: https://www.lennysnewsletter.com

• X: https://twitter.com/lennysan

• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/

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In this episode, we cover:

(00:00) Molly Graham returns

(03:34) What is “Give away your Legos”?

(05:44) The origin story: Google, Facebook, and rapid scale

(11:27) What still holds true in an AI world

(18:13) Engineering’s identity shift: from rowing to steering

(22:09) Loneliness and the collapse of team structure

(24:06) The centaur and the reverse centaur

(25:36) The fear narrative: AI-branded layoffs and overblown doom

(29:20) Survey data: burnout is up to 55%, but half of people are thriving

(35:07) Cleaning up AI slop

(40:01) What’s actually different: delegating to AI vs. giving Legos to a human

(42:02) Why every worker is now a manager, whether they want to be or not

(49:07) Why giving things away creates space for new opportunities

(55:27) Advice for people in the age of AI

(59:38) What Legos you should never give away

(01:03:12) The human sandwich: vision at the top, AI in the middle, humans at the end

(01:05:00) Holding on to the things you love: grief, funerals, and what comes next

(01:09:39) Slow takeoff: why you’re not too late

(01:13:32) The most important skill to build right now

(01:18:58) A message for managers and leaders

(01:24:17) Key takeaways

(01:31:42) Final thoughts

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References: https://www.lennysnewsletter.com/p/the-grief-loneliness-and-burnout

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Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

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Lenny may be an investor in the companies discussed.



To hear more, visit www.lennysnewsletter.com

Episode summary

This AI-generated Shortcast summary may omit nuance. Use the original episode when context or exact wording matters.

Molly, your “give away your Legos” advice helped people grow: hand off the projects and responsibilities you built so you can move into what comes next. But AI makes that less comforting. People are being asked to hand Legos to machines while wondering whether the machine takes the whole job. Where does the old advice still hold, and where needs a caveat?

It came from wild growth at Google and Facebook. You build the thing, become known for owning it, and somebody tells you to hand it over. Your whole body goes, no, I’m good at this, I like this, what if this is the only fun thing? Under change, we get territorial. But if other people join, you can make something new. I thought this was Facebook-scale advice; people everywhere wrote to say, yep, this is exactly what I’m feeling. It was really about change.

That still lands. Make yourself less essential to the current version of the job so you can meet what arrives next. The future belongs more to people who keep learning than people defending what they know. Staying still feels safe, but in a fast-changing company, it is how you end up underwater.

For engineers, that is raw. The familiar pleasure was: sit down, write code, build the thing. Now it can be prompting agents, monitoring them, and reviewing what comes back. People miss the old version. Smaller, agent-heavy teams can also mean less of the collaboration people loved.

Under “I miss being hands-on” can be grief: is the company growing, or is my profession changing under my feet? Somebody said work moved from rowing to steering. Lots of people are saying, I don’t want to fucking steer. Maybe rowing is what they love; maybe they fear it is all they know. A universal-builder future can feel lonely. We do not have to be fluffy bunnies about it. Change can be exciting and still suck.

Leaders need to take that seriously. Strip humans out and you may get efficiency, but also sad humans, and sad humans do not make the best work. The technology and its story change constantly, while people hear, do more for the same money. Of course they ask: I see the bottom-line benefit, but why is this good for me?

Our data is mixed: burnout rose sharply, yet about half of respondents said they were happier than ever. Happiness tracked most strongly with feeling amplified by AI, especially among people with authority and on smaller teams. Designers feel the pressure too: anyone can generate something vaguely designed, but taste, feedback, alignment, and thought still take time.

The gap between “I made a prototype” and “this is exceptional” is huge. We treat AI like the smartest hire ever, when it is often a lazy intern. An intern needs context, coaching, edits, and many passes. You would not send their first deck to your boss untouched. Copy-paste-send outsources accountability and makes the recipient clean up. More output is not more efficient if everyone must wade through it.

That is the revision. With a human, giving away a Lego means they own it and you get mental space back. With AI, the robot does some work, but you still stand behind the tower. Quality, judgment, and the outcome remain yours.

Delegating to a robot is not truly handing something off. You retain the oversight tax. Your team doubled overnight with weird little robots that periodically wreck the tower, and you have to say, no, no, no, that is not what I meant. The skills are management: give context, check work, correct, coach. Lots of people chose not to manage humans, and now everyone manages pre-junior employees. Exhausting.

The old advice assumed that releasing the known thing opened opportunity. AI fear turns it into: teach an employee ten times smarter than you everything you know, then they replace you in six months. Who the fuck wants that deal? Some fear is real, but lots of AI-branded layoffs may be companies covering for other mistakes. We do not have evidence that every profession vanishes.

What if you believed your job continued to exist, but looked radically different every few years? That is more useful than gripping niche knowledge. Lawyers, engineers, designers, product people: what is the next version, and do you want to shape it? Holding tight to the past is not a strategy for thriving in change.

That may mean knocking down role walls. A designer can prototype and perhaps ship code with guardrails; a marketer might build something that reaches production. The question is less, “What tasks belong to a designer?” and more, “What is design for, and what could it become?”

But in AI Land, there are Legos I would keep: judgment, trust, vision, strategy, and work where you cannot define good yet. AI should take more of what humans were never suited to do, not outsource our thinking. Let it amplify the human brain; do not hand your vision of the world to summer interns. Woof.

I like the human sandwich: we set direction and describe the world we want, AI works in the middle, then we review and refine. Otherwise it can optimize for a result we do not want. Something can push a booking or upsell brilliantly and still create an experience humans would rather not make. Not just can we ship this, but should this be the world we are building?

Loss deserves room before reinvention. Sometimes you need a funeral for the part of the job you loved. Be sad, let your team be sad, then ask: what could I care about or become extraordinary at in this version? You can mourn old work and still find possibility in new work.

Managers are modeling what good looks like: how they use AI and whether they acknowledge what this pace does to people. Do not let accountability disappear because a tool made the first draft. Be clear about what humans own, and care for humans navigating. People need to feel seen and supported; that matters no less now.

That is the Trojan horse here. People arrive for tactics and realize they needed permission to feel unsettled while still participating. Grieve what changed, keep learning, choose your human Legos carefully, and help steer toward something genuinely good.

Find people to compare notes with instead of staying alone in a sad hole. We need less panic about the hottest tool and more honesty about the human experience. If you feel a little crazy, lots of people are grieving and recalibrating too. Let this fun, intelligent intern make more room for what you love and the joy you want to put into the world.

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