The biggest mindset shift I made: stop thinking of AI as a replacement for PM work, and start thinking of it as a Toil Compression Engine. https://t.co/EYuLH5FIhe via @LinkedIn
How to debug a team that isn’t working: the Waterline Model - is interesting read. Some of the elements so relatable based on my personal experience over the years
https://t.co/Hc2tVp5Lf4
“There’s a Mexican standoff happening between product manager, designer, and coder.”
Marc Andreessen on how AI is reshaping core tech roles:
“Every coder now believes they can also be a product manager and a designer, because they have AI. Every product manager thinks they can be a coder and a designer. And every designer knows they can be a product manager and a coder.”
“People in each of those roles now know or believe that with AI, they don’t need the other two roles anymore.”
@pmarca on Lenny's Podcast with @lennysan
Much of the dialogue at Davos has focused on geopolitical turbulence. Justifiably so.
However, when the co-founder of one of the world’s most dominant private equity firms states that India provides their highest rate of return globally, that is massive news, even by Davos standards.
This statement is a far greater validation of India’s trajectory than any claim made by local policymakers or business leaders.
Davos is ultimately a convening of capital; when the "smart money" speaks this clearly, the impact is enormous.
My compliments to Amit Dixit, Head of Blackstone Private Equity in Asia, for achieving this podium position.
(Here’s an interesting sidebar: I’m particularly proud because, many moons ago, Amit spent a year at Mahindra before heading to Harvard Business School. He helped launch Automartindia which evolved into Mahindra First Choice, now a premier player in the pre-owned vehicle industry.)
Pain is the new moat
"Anybody who wants to build something these days, the information is at your fingertips more than it's ever been. You can learn anything overnight. So going through the pain of learning and understanding what works and what doesn't work, and going through this pain of developing multiple approaches, and then solving the problem—I feel that is going to be the real moat as an individual going forward."
— @kiritibadam, OpenAI
Okay so I need to talk about what’s happening with Yann LeCun because this is genuinely one of the wildest exits I’ve ever seen in tech.
For those who don’t know—LeCun is one of the “godfathers of AI.” Not a marketing title. The man literally won the Turing Award (basically the Nobel Prize of computer science) for helping invent deep learning. He’s been at Meta for over a decade as their Chief AI Scientist. An absolute legend.
So here’s what happened.
Zuckerberg got frustrated. Llama wasn’t moving fast enough. The AI race was heating up and Meta felt like it was falling behind. So what does Zuck do? He drops $14 BILLION on Scale AI and hires its 28-year-old co-founder, Alexandr Wang, to run a brand new “Superintelligence Lab.”
And then—and this is the part that still blows my mind—he makes Wang… LeCun’s boss.
Think about that for a second. A 65-year-old Turing Award winner. Four decades of groundbreaking research. The guy who helped BUILD this entire field. Now reporting to someone whose company… labels data. (Scale AI is impressive, don’t get me wrong, but they don’t actually build AI models. They annotate training data for other companies.)
LeCun just did an interview with the Financial Times and honestly? He chose violence.
Called Wang “young” and “inexperienced.” Said he has “no experience with research or how you practice research, how you do it. Or what would be attractive or repulsive to a researcher.”
And then dropped this absolute gem: “You don’t tell a researcher what to do. You certainly don’t tell a researcher like me what to do.”
I mean. The man said what he said.
But wait—it gets better. Or worse, depending on how you look at it.
LeCun straight up confirmed that Meta’s team “fudged” the Llama 4 benchmark results. Like, actually manipulated them. Used different models on different tests to make the numbers look better. Remember when everyone was suspicious about those benchmarks back in April? Yeah. Turns out they were right to be.
Apparently Zuckerberg was furious when this came out internally. LeCun says he “lost confidence in everyone who was involved” and basically sidelined the entire GenAI team.
And here’s the thing that really gets me—LeCun has been saying for YEARS that LLMs are a “dead end.” That you can’t get to real intelligence just by predicting the next word. That we need “world models” that actually understand physical reality, not just language patterns.
Everyone at Meta wanted him to stop saying this publicly. Bad for the narrative, you know? But LeCun refused.
His exact words: “I’m not gonna change my mind because some dude thinks I’m wrong. I’m not wrong.”
That’s not arrogance. That’s a scientist who’s seen enough hype cycles to know when something doesn’t add up.
So now he’s out. Launching his own company called AMI Labs—Advanced Machine Intelligence. They’re targeting a $3 billion valuation. Building those world models he’s been talking about. Says he’ll have a “baby version” ready within a year.
Oh, and apparently French President Macron personally texted him after the news dropped. LeCun won’t say what the message said but like… the man is getting DMs from heads of state now.
I don’t know if LeCun is right about everything. Maybe LLMs will surprise us. Maybe Meta will figure it out. But when one of the three people who literally invented modern AI walks out the door saying your entire strategy is fundamentally flawed?
I don’t know man. I’d at least ask some questions.
The AI wars just got very, very interesting
“I like being scared”
Molly Graham (@molly_g) has worked for some of tech’s most effective leaders, including @finkd, @chamath, @sherylsandberg, and @btaylor. She’s best known for her “Give away your Legos” framework and her collection of practical mental models for leading through hypergrowth. Today she leads https://t.co/x4nVAo3kUE, a community for leaders navigating rapid scale, growth, and change.
In our conversation, we dig into:
🔸 Why the best careers look like J-curves, not stairs.
🔸 “The waterline model” for diagnosing team problems (and why you should “snorkel before you scuba”)
🔸 “Give away your Legos”: her framework for scaling yourself as a leader
🔸 Six rules for creating effective goals
🔸 Three rules of thumb for leading through rapid scale
🔸 So much more
Listen now 👇
• YouTube: https://t.co/uYtIw4g1yr
• Spotify: https://t.co/4NXX4u7gki
• Apple: https://t.co/TC5NiifbU2
Thank you to our wonderful sponsors for supporting the podcast:
🏆 @DeveloperXM — The developer intelligence platform designed by leading researchers: https://t.co/INhXcJ5AfD
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"Good product work is seeking clarity. What would make this execution actually matter.
In this era, directing and managing agent work becomes the craft. Writing code is less like constructing a solution and more like setting up the conditions for a good solution to emerge. This might not be even an individual task, but an organizational one: how can you create these conditions as to the whole product team."
“The people who invented refrigeration made some money, but most of the money was made by Coca-Cola, who used refrigeration to build an empire.
LLMs are like as refrigeration. and the Coca-Cola has yet to be built”
~Chamath Palihapitiya
We are still in the waterwheel phase of AI, bolting chatbots onto workflows designed for humans. We need to stop asking AI to be merely our copilots. - great read!!
Welcome Agentforce Sales + ChatGPT! 🌟 Our Christmas gift: The world’s #1 Sales Cloud is now alive inside the world’s #1 LLM—delivering CRM context, data, intelligence, and action to every seller. Your pipeline just got supercharged. Manage your sales force smarter—from literally anywhere (even at the top of Haleakala). Close deals faster than you can say “Mele Kalikimaka”! 🚀❤️🎅 🧑🎄#Agentforce #SalesforceAI
Last quarter I rolled out Microsoft Copilot to 4,000 employees.
$30 per seat per month.
$1.4 million annually.
I called it "digital transformation."
The board loved that phrase.
They approved it in eleven minutes.
No one asked what it would actually do.
Including me.
I told everyone it would "10x productivity."
That's not a real number.
But it sounds like one.
HR asked how we'd measure the 10x.
I said we'd "leverage analytics dashboards."
They stopped asking.
Three months later I checked the usage reports.
47 people had opened it.
12 had used it more than once.
One of them was me.
I used it to summarize an email I could have read in 30 seconds.
It took 45 seconds.
Plus the time it took to fix the hallucinations.
But I called it a "pilot success."
Success means the pilot didn't visibly fail.
The CFO asked about ROI.
I showed him a graph.
The graph went up and to the right.
It measured "AI enablement."
I made that metric up.
He nodded approvingly.
We're "AI-enabled" now.
I don't know what that means.
But it's in our investor deck.
A senior developer asked why we didn't use Claude or ChatGPT.
I said we needed "enterprise-grade security."
He asked what that meant.
I said "compliance."
He asked which compliance.
I said "all of them."
He looked skeptical.
I scheduled him for a "career development conversation."
He stopped asking questions.
Microsoft sent a case study team.
They wanted to feature us as a success story.
I told them we "saved 40,000 hours."
I calculated that number by multiplying employees by a number I made up.
They didn't verify it.
They never do.
Now we're on Microsoft's website.
"Global enterprise achieves 40,000 hours of productivity gains with Copilot."
The CEO shared it on LinkedIn.
He got 3,000 likes.
He's never used Copilot.
None of the executives have.
We have an exemption.
"Strategic focus requires minimal digital distraction."
I wrote that policy.
The licenses renew next month.
I'm requesting an expansion.
5,000 more seats.
We haven't used the first 4,000.
But this time we'll "drive adoption."
Adoption means mandatory training.
Training means a 45-minute webinar no one watches.
But completion will be tracked.
Completion is a metric.
Metrics go in dashboards.
Dashboards go in board presentations.
Board presentations get me promoted.
I'll be SVP by Q3.
I still don't know what Copilot does.
But I know what it's for.
It's for showing we're "investing in AI."
Investment means spending.
Spending means commitment.
Commitment means we're serious about the future.
The future is whatever I say it is.
As long as the graph goes up and to the right.
Loved this deep dive on the Crossbeam–Reveal merger. If you’re building network‑effect products, this is gold on when competitors should merge to unlock real customer value and better unit economics
https://t.co/psU7RkkRzZ