Lenny&#39;s Podcast

Our reading — their words are on the recording

0:15:06
Our reading
Leading right now requires talking about and normalizing the overwhelm people are feeling.
Their wordsThere's a lot of overwhelm that all, you know, manifests. Some of it manifests in burnout, but it's like there is just a lot going on for people right now. And you really can't lead right now without talking about that um and without normalizing that.
empathy management
0:15:48
Our reading
The future will be defined by people who learn, not people who know.
Their wordsthe future will be defined by the people that learn not the people that know.
curiosity agency education
0:16:56
Our reading
In a period of rapid change, standing still is the least safe option, because it guarantees falling behind.
Their wordsBut actually standing still is like the least safe thing you can do. It's basically you're guaranteed to fall behind.
agency
0:20:38
Our reading
Engineering is probably one of the areas where jobs have most visibly been transformed by AI.
Their wordsI think engineering is like probably one of the most visceral areas where people's jobs have genuinely transformed.
coding agents AI and jobs
0:27:01
Our reading
As of now there is not much data showing that AI is genuinely taking jobs away.
Their wordsLike as of right now, like there is not a lot of data, although you may have more than I do that says that AI is genuinely taking jobs away.
LLMs AI and jobs agency
0:27:15
Our reading
AI-branded layoffs are not about AI; they are about badly run companies putting an AI label on having hired too many people.
Their wordsthey are about badly run companies slapping an AI label and getting some share points from that versus saying, "Whoops, we made we hired too many people."
AI and jobs team size management

Peter SellisFormer head of product at Discord; earlier Snap's first product manager, where he spent seven years, and before that a product manager at Ustream.20 Sept 2026 · 1h 36m · 18 korrentsOn product management, management and design

90 minutes of unfiltered product advice from Snap and Discord’s product chief | Peter Sellis

Peter Sellis

All 18 from this episode, along the running time →

Our reading — their words are on the recording

0:06:50
Our reading
Collaboration carries coordination costs that leave a team moving as slow as its slowest node.
Their wordscollaboration comes with incredible coordination costs. And coordination costs essentially assure that you're moving as slow as the slowest node
team size management
0:13:08
Our reading
It is essential to build an organization that can absorb spiky, unconventional talent.
Their wordsI think it's like essential to be able to create an organization that can adopt that type of talent.
agency hiring management
0:15:06
Our reading
Spiky product managers are like bands: sometimes they put out a dud album, and if you still believe in them as artists you stick with them.
Their wordsThat's kind of how I think of a lot of the spikier product managers that I've worked with, which is like, man, sometimes they whiff on an album, but if I still believe in them as an artist, like I'll stick with them.
product management
0:18:18
Our reading
The way the product management profession is set up, its median practitioner is probably pretty bad.
Their wordsmathematically uh it's kind of like set up to be this profession where the the median product manager is actually probably pretty bad.
product management
0:20:16
Our reading
Great engineers rarely complain about product managers, because they bend them to their will and do not put up with bad ones.
Their wordsI really don't hear great engineers complain about product managers that much because great engineers a they know how to bend product managers to their will. They get the the the use out of them that they want and b they just like don't put up with bad ones.
product management
0:21:41
Our reading
Ads are the product-market fit of consumer monetization on the internet.
Their wordsads are truly the magical kind of like product market fit of consumer monetization on the internet.
product management

Roman UgarteLeads product for Grok Bot at SpaceX AI; previously led growth at Cursor, which he joined when it had about 15 people.8 Sept 2026 · 1h 22m · 18 korrentsOn design, AI agents and startups

How we built Grok Bot in a month | Roman Ugarte (SpaceXAI)

Roman Ugarte

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Our reading — their words are on the recording

0:10:27
Our reading
An AI product that adds a tab for each new form factor is shipping its org chart, and users seem to be reacting negatively to it.
Their wordsinstead it's three different visions that all kind of share a screen and you can hop between but it is kind of a shipping your org chart style thing that I think users are reacting negatively to.
design
0:14:58
Our reading
As models get smarter, users should no more need second-by-second updates from an AI agent than from a teammate.
Their wordsAnd the reason for that is we think as these models get smarter, the same way that your teammate, you know, you wouldn't ask for second by- second updates of exactly all the buttons they're pressing and websites they're going to, I think it's too much to ask your bots to do that, too.
LLMs
0:20:38
Our reading
Much of what people want from AI is not menus and features but something they can hand a meaningful task to and have it done.
Their wordsa lot of what people want from AI is not this thing with lots of drop- down menus and bells and whistles, but just a thing that you describe a task, a task that's meaningful to you and it goes and it does it
design
0:28:35
Our reading
Adding things to a product is not the goal and is not what makes it more useful to more people.
Their wordsLike adding things to the product is not the goal. That's not the thing that's going to push this this product forward and make it more useful to more people.
design
0:30:38
Our reading
Users should never have to think about whether an AI agent's work runs locally or in the cloud.
Their wordsAnd the first is you should never have to think about local and cloud and where are these workflows running?
the cloud
0:32:04
Our reading
AI agents need their own computers, because people do not do their jobs through APIs but by clicking and typing on a computer.
Their wordsWe as humans don't do our jobs via MCPS and APIs. Like we use a computer and we click on pixels and we kind of type things in input boxes. And it's very important that your bot has those baseline capabilities as well.
AI agents

Anish AcharyaGeneral partner at Andreessen Horowitz (a16z), focused on consumer investing; previously founded SocialDeck, sold to Google, and Snowball, sold to Credit Karma, where he became VP of Product and then GM of its consumer product and credit card business.6 Sept 2026 · 1h 19m · 20 korrentsOn LLMs, creativity and design

Why companies are becoming a series of loops | Anish Acharya (a16z)

Anish Acharya

Our reading — their words are on the recording

0:03:09
Our reading
The fear of falling into an AI-made permanent underclass is a funny dark fantasy Silicon Valley seems to hold collectively.
Their wordsit's a funny dark fantasy that we seem to have as, you know, Silicon Valley collectively.
Silicon Valley
0:06:14
Our reading
There will be no sudden fast takeoff in AI, even though model progress is happening faster than ever.
Their wordsSo, I don't believe that that's going to happen. I do think that model progress is happening faster than ever before.
AGI LLMs
0:06:47
Our reading
People may be overestimating how many problems are bound by intelligence rather than by other things.
Their wordsSo, I think we might be overestimating how many problems are intelligence bound versus bound by other things.
humility
0:09:45
Our reading
The most ambitious companies are rethinking everything around the models, while others are only giving existing teams access to AI.
Their wordsSo, I do think that like the most ambitious companies are rethinking everything around the models. And those that are a little less ambitious or perhaps a little earlier are thinking more about how do we give people and existing orgs existing job functions access to the technology.
AI and jobs ambition innovation
0:13:18
Our reading
Companies will probably come to run on a cascade of AI loops, from a loop per person up to loops that run large parts of the company.
Their wordsSo, I think we're going to see this sort of cascading set of everything from a loop per person, loop per job function, loop across entire business units to, you know, loops that can run large parts of the company.
agency
0:15:15
Our reading
An AI loop can climb to a local maximum but then plateaus, and human intuition is needed to find the next hill.
Their wordsyou know, the loop will help you climb to the local maxima, but then it plateaus. And you need some sort of out of distribution thinking, you need human intuition, you need somebody to actually help you land at the base of the next hill.
creativity

Tara SeshanProduct lead for ChatGPT Work at OpenAI; previously one of the first five product managers at Stripe, head of product at Watershed, and a Thiel Fellow.30 Aug 2026 · 1h 21m · 17 korrentsOn product management, agency and AI agents

AI’s third era: the rise of persistent AI coworkers | Tara Seshan (OpenAI’s product lead)

Tara Seshan

All 17 from this episode, along the running time →

Our reading — their words are on the recording

0:07:48
Our reading
In a fast-changing AI market, being prolific and empirical matters far more than being academic or theoretical.
Their wordsAnd so actually being prolific and being um more like empirical is way more important than being um like maybe more academic or theoretical.
innovation
0:08:38
Our reading
The most important thinking a product manager does is defining the core hypothesis as pointedly as possible.
Their wordsAnd what that means is the thinking you need to do is being as pointed as possible about what your core hypothesis is. And that hypothesis definition is the most important thing.
product management
0:09:27
Our reading
The core of product management has always been finding the most essential question to ask about a product.
Their wordsBut the core of it has always been about what is like the most essential question you need to ask about your product. Like what is the thing that will determine whether your product works or doesn't work?
product management
0:11:22
Our reading
Work will increasingly look like steering rather than rowing, with agents doing the rowing.
Their wordsI do think that increasingly the future of work will look more like steering than rowing in the sense that there will be agents that you'll you'll be able to work with that do a lot of the rowing and your role increasingly becomes steering the ship in the right direction and pointing it in the right direction.
AI and jobs AI agents
0:12:20
Our reading
People may underrate the power of intuition and of deciding what they want the future to be.
Their wordsI think sometimes that we underrate like that power of like intuition or even um sort of like positive like determinism of what we want the future to be like.
optimism agency
0:18:03
Our reading
Working with agents should ideally feel like a multiplayer game, with people steering their agents together.
Their wordsIdeally, work feels like a multiplayer game where all of us together are getting stuff done, steering our agents as our agents continue to take care of more and more of those like rowing tactical tasks.
AI agents

Jen AbelCo-founder of JJELLYFISH and GM of enterprise sales at State Affairs.23 Aug 2026 · 1h 24m · 24 korrentsOn SaaS, behavioural science and benchmarks

84 minutes of enterprise sales alpha | Jen Abel

Jen Abel

Our reading — their words are on the recording

0:05:02
Our reading
Selling a $100,000 enterprise deal takes the same process as selling a million-dollar one.
Their wordsif you sell a $100,000 solution, it is the same exact process to sell a million-doll solution.
SaaS
0:05:17
Our reading
Enterprise buyers are more sensitive to the sales process they are taken through than to the product demo.
Their wordsthe enterprise organizations are more sensitive to the process you take them through from a sales motion than they almost are with demoing the product.
SaaS behavioural science
0:11:34
Our reading
The best person to reach a corporate executive one-on-one is the founder.
Their wordsThey will respond one-on-one. And the best individual to one-on-one to a corporate executive is the founder.
0:12:52
Our reading
A $100,000 enterprise deal needs an executive sponsor to sign off and allocate the budget.
Their wordsa $100,000 deal needs a executive sponsor to sign off on it to allocate the budget.
SaaS
0:16:07
Our reading
A startup that cannot get an executive excited by its value proposition probably should not be selling top-down into the enterprise.
Their wordsif you don't have executive value, meaning you cannot get an executive exc excited by your value proposition, then you probably shouldn't be moving up into the enterprise doing a top down strategy.
startups
0:19:02
Our reading
The first intro call is where a seller gains all of the information edge, because buyers clam up once it feels like a sales process.
Their wordsthe information they will tell you on the first call, they will clam up moving forward because it starts to feel like a sales process. So, all of the information edge you can gain as a seller is on this first call.
behavioural science

Ian SilberDesigner who led product design at OpenAI, including ChatGPT and Codex; previously at Artifact and, for eight years, Instagram.16 Aug 2026 · 1h 12m · 22 korrentsOn design and LLMs

Chatbots are not the final interface: OpenAI’s Head of Design on what’s next | Ian Silber

Ian Silber

Our reading — their words are on the recording

0:05:08
Our reading
Unlike coding with an agent, the design process is still messy and fluid.
Their wordsthe design process is really still very messy and fluid and you think you have a great idea and you try it and it sucks
design
0:12:32
Our reading
Nobody should feel behind on AI in design, because someone starting today would still have a head start on most people.
Their wordsnobody should feel like behind right now. I think that if you literally started today, you're going to have a leg up on pretty much most people.
design
0:13:34
Our reading
Everyone is still extremely early in working out how AI changes design, and nobody has it figured out.
Their wordsWe're all extremely early in this process and nobody really has like the it figured out.
design
0:15:04
Our reading
The human element of design will become more and more important as more software gets made.
Their wordsI do think that the human element of design is going to really be start to become more and more important.
design
0:17:11
Our reading
This is the best time to be a designer.
Their wordsI really do think it's the best time to be a designer.
design
0:19:12
Our reading
Single siloed role definitions for product, design and engineering do not really make sense.
Their wordsI've always found that these like single siloed um role definitions don't really make sense.
design

Adam WardHead of Talent at Cursor; co-founded the recruiting and talent-strategy firm Growth by Design, which Cursor acquired in November 2025.9 Aug 2026 · 1h 30m · 30 korrentsOn hiring, benchmarks and AI and jobs

The playbook for building high talent density teams | Adam Ward, Head of Talent at Cursor

Adam Ward

All 30 from this episode, along the running time →

Our reading — their words are on the recording

0:05:09
Our reading
The labour market is in a resettlement of talent and of how work gets done.
Their wordsI really believe we're in this like moment where there's this like resettlement of talent and labor and how work gets done.
AI and jobs
0:07:56
Our reading
Demand for narrowly specialised technical people may be waning.
Their wordsI think maybe the thing that is waning, I would say, is like the specialized technical person.
AI and jobs
0:13:23
Our reading
The candidates who reply to cold outreach are not the top 20 percent, just the ones caught on a bad day.
Their words20% of those will reply. By definition that is not the top 20% that is just the 20 people who you caught on a bad day for them.
hiring
0:13:40
Our reading
Funnel-style recruiting weeds people out at each stage and ends up hiring whoever remains.
Their wordsthe way we all recruit is we kind of weed people out at each stage and we hire the remainder. So, this remainder hiring is the output of the funnel of doom.
hiring
0:15:52
Our reading
Treating recruiting like a sales funnel has been somewhat detrimental to companies.
Their wordsI think this connectedness to sales has been somewhat detrimental to companies as they think about doing this in a more strategic way.
hiring
0:16:28
Our reading
When hiring for the top 1 percent, the most important step is getting clear on what top 1 percent means for the company.
Their wordsif you think about going after the 1%, the most important step is getting really clear on what 1% means to you.
hiring

Tom VerrilliChief product officer at the live-shopping marketplace Whatnot, previously chief product officer at Twitch and a product lead on growth at Twitter.2 Aug 2026 · 1h 24m · 24 korrentsOn product management, management and AI and jobs

This CPO regrets that product management exists | Tom Verrilli (CPO of Whatnot)

Tom Verrilli

Our reading — their words are on the recording

0:04:40
Our reading
The only real case for product management as a specialist function is that it is a trade, not a qualification — something you get good at by doing.
Their wordsThe only argument as far as I'm aware for why you would want product management to be a specialist function is really it's a trade, not a qualification.
product management
0:06:36
Our reading
The engineer-designer-PM pod ratio was an HR artifact of scaling, not something anyone showed a product needed.
Their wordssomewhere along the line this kind of HR ratio of like a pod popped into being. You know, every time you hire six engineers, you add a designer or you add a PM, you add an EM
design
0:07:10
Our reading
Hiring product managers by ratio infantilizes engineers and designers who were perfectly capable of deciding for themselves.
Their wordshiring so many PMs infantilizes the engineers and the designers who are perfectly capable of making good decisions, but just never had to because there was always a PM to babysit them.
design product management hiring
0:09:53
Our reading
A company should hire a product manager only against a specific need, never by default.
Their wordswe articulate it that way to kind of force ourselves to remember that you don't hire a PM just for the sake of hiring one, you hire one with a really specific need.
product management
0:10:36
Our reading
Product managers should be assigned to problems, not attached to engineering teams.
Their wordsrather than mapping PMs to teams where you kind of assume that the PM will always do that, we tend to map them to kind of problems or kind of like core projects.
product management
0:14:22
Our reading
AI gives an individual contributor so much leverage that one very senior product manager beats three entry-level ones.
Their wordsyou can have one very senior PM across more things and they can be more efficient than having, you know, three relatively entry-level PMs.
AI and jobs product management team size

Elizabeth StoneChief Product and Technology Officer at Netflix, previously VP of Science at Lyft and an economist at Analysis Group.19 Jul 2026 · 1h 12m · 20 korrentsOn hiring, AI and human skill and AI and jobs

Why Netflix is betting on systems thinkers—not specialists—in the AI era | Elizabeth Stone (CPTO)

Elizabeth Stone

Our reading — their words are on the recording

0:03:47
Our reading
The confusion about who does what is a storming phase every transformative technology causes, and AI is in the middle of it.
Their wordsI think anytime a new technology comes along, especially one that's as transformative as GenAI, you go through a storming phase before you go through the forming phase of things. And I think we are in the middle of that right now.
AI and jobs
0:04:32
Our reading
That AI lets anyone prototype does not mean everyone should be shipping code to production.
Their wordsDo I believe that means anyone should be shipping code to production? That everyone should actually be doing everything? Probably not. But I think that it's good for people to be exploring what's possible.
vibe coding
0:12:26
Our reading
Craft excellence within each discipline is not going away, however much AI blurs the work across functional lines.
Their wordsI still see a craft excellence that's really important in the disciplines that I don't think is going away anytime soon. Even if there's fluidity or blurring of the work across the functional lines.
AI and human skill
0:14:29
Our reading
What made Netflix fast — local teams building whatever stack they needed — stops working once agents operate across systems; common paved paths now matter more.
Their wordsIn a world of AI with agents operating across multiple systems, wanting source of truth data, the importance of having preferred paved paths that get the most of the benefits and produce some guardrails so we can make sure we're doing good work, common infrastructure, common paved paths, solving problems once with a core set of capabilities becomes more important.
0:14:53
Our reading
The rising hire in an AI world is the systems thinker who can look across every business domain and name the building blocks, not the local domain expert.
Their wordsSo, we are hiring more people who can look across all the business domains and abstract that to here's the building blocks we're going to need in a world with AI.
AI and jobs hiring
0:15:59
Our reading
Once non-designers can build products, a design team’s job becomes templates and design systems — otherwise the company ships Frankensteins.
Their wordsI get really nervous about having different design languages or different types of user interactions and shipping Frankensteins, basically. So, designers need to then be the people we're hiring again for design systems thinking.
design

Adam MosseriHead of Instagram since 2018, previously head of Facebook's News Feed.9 Jul 2026 · 1h 08m · 20 korrentsOn social media, AI and jobs and design

The rise of taste, human authenticity and judgment in an AI world | Adam Mosseri (Head of IG)

Adam Mosseri

Our reading — their words are on the recording

0:04:10
Our reading
Small product teams beat large ones for a reason that has nothing to do with AI: fewer people to coordinate means less design by committee.
Their wordsBut they just by virtue of having less people to coordinate they can often move faster and make um better decisions a little bit less design by committee.
design
0:08:31
Our reading
Designers will do well out of AI rather than badly, because taste is the hardest part of their job to imagine being automated away.
Their wordsyou've got these other generalists doing design, you've got engineers doing design, product staff doing design, but I'm actually pretty long on design or designers because they tend to have taste and I think that is something that is much more difficult to imagine being automated away.
AI and jobs design taste
0:14:42
Our reading
Grit, fast learning and self-awareness are enough to get good at anything eventually, and whenever somebody is not working out, one of the three is missing.
Their wordsBecause if you're those three things, if you got fire in your belly, you learn quickly, and you're self-aware, you can kind of get good at anything eventually.
discipline
0:17:40
Our reading
AI resets who succeeds at work: success goes to whoever's strengths happen to match what the new tools and the business need, not to who was good before.
Their wordsSo you know who who succeeds is a function of whose strengths are aligned with the tools needs and the business's needs.
AI and jobs
0:22:30
Our reading
Within a year or two a strong engineer's token spend will rival their salary, and companies will have to cap it like any other resource.
Their wordsI think that you can imagine at least in an year or two coming that the the burn rate of a strong engineer might be the same as their salary or their cost of employment.
coding agents
0:24:50
Our reading
Directing an AI will turn out to be like leading a team: too prescriptive stifles good ideas, too open-ended wastes time going the wrong way.
Their wordsI believe that if you are too prescriptive as a leader with a team you end up stifling good ideas but if you're too open-ended sometimes teams just waste time um going in the wrong direction.
AI agents management

Mark PincusFounder and former CEO of Zynga, the social-games company behind FarmVille, Zynga Poker and Words with Friends, and before that of Freeloader, Support.com and Tribe.net.14 Jun 2026 · 1h 39m · 22 korrentsOn startups, product management and management

The hidden pattern behind successful products | Mark Pincus (FarmVille, Words with Friends, & more)

Mark Pincus

Our reading — their words are on the recording

0:04:29
Our reading
A founder's gut instincts are almost always right and the ideas built on top of them are usually wrong, so the work is to isolate the instinct and test many ideas around it.
Their wordswe have these instincts like in our gut, these human level instincts that are pretty much always right. And then we put these ideas on top of the instincts that are usually wrong. And my rule of thumb is your instincts are right 95% of the time.
startups
0:08:17
Our reading
A team has not earned the right to innovate on a product until it is the world's leading expert on the best versions of that product that already exist.
Their wordsAnd I like to say we we don't we haven't earned the right to innovate on the camera until we are the world's leading PhD on the best mobile cameras that already exist.
0:10:10
Our reading
The genuinely new idea in a product will probably fail; its job is to give people a reason to try the product at all.
Their wordsAnd we have to accept that that new idea is probably going to fail. It's a reason to try it for people, but it's probably going to fail.
product management
0:15:27
Our reading
The taboo against copying is a moral one, which is exactly what makes copying an arbitrage available to founders with less ego invested.
Their wordsin the Peter Teal sense it's almost a moral arbitrage because there's something in our gut as a product you you became a founder an entrepreneur because you wanted to go be an innovator and so it can feel like a beatdown that your path to innovation starts with copying other people's work
startups
0:16:17
Our reading
Ambition should be measured in the eyes of your customer rather than your peers, which means being willing to take the best ideas wherever you find them.
Their wordsif you're truly ambitious, burn your resume. If you and if you define your ambition in the eyes of your consumer, not your peers, you're not trying to win awards and respect from your peers.
ambition
0:17:04
Our reading
Taking something a person already loves and making it one inch better wins more of them than showing them something they have never seen and did not know they wanted.
Their wordsBut if you took something that she loves and you make it one inch better, she might love that more than if you showed her something she's never seen before and didn't wake up knowing that she wanted.

Tony FadellHow to build real taste (and why AI makes it matter more)Creator of the iPod and co-creator of the iPhone at Apple, founder of Nest, and author of Build.7 Jun 2026 · 1h 35m · 23 korrentsOn product management, coding agents and innovation

Tony Fadell: How to build real taste (and why AI makes it matter more)

Tony Fadell

All 23 from this episode, along the running time →

Our reading — their words are on the recording

0:08:58
Our reading
A version 1.0 has no data to be driven by, so one or two people must make the opinion-based decisions and own them.
Their wordsAnd so, if most of your decisions are going to be opinion-based decisions for a 1.0, you have to have one or two or a very, very small set of people who are in charge with making the opinion-based decisions
product management
0:10:41
Our reading
You cannot get real feedback on a new consumer product before shipping the whole thing; feedback starts when somebody spends their own money on it.
Their wordsAnd if you're doing a 1.0 and the world hasn't seen you, you're not going to get that from consumers, ever. You have to ship it, and you have to build the entire kind of ecosystem so those consumers see it in the fullness so that when they do the evaluation and they spend their own money, then you're getting real feedback.
product management
0:14:29
Our reading
Micromanagement should be aimed at the few decisions that matter, never at how people carry the work out.
Their wordsAnd when I mean micromanaging, it means micromanage the decision, not necessarily operations of doing it.
management
0:19:22
Our reading
A home assistant is only as good as its context, and context comes from sensors placed around the house rather than from a better model.
Their wordsthe way you get best context is by having sensors properly placed around the home that don't necessarily invade privacy, but allow you to pick up a lot of comings and goings and who's who in the room and your voice and these kinds of things.
0:23:14
Our reading
What is worth building is found by starting from a long-standing pain and asking which new technology has just made it solvable.
Their wordsAnd so, I always kind of start with okay, where's our current pain and are there new technologies to solve that pain?
product management
0:25:35
Our reading
What you have to invent is the whole system around a product, including how it is sold, bought and installed, not the one piece people remember.
Their wordsSo, you have to think about the full the full thing you're trying to build not just the one piece even though that's what you might remember. You have to remember it's it's a it's a system that you're going to innovate with.

Dan ShipperCo-founder and chief executive of Every, the AI-focused writing and software studio behind Cora, Spiral and Proof.24 May 2026 · 1h 34m · 24 korrentsOn AI agents, AI and jobs and coding agents

AI predictions: Job markets, Codex beats Claude, and the death of org charts | Dan Shipper

Dan Shipper

Our reading — their words are on the recording

0:00:40
Our reading
Every new model makes yesterday’s human competence cheap and therefore commoditised; the human job is to take that frozen competence and make something new with it.
Their wordsWhat models do in general is they make yesterday's human competence cheap. And so, it becomes commoditized. It's not valuable anymore. What humans do is we go in there and we're like, "Yeah, we have all this frozen human competence from yesterday. How do I use this like make something new and interesting?"
AI and jobs
0:00:57
Our reading
Within about a year everyone will have at least one agent they talk to and offload work to.
Their wordsIt's going to bifurcate in two main ways. One is everyone's going to have at least one agent that they talk to, that they can offload work to.
AI agents
0:12:05
Our reading
Most knowledge work will move inside a coding-agent environment like Codex or Claude Co-work, which becomes the operating system for email, documents and everything else.
Their wordsThe second is that most of the work that you do is actually going to happen on your computer in an environment like Codex or Cloud Co-work that becomes the sort of operating system for it becomes the sort of operating system for how how you do all of your work, whether that's your email, the documents you create, like all that kind of stuff.
coding agents AI and jobs Anthropic
0:13:44
Our reading
The workable model right now is one super agent for a whole company, not a personal agent for every person.
Their wordsAnd I have completely flipped. And I I really think that uh the the model for now is going to be a super agent, like one agent for the entire company.
AI agents
0:14:44
Our reading
An AI agent is only useful while a specific human cares about it; sever that personal connection and it stops being useful.
Their wordsin order for an AI agent to be useful right now, it really needs a human who cares about it. It really needs it like a human personal connection with someone who's like watching what it does and make sure that it's doing the right thing and that it's useful for people.
AI agents
0:21:03
Our reading
Codex, not Claude Code, is the right daily driver right now.
Their wordsbut I I think Codex right now is my daily driver. I like spend all all my time in it basically.
coding agents Anthropic

Eric RiesAuthor of The Lean Startup and Incorruptible, and founder of the Long-Term Stock Exchange, who advises companies on corporate governance and mission protection.10 May 2026 · 1h 39m · 24 korrentsOn AI alignment, startups and investing

How Anthropic, Costco, and Patagonia all build incorruptible companies | Eric Ries

Eric Ries

Our reading — their words are on the recording

0:06:38
Our reading
Organizations are dragged into mediocrity by a force no one controls but everyone obeys, until their founders lose control of what they built.
Their wordsI call it the force that no one controls but everyone obeys that tends to drag organizations down into mediocrity to the point that we lose control of them. Now, sometimes we lose control of them because we get fired.
startups
0:08:15
Our reading
What destroys great companies is not competition but their own success, because the more golden the goose the greater the temptation to butcher it.
Their wordsall kinds of famous companies where the thing that destroyed them was not competition. It was not someone else came up with a better product. No, their very success became a liability because the more golden the goose, the greater the temptation to butcher.
0:12:12
Our reading
If you do not get your company's governance right, none of your other decisions will matter for the long term, because you will not be the one making them.
Their wordsIf you don't get this right, no other decision you make about your company will matter for the long term because you're not going to be the one making it.
0:12:20
Our reading
Only a fifth of venture-backed founders are still CEO three years after going public, and the standard documents their lawyers gave them are why.
Their wordsAccording to Harvard Law School, among venturebacked companies that have the standard best practices set up that you got from your lawyer, okay, only 20% of founders are still the CEO 3 years after going public.
startups venture capital
0:18:31
Our reading
There is never a right time to protect a company's mission: it is too early until it is suddenly too late, and success is what makes you a target.
Their wordsWas it ever the right time? No, it is never the right time to do this. If you put this off, you will eventually find yourself in a situation where you can no longer do it. You will have lost the leverage. Success will not protect you because success is what makes you a target.
0:23:58
Our reading
The corporate best practices lawyers and bankers push on founders are younger than the trees in the local park.
Their wordsso many of the best practices that your lawyers, your bankers, whoever advisers you have, they're going to be pushing best practices on you that are younger than the trees in your local park.
startups

Evan SpiegelCo-founder and CEO of Snap Inc., the company behind Snapchat, which he started in 2011 while studying product design at Stanford.26 Apr 2026 · 1h 10m · 22 korrentsOn design, management and product management

How to win when software is not a moat | Evan Spiegel (Snapchat CEO)

Evan Spiegel

Our reading — their words are on the recording

0:04:42
Our reading
Distribution, not product-market fit, is the hard part of consumer technology, and almost nobody spends enough time on it.
Their wordsAnd I think people don't spend nearly enough time thinking about, you know, distribution and figuring out distribution. And that seems to me uh to be a huge differentiator.
product management
0:05:25
Our reading
The value of a social network is in connecting you to the handful of people you care most about, not in how many people it connects.
Their wordswhat really mattered was connecting you to the right people. And so, if you could just connect someone not to all their friends, but to their best friend, to their partner, to their spouse, the people that they cared most about in the world, that that that's where the majority of the value is in the network.
social media
0:07:00
Our reading
The next generation of great consumer companies will be born on new form factors like glasses, the way the last one was born on mobile.
Their wordsas we look forward to, you know, sort of these next generation form factors, things like glasses, there's going to be a whole new set of opportunities and a whole new surface for people to build generational consumer companies.
0:10:23
Our reading
Software is not a moat, and the AI industry is only now discovering what Snap learned fifteen years ago.
Their words15 years ago we essentially learned that software is not a moat, right? Which is something that everyone is discovering today with AI, right?
0:11:08
Our reading
A platform of creators and developers is a durable moat, because an ecosystem, unlike a feature, cannot be cloned.
Their wordsthe more that we could build a platform uh around our business, the more that we could build an ecosystem with creators and developers, the harder it would be for folks uh to to just copy that.
0:12:03
Our reading
Network effects are not a sufficient moat, because software features get copied however many patents you hold.
Their wordsnetwork effects are certainly an important piece of the puzzle for sure, um but I don't think they're enough when it comes to these sorts of software uh you know, software cloning.

Jason CohenFounder of WP Engine and Smart Bear, and the author of the long-running startup blog A Smart Bear.25 Jan 2026 · 1h 46m · 24 korrentsOn SaaS, startups and behavioural science

The surprising advice from a founder who built 2 unicorns | Jason Cohen (WP Engine)

Jason Cohen

Our reading — their words are on the recording

0:06:51
Our reading
Writing on a schedule is worth less than only publishing what is the best you can do, even if that means one post a year.
Their wordsmy attitude was was always I will only put out stuff if if it's the best that I can do. It's up to the reader to decide if it's good or useful. Um, and if so, if I don't have that, I'm just not going to publish.
writing
0:11:00
Our reading
Diagnosing stalled growth has a strict order, because fixing a later problem does nothing while an earlier one is still broken.
Their wordsthere's a there's a series of of questions that I ask to to diagnose why is growth slowing in this order because it's one of these things where the first one that's a problem, if you don't fix that, it doesn't matter if you fix one of the ones below.
startups
0:12:44
Our reading
A cancelling customer already survived an improbable gauntlet to buy, which makes churn an emotional emergency before it is ever a metric.
Their wordsThey actually had the budget and bought the stupid thing. Then they went through onboarding and invested their time etc etc. That is a crazy gauntlet that almost no one gets through.
SaaS
0:15:38
Our reading
Cancellations always overtake marketing, because cancellations grow automatically with the company while marketing grows only as fast as you can improve it.
Their wordsMarketing grows only as fast as you can improve marketing. We all know that's quite hard actually. It's linear. It's hard to find new channels that aren't trivial. Like, it's hard. Of course, we're going to do it, but like it it's hard. Whereas, cancellations grow automatically as you grow, right? So, cancellations always overtake marketing for this reason.
SaaS
0:16:42
Our reading
Every subscription business has a hard ceiling on its size: new customers per month divided by the cancellation rate.
Their wordsSo let's suppose you add 100 customers a month and you have 5% cancellation. So 100 divided by 5% is 2,000. So a company like that will never have more than 2,000 customers.
SaaS
0:18:56
Our reading
A cancellation-reason drop-down measures list order rather than reasons: randomise the options and every one of them gets picked equally.
Their wordsAnd I realized it was the first one on the list and I thought, huh, I wonder if people are just picking the first one. So then then we randomized the list so everyone saw a different order of the list and now all the items were picked equally
behavioural science

Jason LemkinFounder and CEO of SaaStr, the B2B software community and events business, and a SaaS investor who previously co-founded EchoSign and sold it to Adobe.1 Jan 2026 · 1h 42m · 24 korrentsOn AI agents, AI and jobs and SaaS

We replaced our sales team with 20 AI agents—here's what happened next | Jason Lemkin (SaaStr)

Jason Lemkin

Our reading — their words are on the recording

0:00:30
Our reading
AI is not taking the jobs people wanted; it is taking the jobs nobody wanted and the careers of everyone who is merely average.
Their wordsAI is replacing the jobs people don't want to do today, and it is displacing the midpack and the mediocre.
AI and jobs
0:09:33
Our reading
AI sales agents do not work out of the box; the training is the product.
Their wordsI think it's important that it takes time to train these agents. They don't work out of the box.
AI agents
0:18:09
Our reading
In many software categories more than half of all prospects are now in market at once, against a historical three to five percent.
Their wordsSo, add all that up, 5%. In many categories, we're north of 50% in market. So, that just totally changes.
SaaS
0:19:47
Our reading
The email-based sales development rep will be ninety percent displaced by AI within a year.
Their wordsThe emailbased cadence SDR will be 90% displaced by AI next year.
AI and jobs
0:19:58
Our reading
Having a human qualify inbound leads is already obsolete, and the role should be extinct within a year.
Their wordsThe contact mess that we see, we have no need for them today. They should be extinct next year.
AI and jobs
0:29:11
Our reading
Almost nobody should build their own AI go-to-market tools; buy them, the way you would buy any other software.
Their wordsDon't build it yourself. You're not Versel. You don't have a full-time wicked awesome engineer that wants to build this.
SaaS

Dylan FieldCo-founder and chief executive of Figma, the collaborative design platform he started in 2012 and took public in 2025.16 Oct 2025 · 1h 26m · 22 korrentsOn design, product management and LLMs

Figma’s CEO: Why AI makes design, craft, and quality the new moat for startups | Dylan Field

Dylan Field

Our reading — their words are on the recording

0:27:54
Our reading
Fun can be a product's differentiator, even when the team thinks that is an absurd thing to compete on.
Their wordsThe team was like what we're gonna make fun our differentiator and in retrospect it was absolutely the right move.
product management
0:33:23
Our reading
After a decade of Swiss minimalism, design is about to swing back to something far more expressive.
Their wordsI think we're going to swing back to being way more expressive and draw as part of that story.
design simplicity
0:35:10
Our reading
AI cannot get a product to the quality bar on its own, because it still works in the realm of averages.
Their wordsAnd AI won't get you there alone. AI is uh still in the realm of kind of law of averages and uh better prompting can help of course
LLMs product management
0:35:50
Our reading
In a product review a prototype beats a static mock, and a static mock beats a lot of words.
Their wordsat least my product reviews and uh product conversations, I feel like prototypes beat static mocks and static mocks beat lots of words.
design
0:40:24
Our reading
The thing to optimise at launch is time to value — how fast a new user reaches the moment that shows what the product can do.
Their wordsshortening the time to seeing and having that incredible moment and seeing, you know, the true value of the product, for example, in Figma design, can we get you to have a collaborative multiplayer moment?
0:42:22
Our reading
Striking down the boring blockers one by one moves retention and activation as visibly as any new feature does.
Their wordswe literally at some point had a team that would that was called blockers and they just went and one by one struck them down and each time we saw uh improvement in retention, improvement in activation the metrics for as we addressed each one you could literally see the change in the graph.
product management

Albert ChengHead of growth at Chess.com, previously growth and monetization lead at Grammarly and Duolingo and a product manager at Google.5 Oct 2025 · 1h 25m · 26 korrentsOn startups, product management and design

Finding hidden growth opportunities in your product | Albert Cheng (Duolingo, Grammarly, Chess.com)

Albert Cheng

All 26 from this episode, along the running time →

Our reading — their words are on the recording

0:10:32
Our reading
A growth team that only explores turns scattershot, and one that only exploits saturates — the job is to keep oscillating between the two.
Their wordsIf you do too much exploration, you can have your team feel a little bit too scattershot, just trying a 100 different random ideas. What's the through line? What's the strategy? How do you pattern match, you know, successes across them? And if you do too much in exploitation, which is often the MMO of growth teams, it can lead to this like saturation and stagnation where you're just locally maximizing a thing.
startups innovation
0:12:03
Our reading
After a defeat people want encouragement, not a list of their mistakes — so a learning product should lead with what the user did well.
Their wordsWhen you lose a game now as opposed to surfacing your blunders and your like horrible stuff that you did, we flip it on its head. And so we show you your brilliant moves, your best moves. And we have coach say something encouraging. You know, losing just part of learning like keep it up, that type of thing. That change alone was pretty dramatic for us. It grew game reviews by 25%, subscriptions by 20%
design motivation
0:13:34
Our reading
Only 30 to 50 percent of product experiments win, because consumer behaviour is too unpredictable to be predicted from a hypothesis.
Their wordsI mean in my experience the typical win rate and I hate to use that term for experiments is is often something like 30 to 50%. Like usually you're not actually get like you're trying a bunch of things a lot of hypotheses turn out not to be true. you know, consumer products are very unpredictable like that.
product management
0:16:13
Our reading
A rising share of statistically insignificant experiments is the signal that a team has exploited an area too far and should go back to exploring.
Their wordsAnd if I'm starting to see like more and more experiments that are not statistically significant, that may be a signal to me to say, okay, we might have kind of tried to exploit a little bit too far. Like there might not be as much juice to squeeze.
startups innovation
0:17:36
Our reading
Most of the questions people have about a company's data are never asked, and giving them a machine to ask instead of a colleague uncovers them.
Their wordsAnd I think what's also kind of interesting is that just human nature is that if you have a question that you feel like, you know, you might be a bit embarrassed to ask or you don't want to bother someone, you just don't ask the question, right? And so by the nature of having these tools, you get actually a pretty large explosion of questions being asked.
LLMs behavioural science
0:19:48
Our reading
AI has made prototyping fast but has not yet joined it to the workflow, so at any real scale the handoffs between functions are still there.
Their wordsI would say though that something that is kind of annoying to me is that we haven't yet figured out the bridging from the tinkering to the workflow quite as seamlessly as I would like.
developer tools

Julie ZhuoCo-founder of Sundial; former vice president of product design at Facebook; author of The Making of a Manager; writes The Looking Glass.21 Sept 2025 · 1h 36m · 22 korrentsOn management, design and product management

From managing people to managing AI: The leadership skills everyone needs now | Julie Zhuo

Julie Zhuo

Our reading — their words are on the recording

0:09:22
Our reading
Managing agents is the same job as managing people: fix the outcome, work out what your resources are good at, and design the process.
Their wordsmanagement is just about in my mind having an outcome. So you want to get something done. That's the thing. You have a northstar. You have a vision and you're just trying to figure out how to use the resources that you have to get that thing done.
design
0:10:14
Our reading
Models have personalities the way people do, and using them well means developing an intuition for which one to reach for.
Their wordsAnd you have to understand the strengths of of you know used to be people but now it's basically models and different models have different strengths. So it's like they have different personalities
LLMs
0:13:49
Our reading
If you cannot say crisply what success looks like, you will not get great work — out of a team or out of an AI.
Their wordsif you're really unclear about what success looks like the prompt, you're probably not going to get the most amazing work. Um I think that's true for managing teams and it's very much true for managing AIs.
management
0:15:20
Our reading
AI will not make you world-class at a skill, but it takes a near-beginner to roughly the sixtieth or seventieth percentile of it today.
Their wordsbut if I was, you know, at the zero or 10th percentile, it can certainly get me even today very quickly up to like the 60th 70th in terms of um what the state of the art is.
AI and human skill
0:15:36
Our reading
AI has made individuals capable enough that the boundaries between engineer, designer, researcher and product manager should be dissolved.
Their wordsAnd so the main thing that I felt so excited about and this is something I tell my team all the time is we need to dissolve the boundaries of these traditional roles.
design product management
0:17:17
Our reading
Putting a product manager on a team invites everyone else to delegate the product thinking away, which is why she does not hire them.
Their wordsI find that sometimes when you have like a designer or product manager and let's say I'm an engineer, then when I have a problem like, oh, I need to figure out the product definition, my default will be, well, I've got these people and that's kind of their job description, so I'm just going to delegate that to them.
product management

Rahul VohraFounder and chief executive of Superhuman, the email client; previously founder of Rapportive, which he sold to LinkedIn; a professional game designer before that.23 Mar 2025 · 1h 25m · 24 korrentsOn product management, startups and design

Superhuman's secret to success | Rahul Vohra (CEO and founder)

Rahul Vohra

Our reading — their words are on the recording

0:10:12
Our reading
Referral growth is driven by whales — single users who invite fifty or a hundred people — not by many users each inviting a few.
Their wordswe've definitely found that there are whales to use the gaming terminology that one person is going to be responsible for inviting 25, 50, 100 people
0:15:25
Our reading
Everything a company can build is either solution deepening or market widening, and doing one means not doing the other.
Their wordsyou can classify anything that you build in a company into one of two categories. Solution deepening and market widening. Now solution deepening means making your product better for its existing users but not making it available to more users. Whereas market widening means making your product available to more users but not making the product itself any better.
product management
0:17:35
Our reading
A company that looks to its users as though it has stopped shipping is usually widening its market, and grinding through that is worth it.
Their wordsBut this is the hard part. When you're when you're doing that market widening, you're not solution deepening. And so your perceived product velocity may decrease. You can avoid some of these things with some smart technology decisions, but mostly you just have to grind through it and it is worth it to get to the other side.
ambition product management
0:19:21
Our reading
A company deserves everyone in it, the chief executive included, to spend as much time as possible in their zone of genius — which is an org design problem.
Their wordsAnd number two, the superhuman opportunity deserves everyone who works at the company to spend as much time as possible in their zone of genius. And so that includes me as well as everybody else. So what I did is I hired a really great president. I went from eight direct reports to two.
design
0:20:46
Our reading
Your calendar records what you thought you were going to do; only a log of every task switch records what you actually did.
Their wordsSo, this is a technique that I call the switch log. And it's born out of the observation that your calendar says what you thought you were going to do, but it's really only your trail of work that describes what you actually did.
management
0:22:45
Our reading
The right way to work is to do whatever feels right for as long as it feels right, and read your time back at the end of the week — not to obey a timetable.
Their wordsWhat I'm saying is do what feels right for as long as as it feels right to do. Then at the end of the week you can see where your time is going.

Elena VernaLeads growth at Lovable; previously led growth at Miro, Amplitude, Dropbox and SurveyMonkey.19 Jan 2025 · 1h 35m · 26 korrentsOn startups, design and hiring

10 growth tactics that never work | Elena Verna (Amplitude, Miro, Dropbox, SurveyMonkey)

Elena Verna