Instead of altering the fundamental fabric of reality, maybe it is used to create better versions of features we have used for decades. This would not necessarily be a bad outcome. I have used this example before, but the evolution of object removal tools in photo editing software is illustrative. There is no longer a need to spend hours cloning part of an image over another area and gently massaging it to look seamless. The more advanced tools we have today allow an experienced photographer to make an image they are happy with in less time, and lower barriers for newer photographers.

You’re also not learning anything this way. Part of what makes art special is that it’s difficult to make, even with all the tools right in front of you. It takes practice, it takes skill, and every time you do it, you expand on that skill. […] Generative A.I. is only about the end product, but it won’t teach you anything about the process it would take to get there.

I feel lucky that I enjoy cooking, but there are certainly days when it is a struggle. It would seem more appealing to type a prompt and make a meal appear using the ingredients I have on hand, if that were possible. But I think I would be worse off if I did. The times I have cooked while already exhausted have increased my capacity for what I can do under pressure, and lowered my self-imposed barriers. These meals have improved my ability to cook more elaborate dishes when I have more time and energy, just as those more complicated meals also make me a better cook.

I am wary of using an example like cooking because it implies a whole set of correlative arguments which are unkind and judgemental toward people who do not or cannot cook. I do not want to provide kindling for these positions.

Plenty of writing is not particularly artistic, but the mental muscle exercised by trying to get ideas into legible words is also useful when you are trying to produce works with more personality. This is true for programming, and for visual design, and for coordinating an outfit — any number of things which are sometimes individually expressive, and other times utilitarian.

This boundary only exists in these expressive forms. Nobody, really, mourns the replacement of cheques with instant transfers. We do not get better at paying our bills no matter which form they take. But we do get better at all of the things above by practicing them even when we do not want to, and when we get little creative satisfaction from the result.

Having an opinionated set of tradeoffs exposes your approach to a set of weaknesses. The more you tip the scale on one side, the weaker something else will be. That’s okay! Making those difficult choices is what people pay you for. You should be proud of your compromises. My favorite products are opinionated. They make a clear statement about what they are not good at, in favor of being much better at something else.

At Netflix, we have such a diverse population of shows in 183 countries around the world. We’re really trying to serve up lots of stories people haven’t heard before. When you go into our environment, you’re like, “Ooh, what is that?” You’re almost kind of afraid to touch it, because you’re like, “Well, I don’t want to waste my time.”That level of discovery is literally, I’m not bullshitting you, man, that’s the thing that keeps me up at night. How do I help figure out how to help people discover things, with enough evidence that they trust it? And when they click on it, they love it, and then they immediately ping their best friend, “Have you seen this documentary? It’s amazing.” And she tells her friends, and then that entire viral loop starts.

The discovery engine is very temporal. Member number 237308 could have been into [reality TV] because she or he just had a breakup. Now they just met somebody, so all of a sudden it shifts to rom-coms.Now that person that they met loves to travel. So [they might get into] travel documentaries. And now that person that they’re with, they may have a kid, so they might want more kids’ shows. So, it’s very dangerous for us to ever kind of say, “This is what you like. You have a cat. You must like cat documentaries.”

We don’t see each other, obviously, and I don’t want to social network on Netflix. But knowing other humans exist there is part of it.You answered the question absolutely perfectly. Not only because it’s your truth, but that’s what everyone says! That connection part. So another thing that goes back to your previous question, when you’re asking me what’s on my mind? It’s that. How do I help make sure that when you’re in that discovery loop, you still feel that you’re connected to others.I’m not trying to be the Goth kids on campus who are like, “I don’t care about what’s popular.” But I’m also not trying to be the super poppy kids who are always chasing trends. There’s something in between which is, “Oh, hey, I haven’t heard about that, and I kind of want to be up on it.”

I am looking forward to seeing what Apple does with this and then figuring out more, how are people going to use it? Then I think that we should have a real discussion about how Netflix does it.But to just port Netflix over? No. It’s got to make sure that it’s using the power of the system as much as humanly possible so that it’s really making that an immersive experience. I don’t want to put resources toward that right now.

The design team here at Netflix, we played a really big hand in how that worked because we had to design the back-end tool. What people don’t know about our team is 30% of our organization is actually designing and developing the software tools that we use to make the movies. We had to design a tool that allowed the teams to understand both what extra footage to shoot and how that might branch. When the Black Mirror team was trying to figure out how to make this narrative work, the software we provided really made that easier.

inside look at how Perplexity builds product—which to me feels like what the future of product development will look like for many companies:AI-first: They’ve been asking AI questions about every step of the company-building process, including “How do I launch a product?” Employees are encouraged to ask AI before bothering colleagues.Organized like slime mold: They optimize for minimizing coordination costs by parallelizing as much of each project as possible.Small teams: Their typical team is two to three people. Their AI-generated (highly rated) podcast was built and is run by just one person.Few managers: They hire self-driven ICs and actively avoid hiring people who are strongest at guiding other people’s work.A prediction for the future: Johnny said, “If I had to guess, technical PMs or engineers with product taste will become the most valuable people at a company over time.”

Typical projects we work on only have one or two people on it. The hardest projects have three or four people, max. For example, our podcast is built by one person end to end. He’s a brand designer, but he does audio engineering and he’s doing all kinds of research to figure out how to build the most interactive and interesting podcast. I don’t think a PM has stepped into that process at any point.

We leverage product management most when there’s a really difficult decision that branches into many directions, and for more involved projects.

The hardest, and most important, part of the PM’s job is having taste around use cases. With AI, there are way too many possible use cases that you could work on. So the PM has to step in and make a branching qualitative decision based on the data, user research, and so on.

a big problem with AI is how you prioritize between more productivity-based use cases versus the engaging chatbot-type use cases.

we look foremost for flexibility and initiative. The ability to build constructively in a limited-resource environment (potentially having to wear several hats) is the most important to us.

We look for strong ICs with clear quantitative impacts on users rather than within their company. If I see the terms “Agile expert” or “scrum master” in the resume, it’s probably not going to be a great fit.

My goal is to structure teams around minimizing “coordination headwind,” as described by Alex Komoroske in this deck on seeing organizations as slime mold. The rough idea is that coordination costs (caused by uncertainty and disagreements) increase with scale, and adding managers doesn’t improve things. People’s incentives become misaligned. People tend to lie to their manager, who lies to their manager. And if you want to talk to someone in another part of the org, you have to go up two levels and down two levels, asking everyone along the way.

Instead, what you want to do is keep the overall goals aligned, and parallelize projects that point toward this goal by sharing reusable guides and processes.

Perplexity has existed for less than two years, and things are changing so quickly in AI that it’s hard to commit beyond that. We create quarterly plans. Within quarters, we try to keep plans stable within a product roadmap. The roadmap has a few large projects that everyone is aware of, along with small tasks that we shift around as priorities change.

Each week we have a kickoff meeting where everyone sets high-level expectations for their week. We have a culture of setting 75% weekly goals: everyone identifies their top priority for the week and tries to hit 75% of that by the end of the week. Just a few bullet points to make sure priorities are clear during the week.

All objectives are measurable, either in terms of quantifiable thresholds or Boolean “was X completed or not.” Our objectives are very aggressive, and often at the end of the quarter we only end up completing 70% in one direction or another. The remaining 30% helps identify gaps in prioritization and staffing.

At the beginning of each project, there is a quick kickoff for alignment, and afterward, iteration occurs in an asynchronous fashion, without constraints or review processes. When individuals feel ready for feedback on designs, implementation, or final product, they share it in Slack, and other members of the team give honest and constructive feedback. Iteration happens organically as needed, and the product doesn’t get launched until it gains internal traction via dogfooding.

all teams share common top-level metrics while A/B testing within their layer of the stack. Because the product can shift so quickly, we want to avoid political issues where anyone’s identity is bound to any given component of the product.

We’ve found that when teams don’t have a PM, team members take on the PM responsibilities, like adjusting scope, making user-facing decisions, and trusting their own taste.

What’s your primary tool for task management, and bug tracking?Linear. For AI products, the line between tasks, bugs, and projects becomes blurred, but we’ve found many concepts in Linear, like Leads, Triage, Sizing, etc., to be extremely important. A favorite feature of mine is auto-archiving—if a task hasn’t been mentioned in a while, chances are it’s not actually important.The primary tool we use to store sources of truth like roadmaps and milestone planning is Notion. We use Notion during development for design docs and RFCs, and afterward for documentation, postmortems, and historical records. Putting thoughts on paper (documenting chain-of-thought) leads to much clearer decision-making, and makes it easier to align async and avoid meetings.Unwrap.ai is a tool we’ve also recently introduced to consolidate, document, and quantify qualitative feedback. Because of the nature of AI, many issues are not always deterministic enough to classify as bugs. Unwrap groups individual pieces of feedback into more concrete themes and areas of improvement.

High-level objectives and directions come top-down, but a large amount of new ideas are floated bottom-up. We believe strongly that engineering and design should have ownership over ideas and details, especially for an AI product where the constraints are not known until ideas are turned into code and mock-ups.

Big challenges today revolve around scaling from our current size to the next level, both on the hiring side and in execution and planning. We don’t want to lose our core identity of working in a very flat and collaborative environment. Even small decisions, like how to organize Slack and Linear, can be tough to scale. Trying to stay transparent and scale the number of channels and projects without causing notifications to explode is something we’re currently trying to figure out.

Maybe one frame is through taking control of your own personal development and learning: after all “learning is the one thing your employer can’t take away from you”

Over the years we’ve seen the rise of bro-etry and cringe “thought leadership” and crying CEOs. When I scroll my feed I have to sidestep the clearly threadboi and #personalbrand engagement-farming posts and try and focus on the real content.

Networking is useful, but distasteful to many. Instead, participating in self-directed learning communities is networking

“Don’t become a marketing manager, become someone who knows how to run user research”

Describe things that someone can explain to someone else, or you'll miss out on word-of-mouth growth. Imagine you wandered into some party and met an investor/donor/customer named Emily. Even if you're the most persuasive person ever and she walks away from the conversation energized and excited, your time is wasted because Emily can't explain to her coworkers/friends/legislative-body what specifically she's excited about.

If Emily is a potential customer and all she heard was nothing-language, then you've gained no information. She might be interested! But that interest might only be in something she's imagined — not what you're actually making.

Nothing-language is describing your product as "an investigation into how we generate dispersed intimacy, signify alliance, and physical representations of our digital coordination praxis"1 instead of saying you're an investment fund. If you're going to "revolutionize", "create the operating system for", "build at the intersection between", "empower", "democratize", "individually flourish", or "be interdisciplinary", the universe should pause, rewind, and let you explain again. It's kind and wants you to succeed.

Be boring. Say you're "plaid for messaging apps" or "a figma plugin that generates svg icons from gpt-3" or "chrome extension that adds cmd-k to every website".

Some of the topics I touch on: Why I believe Vision Pro may be an over-engineered “devkit” The genius & audacity behind some of Apple’s hardware decisions Gaze & pinch is an incredible UI superpower and major industry ah-ha moment Why the Vision Pro software/content story is so dull and unimaginative Why most people won’t use Vision Pro for watching TV/movies Apple’s bet in immersive video is a total game-changer for live sports Why I returned my Vision Pro… and my Top 10 wishlist to reconsider Apple’s VR debut is the best thing that ever happened to Oculus/Meta My unsolicited product advice to Meta for Quest Pro 2 and beyond

Apple really played it safe in the design of this first VR product by over-engineering it. For starters, Vision Pro ships with more sensors than what’s likely necessary to deliver Apple’s intended experience. This is typical in a first-generation product that’s been under development for so many years. It makes Vision Pro start to feel like a devkit.

A sensor party: 6 tracking cameras, 2 passthrough cameras, 2 depth sensors(plus 4 eye-tracking cameras not shown)

it’s easy to understand two particularly important decisions Apple made for the Vision Pro launch: Designing an incredible in-store Vision Pro demo experience, with the primary goal of getting as many people as possible to experience the magic of VR through Apple’s lenses — most of whom have no intention to even consider a $4,000 purchase. The demo is only secondarily focused on actually selling Vision Pro headsets. Launching an iconic woven strap that photographs beautifully even though this strap simply isn’t comfortable enough for the vast majority of head shapes. It’s easy to conclude that this decision paid off because nearly every bit of media coverage (including and especially third-party reviews on YouTube) uses the woven strap despite the fact that it’s less comfortable than the dual loop strap that’s “hidden in the box”.

Apple’s relentless and uncompromising hardware insanity is largely what made it possible for such a high-res display to exist in a VR headset, and it’s clear that this product couldn’t possibly have launched much sooner than 2024 for one simple limiting factor — the maturity of micro-OLED displays plus the existence of power-efficient chipsets that can deliver the heavy compute required to drive this kind of display (i.e. the M2).

Building something valuable is no longer about validating a novel idea as fast as possible. Instead, the modern MVP exercise is about building a version of an idea that is different from and better than what exists today. Most of us aren’t building for a net-new market. Rather, we’re finding opportunities to improve existing categories. We need an MVP concept that helps founders and product leaders iterate on their early ideas to compete in an existing market.

It’s not good enough to be first with an idea. You have to out-execute from day 1.

The MVP as a practice of building a hacky product as quickly and cheaply as possible to validate the product does no longer work. Many product categories are already saturated with a variety of alternatives, and to truly test the viability of any new idea you need to build something that is substantially better.

Airbnb wanted to build a service that relied on people being comfortable spending the night at a stranger’s house. When they started in 2009, it wasn’t obvious if people were ready for this. Today, it’s obvious that it works, so they wouldn’t need to validate the idea. A similar analogy works for Lyft when they started exploring ridesharing as a concept.

Today, the MVP is no longer about validating a novel idea as quickly as possible. Rather, its aim is to create a compelling product that draws in the early users in order to gather feedback that you then use to sharpen the product into the best version of many.

If you look at successful companies that have IPO'd in the recent years–Zoom, Slack, TikTok, Snowflake, Robinhood–you see examples not of novel ideas, but of these highly-refined ideas.Since many of us are building in a crowded market, the bar for a competitive, public-ready MVP is much higher than the MVP for a novel idea, since users have options. To get to this high bar, we have to spend more time refining the initial version.

The original MVP idea can still work if you’re in the fortunate position of creating a wholly new category of product or work with new technology platforms, but that becomes rarer and rarer as time goes on.

Let’s jump over the regular startup journey that you might take today when building a new product:You start with the idea on how you want to improve on existing products in a category.You build your first prototype.You iterate with your vision and based on feedback from early users.You get an inkling of product market fit and traction.Optional: You start fundraising (with demonstrable traction).Optional: You scale your team, improve the product, and go to market.

In today’s landscape, you’re likely competing against many other products. To win, you have to build a product that provides more value to your users than your competition does.To be able to do this with limited resources, you must scope down your audience (and thus your ambitions) as much as possible to make competing easier, and aim to solve the problems of specific people.

When we started Linear, our vision was to become the standard of how software is built. This is not really something you can expect to do during your early startup journey, let alone in an MVP. But you should demonstrate you have the ability to achieve your bigger vision via your early bets. We chose to do this by focusing on IC’s at small startups. We started with the smallest atomic unit of work they actually needed help with: issue tracking.

We knew we wanted our product to demonstrate three values:It should be as fast as possible (local data storage, no page reloads, available offline).It should be modern (keyboard shortcuts, command menu, contextual menus).It should be multiplayer (real-time sync and teammates presence).

Remember, you’re likely not building a revolutionary or novel product. You’re unlikely to go viral with your announcement, so you need a network of people who understand the “why” behind your product to help spread the word to drive people to sign up. Any product category has many people who are frustrated with the existing tools or ways of working. Ideally you find and are able to reach out to those people.

Once you have a bunch of people on your waitlist, you need to invite the right users at each stage of your iteration. You want to invite people who are likely to be happy with the limited set of features you’ve built so far. Otherwise, they’ll churn straight away and you’ll learn nothing.

To recap:Narrow down your initial audience and build for them: Figure out who you're building the product for and make the target audience as small as possible before expanding.Build and leverage your waitlist: The waitlist is the grinding stone with which you can sharpen your idea into something truly valuable that will succeed at market, so use it effectively.Trust your gut and validate demand with your users: Talk, talk, talk to your users and find out how invested in the product they are (and if they’d be willing to pay)

Imagine, for example, that you were thinking of starting Netflix back when it was founded in 1997. How would content providers, distribution channels, and competitors respond? How soon would technology develop to open a hidden door and let you distribute online instead of by mail? Or consider Dropbox in 2007. Dozens of cloud storage companies had been started before. What mistakes had they made? How would incumbents like Amazon and Google respond? How would new platforms like mobile affect you?

When you’re starting out, it’s impossible to completely map out the idea maze. But there are some places you can look for help: History. If your idea has been tried before (and almost all good ideas have), you should figure out what the previous attempts did right and wrong. A lot of this knowledge exists only in the brains of practitioners, which is one of many reasons why “stealth mode” is a bad idea. The benefits of learning about the maze generally far outweigh the risks of having your idea stolen. Analogy. You can also build the maze by analogy to similar businesses. If you are building a “peer economy” company it can be useful to look at what Airbnb did right. If you are building a marketplace you should understand eBay’s beginnings. Etc.

Muse as a brand and a product represented something aspirational. People want to be deeper thinkers, to be more strategic, and to use cool, status-quo challenging software made by small passionate teams. These kinds of aspirations are easier to indulge in times of plenty. But once you're getting laid off from your high-paying tech job, or struggling to raise your next financing round, or scrambling to protect your kids' college fund from runaway inflation and uncertain markets... I guess you don't have time to be excited about cool demos on Twitter and thoughtful podcasts on product design.

I’d speculate that another factor is the half-life of cool new productivity software. Evernote, Slack, Notion, Roam, Craft, and many others seem to get pretty far on community excitement for their first few years. After that, I think you have to be left with software that serves a deep and hard-to-replace purpose in people’s lives. Muse got there for a few thousand people, but the economics of prosumer software means that just isn’t enough. You need tens of thousands, hundreds of thousands, to make the cost of development sustainable.

We envisioned Muse as the perfect combination of the freeform elements of a whiteboard, the structured text-heavy style of Notion or Google Docs, and the sense of place you get from a “virtual office” ala group chat. As a way to asynchronously trade ideas and inspiration, sketch out project ideas, and explore possibilities, the multiplayer Muse experience is, in my honest opinion, unparalleled for small creative teams working remotely.

But friction began almost immediately. The team lead or organizer was usually the one bringing Muse to the team, and they were already a fan of its approach. But the other team members are generally a little annoyed to have to learn any new tool, and Muse’s steeper learning curve only made that worse. Those team members would push the problem back to the team lead, treating them as customer support (rather than contacting us directly for help). The team lead often felt like too much of the burden of pushing Muse adoption was on their shoulders. This was in addition to the obvious product gaps, like: no support for the web or Windows; minimal or no integration with other key tools like Notion and Google Docs; and no permissions or support for multiple workspaces. Had we raised $10M back during the cash party of 2020–2021, we could have hired the 15+ person team that would have been necessary to build all of that. But with only seven people (we had added two more people to the team in 2021–2022), it just wasn’t feasible.

We neither focused on a particular vertical (academics, designers, authors...) or a narrow use case (PDF reading/annotation, collaborative whiteboarding, design sketching...). That meant we were always spread pretty thin in terms of feature development, and marketing was difficult even over and above the problem of explaining canvas software and digital thinking tools.

being general-purpose was in its blood from birth. Part of it was maker's hubris: don't we always dream of general-purpose tools that will be everything to everyone? And part of it was that it's truly the case that Muse excels at the ability to combine together so many different related knowledge tasks and media types into a single, minimal, powerful canvas. Not sure what I would do differently here, even with the benefit of hindsight.

Muse built a lot of its reputation on being principled, but we were maybe too cautious to do the mercenary things that help you succeed. A good example here is asking users for ratings; I felt like this was not to user benefit and distracting when the user is trying to use your app. Our App Store rating was on the low side (~3.9 stars) for most of our existence. When we finally added the standard prompt-for-rating dialog, it instantly shot up to ~4.7 stars. This was a small example of being too principled about doing good for the user, and not thinking about what would benefit our business.

Growing the team slowly was a delight. At several previous ventures, I've onboard people in the hiring-is-job-one environment of a growth startup. At Muse, we started with three founders and then hired roughly one person per year. This was absolutely fantastic for being able to really take our time to find the perfect person for the role, and then for that person to have tons of time to onboard and find their footing on the team before anyone new showed up. The resulting team was the best I've ever worked on, with minimal deadweight or emotional baggage.

ultimately your product does have to have some web presence. My biggest regret is not building a simple share-to-web function early on, which could have created some virality and a great deal of utility for users as well.

In terms of development speed, quality of the resulting product, hardware integration, and a million other things: native app development wins.

After decades working in product development, being on the marketing/brand/growth/storytelling side was a huge personal challenge for me. But I feel like I managed to grow into the role and find my own approach (podcasting, demo videos, etc) to create a beacon to attract potential customers to our product.

when it comes time for an individual or a team to sit down and sketch out the beginnings of a new business, a new book, a new piece of art—this almost never happens at a computer. Or if it does, it’s a cobbled-together collection of tools like Google Docs and Zoom which aren’t really made for this critical part of the creative lifecycle.

any given business will find a small number of highly-effective channels, and the rest don't matter. For Heroku, that was attending developer conferences and getting blog posts on Hacker News. For another business it might be YouTube influencer sponsorships and print ads in a niche magazine. So I set about systematically testing many channels.

The most powerful thing a product can do is give its user a premise.1 A premise is the foundational belief that shapes a user’s behavior. A premise can normalize actions that people otherwise might not take, held back by some existing norm

AirBnb. The premise: It’s ok to stay in strangers’ homes.

the idea of staying in strangers’ homes for short stays was doubted even by the founders. Crashing in someone’s spare room wasn’t unheard of, but it might be seen as weird, taboo, or even dangerous.

Bumble. The premise: It’s ok for women to ask men out.

The best way to follow through on a premise is to make it the core feature of the app. Bumble did, requiring that women make the first move on the app. A woman would be presented with a list of her matches and would have to make the first "move" before men could reply. This of course became a powerful differentiating feature and marketing hook.

Substack. The premise: It’s ok to charge for your writing.

Substack's premise aimed to normalize the hardest part of internet writing: getting paid. They aimed to show that independent authors could succeed at making a living (and subscription models aligned with this ethos). In doing so, Substack also made the less-hard parts of internet writing even easier. You could start a newsletter and keep it free until you felt confident about going paid. This not only normalized the end goal but also lowered the barrier to getting started.

A premise is valuable not only for “products,” but also for experiences.As I recently shouted, people still underestimate the power of giving a social event a premise. Hackathons, housewarmings, happy hours and the like are hangouts with a narrative. They have a good premise — a specific context that makes it more comfortable to do something that can be hard: socialize. (Side note: some of the best tv series and films are built on great premises.)

Premises work best on end consumers, prosumers, small business freelancers, and the like. Many two-sided marketplaces serving two of these stakeholder groups tend to have a good premise. For example, Kickstarter's premise for the creator might be: It’s ok to ask for money before you've built a product.

in their efforts to provide better products than their competitors and earn higher prices and margins, suppliers often “overshoot” their market: They give customers more than they need or ultimately are willing to pay for. And more importantly, it means that disruptive technologies that may underperform today, relative to what users in the market demand, may be fully performance-competitive in that same market tomorrow. This was the basis for insisting that the iPhone must have a low-price model: surely Apple would soon run out of new technology to justify the prices it charged for high-end iPhones, and consumers would start buying much cheaper Android phones instead! In fact, as I discussed in after January’s earnings results, the company has gone in the other direction: more devices per customer, higher prices per device, and an increased focus on ongoing revenue from those same customers.

Apple seems to have mostly saturated the high end, slowly adding switchers even as existing iPhone users hold on to their phones longer; what is not happening, though, is what disruption predicts: Apple isn’t losing customers to low-cost competitors for having “overshot” and overpriced its phones. It seems my thesis was right: a superior experience can never be too good — or perhaps I didn’t go far enough.

Jeff Bezos has been writing an annual letter to shareholders since 1997, and he attaches that original letter to one he pens every year. It included this section entitled Obsess Over Customers: From the beginning, our focus has been on offering our customers compelling value. We realized that the Web was, and still is, the World Wide Wait. Therefore, we set out to offer customers something they simply could not get any other way, and began serving them with books. We brought them much more selection than was possible in a physical store (our store would now occupy 6 football fields), and presented it in a useful, easy-to-search, and easy-to-browse format in a store open 365 days a year, 24 hours a day. We maintained a dogged focus on improving the shopping experience, and in 1997 substantially enhanced our store. We now offer customers gift certificates, 1-Click shopping, and vastly more reviews, content, browsing options, and recommendation features. We dramatically lowered prices, further increasing customer value. Word of mouth remains the most powerful customer acquisition tool we have, and we are grateful for the trust our customers have placed in us. Repeat purchases and word of mouth have combined to make Amazon.com the market leader in online bookselling.

This year, after highlighting just how much customers love Amazon (answer: a lot), Bezos wrote: One thing I love about customers is that they are divinely discontent. Their expectations are never static — they go up. It’s human nature. We didn’t ascend from our hunter-gatherer days by being satisfied. People have a voracious appetite for a better way, and yesterday’s ‘wow’ quickly becomes today’s ‘ordinary’. I see that cycle of improvement happening at a faster rate than ever before. It may be because customers have such easy access to more information than ever before — in only a few seconds and with a couple taps on their phones, customers can read reviews, compare prices from multiple retailers, see whether something’s in stock, find out how fast it will ship or be available for pick-up, and more. These examples are from retail, but I sense that the same customer empowerment phenomenon is happening broadly across everything we do at Amazon and most other industries as well. You cannot rest on your laurels in this world. Customers won’t have it.

when it comes to Internet-based services, this customer focus does not come at the expense of a focus on infrastructure or distribution or suppliers: while those were the means to customers in the analog world, in the online world controlling the customer relationship gives a company power over its suppliers, the capital to build out infrastructure, and control over distribution. Bezos is not so much choosing to prioritize customers insomuch as he has unlocked the key to controlling value chains in an era of aggregation.

consumer expectations are not static: they are, as Bezos’ memorably states, “divinely discontent”. What is amazing today is table stakes tomorrow, and, perhaps surprisingly, that makes for a tremendous business opportunity: if your company is predicated on delivering the best possible experience for consumers, then your company will never achieve its goal.

In the case of Amazon, that this unattainable and ever-changing objective is embedded in the company’s culture is, in conjunction with the company’s demonstrated ability to spin up new businesses on the profits of established ones, a sort of perpetual motion machine

Owning the customer relationship by means of delivering a superior experience is how these companies became dominant, and, when they fall, it will be because consumers deserted them, either because the companies lost control of the user experience (a danger for Facebook and Google), or because a paradigm shift made new experiences matter more (a danger for Google and Apple).

what I cheered as an analyst was Altman’s clear articulation of the company’s priorities: lower price first, speed later. You can certainly debate whether that is the right set of priorities (I think it is, because the biggest need now is for increased experimentation, not optimization), but what I appreciated was the clarity.

The fact that Microsoft is benefiting from OpenAI is obvious; what this makes clear is that OpenAI uniquely benefits from Microsoft as well, in a way they would not from another cloud provider: because Microsoft is also a product company investing in the infrastructure to run OpenAI’s models for said products, it can afford to optimize and invest ahead of usage in a way that OpenAI alone, even with the support of another cloud provider, could not. In this case that is paying off in developers needing to pay less, or, ideally, have more latitude to discover use cases that result in them paying far more because usage is exploding.

You can, in effect, program a GPT, with language, just by talking to it. It’s easy to customize the behavior so that it fits what you want. This makes building them very accessible, and it gives agency to everyone.

Stephen Wolfram explained: For decades there’s been a dichotomy in thinking about AI between “statistical approaches” of the kind ChatGPT uses, and “symbolic approaches” that are in effect the starting point for Wolfram|Alpha. But now—thanks to the success of ChatGPT—as well as all the work we’ve done in making Wolfram|Alpha understand natural language—there’s finally the opportunity to combine these to make something much stronger than either could ever achieve on their own.

This new model somewhat alleviates the problem: now, instead of having to select the correct plug-in (and thus restart your chat), you simply go directly to the GPT in question. In other words, if I want to create a poster, I don’t enable the Canva plugin in ChatGPT, I go to Canva GPT in the sidebar. Notice that this doesn’t actually solve the problem of needing to have selected the right tool; what it does do is make the choice more apparent to the user at a more appropriate stage in the process, and that’s no small thing.

ChatGPT will seamlessly switch between text generation, image generation, and web browsing, without the user needing to change context. What is necessary for the plug-in/GPT idea to ultimately take root is for the same capabilities to be extended broadly: if my conversation involved math, ChatGPT should know to use Wolfram|Alpha on its own, without me adding the plug-in or going to a specialized GPT.

the obvious technical challenges of properly exposing capabilities and training the model to know when to invoke those capabilities are a textbook example of Professor Clayton Christensen’s theory of integration and modularity, wherein integration works better when a product isn’t good enough; it is only when a product exceeds expectation that there is room for standardization and modularity.

To summarize the argument, consumers care about things in ways that are inconsistent with whatever price you might attach to their utility, they prioritize ease-of-use, and they care about the quality of the user experience and are thus especially bothered by the seams inherent in a modular solution. This means that integrated solutions win because nothing is ever “good enough”

the fact of the matter is that a lot of people use ChatGPT for information despite the fact it has a well-documented flaw when it comes to the truth; that flaw is acceptable, because to the customer ease-of-use is worth the loss of accuracy. Or look at plug-ins: the concept as originally implemented has already been abandoned, because the complexity in the user interface was more detrimental than whatever utility might have been possible. It seems likely this pattern will continue: of course customers will say that they want accuracy and 3rd-party tools; their actions will continue to demonstrate that convenience and ease-of-use matter most.

There are four signs your idea has legs:People pay you money: Several people start to pay for your product, ideally people you don’t have a direct connection toContinued usage: People continue to use your prototype product, even if it’s hackyStrong emotion: You’re hearing hatred for the incumbents (i.e. pain) or a deep and strong emotional reaction to your idea (i.e. pull)Cold inbound interest: You’re seeing cold inbound interest in your product

Every prosumer collaboration product, including Figma, Notion, Coda, Airtable, Miro, and Slack, spent three to four years wandering in the dark until they stumbled on something that clicked.

Oh ElonWell, look, if I were the newly hired chief executive officer of a social media company, and if the directors and shareholders who brought me in as CEO had told me that my main mission was to turn around the company’s precarious financial situation by improving our position with advertisers, and if I spent my first few weeks reassuring advertisers and rebuilding relationships and talking up our site’s unique audience and powerful engagement, and then one day my head of software engineering came to me and said “hey boss, too many people were too engaged with too many posts, so I had to limit everyone’s ability to view posts on our site, just FYI,” I would … probably … fire ... him?

I mean I suppose I might ask questions like “Is this because of some technological limitation on our system? Is it because you were monkeying with the code without understanding it? Is it because you tried to stop people from reading the site without logging in, 3 and messed up and stopped them from reading the site even when they logged in? Is it because you fired and demoralized too many engineers so no one was left to keep the systems running normally? Is it because you forgot to pay the cloud bills? Is it because deep down you don’t like it when people read posts on our site and you want to stop them, or you don’t like relying on ad revenue and want to sabotage my ability to sell ads?”

no matter what the answers are, this guy’s gotta go. If you are in charge of the software engineers at a social media site, and you make it so that people can’t read the site, that’s bad.

Over the past 10 days, [Ultimate Fighting Championship President Dana] White said he, Mr. Musk and [Mark] Zuckerberg — aided by advisers — have negotiated behind the scenes and are inching toward physical combat. While there are no guarantees a match will happen, the broad contours of an event are taking shape, said Mr. White and three people with knowledge of the discussions.People keep emailing to ask about, like, the fiduciary duties and securities-law disclosure issues here, but I’m gonna wait until they’re in the octagon before I worry about that stuff

Prompt engineers not only need to get the model to respond to a given question but also structure the output in a parsable way (such as JSON), in case it needs to be rendered in some UI components or be chained into the input of a future LLM query. They scaffold the raw input that is fed into an LLM so the end user doesn’t need to spend time thinking about prompting at all.

From the user’s side, it’s hard to decide what to ask while providing the right amount of context.From the developer’s side, two problems arise. It’s hard to monitor natural language queries and understand how users are interacting with your product. It’s also hard to guarantee that an LLM can successfully complete an arbitrary query. This is especially true for agentic workflows, which are incredibly brittle in practice.

When we speak to other people, there is a shared context that we communicate under. We’re not just exchanging words, but a larger information stream that also includes intonation while speaking, hand gestures, memories of each other, and more. LLMs unfortunately cannot understand most of this context and therefore, can only do as much as is described by the prompt

most people use LLMs for ~4 basic natural language tasks, rarely taking advantage of the conversational back-and-forth built into chat systems:Summarization: Summarizing a large amount of information or text into a concise yet comprehensive summary. This is useful for quickly digesting information from long articles, documents or conversations. An AI system needs to understand the key ideas, concepts and themes to produce a good summary.ELI5 (Explain Like I'm 5): Explaining a complex concept in a simple, easy-to-understand manner without any jargon. The goal is to make an explanation clear and simple enough for a broad, non-expert audience.Perspectives: Providing multiple perspectives or opinions on a topic. This could include personal perspectives from various stakeholders, experts with different viewpoints, or just a range of ways a topic can be interpreted based on different experiences and backgrounds. In other words, “what would ___ do?”Contextual Responses: Responding to a user or situation in an appropriate, contextualized manner (via email, message, etc.). Contextual responses should feel organic and on-topic, as if provided by another person participating in the same conversation.

Prompting nearly always gets in the way because it requires the user to think. End users ultimately do not wish to confront an empty text box in accomplishing their goals. Buttons and other interactive design elements make life easier.The interface makes all the difference in crafting an AI system that augments and amplifies human capabilities rather than adding additional cognitive load.Similar to standup comedy, delightful LLM-powered experiences require a subversion of expectation.

Users will expect the usual drudge of drafting an email or searching for a nearby restaurant, but instead will be surprised by the amount of work that has already been done for them from the moment that their intent is made clear. For example, it would a great experience to discover pre-written email drafts or carefully crafted restaurant and meal recommendations that match your personal taste.If you still need to use a text input box, at a minimum, also provide some buttons to auto-fill the prompt box. The buttons can pass LLM-generated questions to the prompt box.

The VP in charge of Google Plus hosted the Friday all-hands several times to get us all excited about what they were building. It was obvious to me and many others that there was no reason for people already on Facebook to switch from Facebook. Someone asked a direct question, but the VP deflected and talked about how easy it would be to group your friends with the Circles feature — which was not at all a reason to switch.It seemed like Google didn’t have the processes or experience to get the product strategy right. “Who are our potential users and what does it take to win them?” is product strategy 101. Maybe someone raised this question in an exec review, but it didn’t become a launch blocker. Google+ never took off, and was eventually shut down.

If Google didn’t start with a conviction that they needed the product, it makes sense that they wouldn’t have the stamina to keep iterating and investing. Most other companies don’t have the money to build and launch products with such little conviction and oversight. Other companies need their products to succeed, so they try harder & smarter to make the products successful.

IME people often don’t realize that product strategies are actually way more important and influential than company strategies. Simply because it’s the products that have an impact on people’s lives, not the company.

Google has a company strategy, but they don’t make product strategies.

Google’s company strategy is “Hire all the smart people.” Hire all the smart people and let them build. Hire all the smart people so they can’t work at a competitor. Hire all the smart people even if we don’t have something important for them to work on.Google acts like a venture capitalist, investing in promising people with the expectation that most will fail. They invest broadly in search of the idea that will deliver 100x. Let 1000 flowers bloom, and see which are the best.

Meta, today, has roughly the right price and is working forward to the right device: Apple has started with the right device and will work back to the right price. Meta is trying to catalyse an ecosystem while we wait for the right hardware - Apple is trying to catalyse an ecosystem while we wait for the right price.

one of the things I wondered before the event was how Apple would show a 3D experience in 2D. Meta shows either screenshots from within the system (with the low visual quality inherent in the spec you can make and sell for $500) or shots of someone wearing the headset and grinning - neither are satisfactory. Apple shows the person in the room, with the virtual stuff as though it was really there, because it looks as though it is.

For Meta, the device places you in ‘the metaverse’ and there could be many experiences within that. For Apple, this device itself doesn’t take you anywhere - it’s a screen and there could be five different ‘metaverse’ apps. This iPhone was a piece of glass that could be anything - this is trying to be a piece of glass that can show anything.

A lot of what Apple shows is possibility and experiment - it could be this, this or that, just as when Apple launched the watch it suggested it as fitness, social or fashion, and it turn out to work best for fitness (and is now a huge business).

Mark Zuckerberg, speaking to a Meta all-hands after Apple’s event, made the perfectly reasonable point that Apple hasn’t shown much that no-one had thought of before - there’s no ‘magic’ invention. Everyone already knows we need better screens, eye-tracking and hand-tracking, in a thin and light device.

It’s worth remembering that Meta isn’t in this to make a games device, nor really to sell devices per se - rather, the thesis is that if VR is the next platform, Meta has to make sure it isn’t controlled by a platform owner who can screw them, as Apple did with IDFA in 2021.

On the other hand, the Vision Pro is an argument that current devices just aren’t good enough to break out of the enthusiast and gaming market, incremental improvement isn’t good enough either, and you need a step change in capability.

Apple’s privacy positioning, of course, has new strategic value now that it’s selling a device you wear that’s covered in cameras

the genesis of the current wave of VR was the realisation a decade ago that the VR concepts of the 1990s would work now, and with nothing more than off-the-shelf smartphone components and gaming PCs, plus a bit more work. But ‘a bit more work’ turned out to be thirty or forty billion dollars from Meta and God only knows how much more from Apple - something over $100bn combined, almost certainly.

So it might be that a wearable screen of any kind, no matter how good, is just a staging post - the summit of a foothill on the way to the top of Everest. Maybe the real Reality device is glasses, or contact lenses projecting onto your retina, or some kind of neural connection, all of which might be a decade or decades away again, and the piece of glass in our pocket remains the right device all the way through.

I think the price and the challenge of category creation are tightly connected. Apple has decided that the capabilities of the Vision Pro are the minimum viable product - that it just isn’t worth making or selling a device without a screen so good you can’t see the pixels, pass-through where you can’t see any lag, perfect eye-tracking and perfect hand-tracking. Of course the rest of the industry would like to do that, and will in due course, but Apple has decided you must do that.

For VR, better screens are merely better, but for AR Apple thinks this this level of display system is a base below which you don’t have a product at all.

For Meta, the device places you in ‘the metaverse’ and there could be many experiences within that. For Apple, this device itself doesn’t take you anywhere - it’s a screen and there could be five different ‘metaverse’ apps. The iPhone was a piece of glass that could be anything - this is trying to be a piece of glass that can show anything.

This reminds me a little of when Meta tried to make a phone, and then a Home Screen for a phone, and Mark Zuckerberg said “your phone should be about people.” I thought “no, this is a computer, and there are many apps, some of which are about people and some of which are not.” Indeed there’s also an echo of telco thinking: on a feature phone, ‘internet stuff’ was one or two icons on your portable telephone, but on the iPhone the entire telephone was just one icon on your computer. On a Vision Pro, the ‘Meta Metaverse’ is one app amongst many. You have many apps and panels, which could be 2D or 3D, or could be spaces.

Reddit is rumored to have plans to go public, but they need better leadership than the current team. Huffman has shown no leadership skills. He doesn’t know how to read the room. Most importantly, he lacks the social empathy to lead a social platform. Even more disappointing is the lack of comments or intervention from Reddit co-founder Alexis Ohanian, the always chatty — who seems to have advice for every other founder, except for his co-founder. […] In an attempt to monetize the content generated by the community, Huffman forgot that it is the people who make the platform. The community is the platform. It is something the owners of social media platforms forget. […] It happened with MySpace. It has happened with Twitter. It is now happening with Reddit. They never learn from past mistakes. They assume that because they own the platform, they own the community. Every time they forget that important thing, they erode the community’s trust. And once that trust goes, so does the unfettered loyalty. People start looking for options.

I have zero faith in Steve Huffman’s ability to lead Reddit. What kind of chief executive officer posts this comment after a massive community backlash?

closing off 3rd party API access mostly serves an IPO, not OpenAI. If Reddit merely wanted to restrict the ability to scrape its data, they could have done so without killing off clients – e.g. via licensing deals. However, perhaps if access to training data is seen as an elbows-out brawl, I could see how Reddit would be extremely protective of its data. I mean, lyrics websites, map makers, and dictionaries go to great lengths to protect their data. It would not be a giant stretch for Reddit to do so as well.

Huffman is right that, in the end, the whole situation reflects a product problem: the native Reddit apps, both on desktop and on mobile, are ugly and difficult to use. (In particular, I find the nested comments under each post bizarrely difficult to expand or collapse; the tap targets for your fingers are microscopic.) Reddit didn’t really navigate the transition to mobile devices so much as it endured it; it’s little wonder that millions of the service’s power users have sought refuge in third-party apps with more modern designs.

It’s no surprise that Apple considered holding off on announcing the price until months after WWDC to avoid the negative headlines. In the end, the company decided the price would become an even larger target if it wasn’t revealed at the event. Consumers now have nine months to digest it before the Vision Pro goes on sale.