Lenny's Podcast: Product | Career | Growth
00:34:30 · Tara Seshan
[00:34:30] S0: Yeah, I think one of the most interesting things here is that one of the goals of launching Work in ChatGPT web and launching it in the desktop app and bringing these things together was to look at those billion people who are using ChatGPT and bring them more and more of the agent's power. If you think about the first era of AI products as chat, the second era of these products is clearly working with agents and primarily has been coding agents. We'd like to bring it to more domains certainly, like knowledge work. And that is part of the goal of giving all these billion chat users the power of Work. Certainly the product challenge that's on us is, how do we not only bring it to them, but make it natural and easy to adopt, make it not a decision they have to explicitly make? We can just help them do the right thing. How do we decomplexify it so they don't need to think about things like harnesses, which feel like crazy concepts for a billion consumers to understand? So that is primarily the challenge. And then of course, that third era that might come soon is how do you work with a persistent coworker who is able to get things done with you, maybe collaboratively with other people? And so part of this challenge in the near term is we are introducing agents to a billion people who may not have experienced them yet. How do we do so in the easiest, most natural, and most usable way possible? Certainly there's a lot more for us to do to make that happen. But part of this is also a lesson I've had maybe contrasting pre-AI era or past product experience with this one, which is at previous companies, like polish was king, getting every UI interaction or getting every little thing completely right was way more important than shipping something early because time didn't make as much of a difference in terms of the outcome. And so as such, if every corner wasn't perfectly polished and everything wasn't exactly correct, you might as well not ship it. But I think what's been really compelling and interesting about this era and this product experience has been getting the product in the hands of users when you have so much conviction that, hey, it's transformative, is way better than perfect. And that urgency and that introduction of that product is so important.
00:37:02 · Tara Seshan, Lenny Rachitsky
So we have a lot to do to make it more usable and easier for chat users, certainly especially for folks who are not maybe even using it for productivity, but using it for consumer tasks. But yeah, done is better than perfect, and we have so much more to do. [00:37:20] S1: Yeah, I remember when this app first launched, there was a lot of comments about the confusion and seeing how quickly the team iterated and respond to the feedback is exactly what I'm hearing here is get it out, figure out what's not working, how people are using it, iterate quickly. Feels like that's the model now.
00:37:36 · Tara Seshan
[00:37:36] S0: And of course there are things that you can continue to iterate and get that feedback prior to launching. And there's a lot that we can and should always do better. But iterating as quickly as possible and listening to the right signals is regardless of whether that's pre-launch, post-launch, ideally pre-launch, is the key thing. I think there's this phrase which is, "Before enlightenment carry water, chop wood. Post enlightenment, carry water, chop wood," sort of thing. And actually with the Codex app, the team who initially got it up and running and were working on it were super, again, user-focused, tight iteration loop, really dogfooded the thing, mainlined the app as much as possible to get everything right. Folks started to realize that was happening externally and on Twitter and users started to really notice. But the team was always really focused on users, really focused on that iteration. And it was merely, to some extent, the market catching up, that was the change. And that process has not changed internally. Everyone still constantly uses the app. Everyone who's building it obviously is a developer using it for development and is constantly fixing not only their own problems, but trying to listen to other people in the company's problems and user problems. Actually, what's sort of remarkable is that the mode of operating hasn't changed. It's always been the same thing I had mentioned earlier. Are we elevating our mission sufficiently? Are we maximally accelerating progress and are we mainlining it as much as possible? And I think it's great that users and folks on Twitter have noticed, but that operation, that full credit to the team, that hasn't changed.
00:41:24 · Lenny Rachitsky, Tara Seshan
[00:41:24] S1: What's really interesting about this answer is the very human part of it. It's you, it's Andrew, it's Tibo, it's the team just being obsessed with the customer, the product. And it's not like AI was the answer, it's the humans that made the difference. [00:41:39] S0: Yeah. The team deserves full credit here. Everyone on the team is incredibly thoughtful and independent and to the point of there are many founders at OpenAI, almost everyone on that team, the desktop team especially, acts like founders and cares about every piece and every detail. And when they notice an area that should be better, they go build it very independently and get the thing up and running. And if it doesn't test well internally, people aren't using it, if people don't find it useful, they'll iterate on it and then finally ship it externally. But that loop is full credit to people on the team and individuals for making that happen. [00:42:20] S1: Something you touched on is this idea of roles overlapping, this idea of engineers are doing PME work, you're doing probably shipping prototypes and building, maybe shipping to production. I don't know. It feels like that also creates a lot of challenges. I hear from a lot of people, "What is my job now as a designer? What am I responsible for? What am I not responsible for? As a marketer, what am I doing?" Is that something you notice? Is that something that you're dealing with? Just any thoughts along those lines.
00:42:48 · Tara Seshan
[00:42:48] S0: I think the thing I've always liked the most about working at startups, and sometimes I've started at a startup that accidentally grew into a large company, but largely primarily working at startups, is that there are very few boundaries around your role, that everything and nothing is your responsibility. But ultimately, you're accountable for success. Actually, Stripe was very, very much this way where there are no boundaries around what a engineer could do versus a product manager could do versus a designer could do. Everyone could do anything. And so actually it feels like I've always really loved that mentality and now finally capability is catching up to that. But the thing I really care about is that someone needs to look after or have core accountability for, is this product being used by users? Is it something that people want? Is it high quality? Is it effective? And whether that person is an engineer or designer or a PM or whomever, someone is the DRI. And then whatever work needs to be done to make that possible, certainly people can pick it up based on their affinity, based on their capability. But I like a team that doesn't really mind what the boundaries are between individual roles, but everyone's just focused on making the outcome happen. The converse of this is I also really love, the craft aspects of being a PM. There are so many aspects to PM craft that I know folks like Shreyas or maybe Marty Cagan, or Shishir, all these people have really espoused that I think are wonderful. And sometimes maybe some of these questions come from, "Wait, I so love the craft of my domain. By taking this more fluid approach to teamwork and collaboration to get something done, do I lose out on getting better in polishing my craft?" And I truly don't have an answer for that question. I think it's something we're all experiencing together, which is some pieces of our craft are actually getting abstracted by models being able to do it really effectively, maybe better than individuals can. And your craft moves from being able to do that very specific task you did in the past to now applying it to some other part of the product or the discipline.
00:45:06 · Tara Seshan, Lenny Rachitsky
But yeah, that is still a question I'm thinking about, which is how do I balance my desire to be part of a team and use these tools and feel so compelled by how effective one can be now with all these products, with my love of the... Yeah, it's really fun handwriting code for an engineer all the time and one doesn't really do that anymore. [00:45:28] S1: Yes, that's where I was going to go. It's just unbelievable how different the engineering role is now. It's like you used to write code all day, that was your job and that is no longer your job, and that happened so quickly, like you do not write code. [00:45:42] S0: I see people mourn the flow state of writing code manually yourself versus now what one does. Yeah, it's a tough transition. [00:45:54] S1: Yeah. And some people love it, some people don't, and that's a whole other topic. Along those lines, something I'd like to ask people at the frontier of AI is, where do you think human brains will continue to be valuable in the future? It's impossible to predict long term, will we need humans? Hopefully. But I'd say in the, I don't know, the next couple years, just where do you think human brains will continue to be most valuable?