Behind Latent Space: Kill My SaaS, Jev & AI in 2026 | AIEi Shanghai

14,182 words · about 57 min to read

Bringing the AI Engineer conference to Shanghai

0:00 Well, this is a special podcast because it's about AIE Shanghai. AI Shanghai is the first AIE in China. Uh, it's brought to us by Standard Partners, which is one of the local partners that we have. We have a few AIES worldwide that my team doesn't run. And this is the first one in Shanghai. I've always wanted to bring AIE to China. I think there's a lot of east meets west uh and a lot of progress in China that needs to be shared and distributed among the global community.

0:28 China's super interested in us. Um, there's been many Chinese fans of the Inspace and I'll flash a few of them up on screen here on YouTube and uh, primarily I want to recognize Mang Shao who is our primary fan uh, always translating basically every episode into Chinese which I which I am super appreciative of. Um, and in general, I think I want to also congratulate and and celebrate uh the progress that China has made uh not just in open source models, but in robotics uh and a lot of other uh sort of startups uh. You know, who can remember Manis, that was started uh this time last year and then moved to Singapore?

1:06 Um and obviously Open Claw had a big run, and we talk a lot about what that like what that's like in terms of the the overall mood on the ground and how the scale of AI community is so different in China and the the type of things get adopted, as well as the, I guess, the startup culture people hear a lot about 996. We talk about the reality of that versus, uh, in a place like Cognition.

1:32 Um, and finally, we also talk a little bit about the origin story of Lat, which some of you may not have heard if you're newer to the podcast. Talk about when it was started and why it was started and how we think about running the multiple shows that we're running. Um, and a little bit about safety and alignment and all that other stuff. So, there's a little bit here for everyone. It's basically for the fans if you've been following the inspace for a while. Um, and if you're interested in AI Shanghai, it's not being live streamed, but we're going to post it up on the YouTube at some point. Starts tomorrow. So anyone here in China who's watching this, I'm really looking forward to having it. And thanks to Ming and um team for organizing all of this. Um I also have to shout out Hanu Leu who basically got this thing started. I we you know it nearly did not happen a few times but it's so so exciting to have AI in Shanghai and to bring lean space to China in general. So thanks for watching and look forward to the interview. The models are very good

2:32 at clicking through every screen of your software and then replicating it independently. Oh yeah. Right. So the moment I have access to your software, I can clone it. So good luck. There's a lot of talking heads who have never coded a single day in their lives. They're all like, "Ah, my timeline to AGI is like 2 years away. All of you are going to have not going to have jobs in the future. You need to prepare for what's next." Conveniently, whatever is next looks like their job. I I have my own Canal. I have my own Google Drive. I have my own GitHub. I'm serious. They're such good founders. They live in the wrong country. If they live in the US, they'll kill Amazon. They'll kill like Facebook. The only reason they're not richer is they live in China. AI doom.

3:11 Uh in all of human history, when a more advanced civilization comes along and meets a less advanced civilization, the less advanced civilization goes extinct. And this thing is evolving roughly 1,000

Transitioning from finance to tech and media

3:23 times faster than us. Hi, Sean. So thank you for joining me for this show. So I've been a good a longtime listener for the latent space podcast. I know that many founders in AI engineers in China as well have already learned a lot from your work and conversations on the podcast as well. And also I'm grateful that you know you are bringing the AIE the AI engineer conference to Shanghai the first time this year. So uh, I think also like several months ago, I read your piece actually on drive forth about your essay on, you know, your relationship with uh the Silicon Valley. You moved back and forth from um Singapore and here. I guess that's why, how you actually coin or invented the the role of AI engineer the last time you moved to Silicon Valley. And also this just makes me feel like it's very special, and that this time you bring the AI to to Shanghai the first. And so uh, tell us a little bit about your background and your relationship with

4:25 I, I should correct you on one thing that's that's wrong. I did not bring AI to Shanghai. Shanghai brought AI to Shanghai. Okay.

4:31 Right. Uh it's like Hanoa and like uh Leu and Mying and those those folks stand up partners. Um so I'm very grateful for them because we I always wanted to do something in China but I'm not a Chinese citizen and I have no contacts or relationships there. I think that there's a lot of interest on both sides of the world on uh US and China, China, Chinese AI in general. You know, whatever we can do to to surface like highquality conversations, um I think that AIE in China can help there. So, my TLDDR is I'm from Singapore. Uh you know, fifth generation Singaporean, sorry, fifth generation Chinese, right? Most uh Singaporean is majority Chinese. Um I think I am from people asked me like

5:17 oh

5:18 nice Chinese

5:20 I, uh, uh, so, um, and I don't know, and like, that's, that's like how it feels like to be like Chinese diaspora, right? Like, we don't know what our origins are because it's just mixed, that nobody kept any records, like nobody even knows our birthdays, like sometimes, you know? But fifth generation Singapore, uh, grew and raised up in Singapore, and, uh, went to the US for university, and, uh, did my first career in finance. I I was in uh trading and investment banking and uh hedge funds for 10 years sorry 8 years

5:57 and then switched to um tech. So I worked in uh Amazon and a few startups and then four years ago became independent role lead in space uh figured out that there was going to be this AI engineer thing and then I I started AIE.

6:12 Cool. And I know that actually you have different roles right now. You're you're doing the uh latent space podcast you're writing newsletters and also I find out that you have different roles in um several startups like connection etc. Yes.

6:26 Yeah. just wonder you know you know what your current titles or roles in different different roles and

6:33 yeah so it's very funny because I recently had to go over my taxes

6:38 Like figure out, like, what money do I have? So, Cognition is the biggest one. Is I'm an adviser? I'm still an adviser to Cognition. Uh, I was an employee for a long time, for, for, for a while. So, basically, the idea was, uh, I have three companies: I have AIE, I have Latent Space, and then I have miscellaneous it used to be Small AI, which is my personal sort of startup vehicle.

7:00 Uh, basically, got acquired into Cognition, worked there for 6 months, and then stepped back to be an adviser because AIE is now, you know, a global conference conference organization, and I had to be CEO; I couldn't be part-time employee. parttime here is very big, Fireworks is very big, Modal is very big, superbase. Um, so, uh, I think it's a very common thing if you're a Silicon Valley influencer uh, or you've been in developer relation circles for a long time. So that, that is my specialty, in which is that I am a technical, but I also write and speak, and that is a good combination of skills to have for people because any startup will want to pay you to, like, talk about their stuff. And I think, you know then, then you start working with a bunch of things. So, like, uh, a lot of, uh, this is not a normal career I actually don't even recommend it for most people but it is my role in life

Learning in public leverages the positive-sum nature of tech

7:49 that I I can advise uh a few different companies and uh work with them in in exchange for talk and that's, the that's the rough idea. I just want to deep dive a bit more into the early days of latent space, because I know I wrote read your essay that you start to, you know, learn in public and then tell everyone what you learned, uh, in the early days. And then, and then you felt the need you need to, you know, uh, transfer the conversation. You talk with different researchers online and then become the early some conversation of the latent space, probably just.

8:20 you know yeah talking about the past days how you build up latent space and

8:24 there's there's kind of two different things that you're mixing together, right? The first thing is the principle

1 Highlight · Why tech is positive-sum unlike finance

8:29 of learning in public, which is something I realized when I left finance and I worked in tech. Why is tech so much better going so much better for me? It feels so much more comfortable. Uh and the very core reason for people who are interested in both fields both are high paying jobs like uh prestigious jobs. The difference is finance is zero sum, right? If I know something and I tell you uh that that truth loses value,

8:55 right? But in tech it is most stuff is things are positive some if I know something I tell you it increases value uh and that's a very different paradigm for people who are crossing over from finance to tech and it's very liberating it means that people will get on stage and they open source their work

9:12 They share their code, they screw up, they share it that they screwed up. In finance no like you want to pretend that you never screwed up and everything is top secret, and I think that is something that I really took to heart. And I, I think I

9:26 realized that, oh the, the other thing that happened to me was my first job was at Two Sigma, which is still in finance, but I was on the software engineering side and I realized that I had a bad boss. So then I got really bored and I started to do a lot of writing and speaking because at work I wasn't able to do the things that I wanted to do cuz they didn't let me. But like obviously because I was so bored at work and then I put all my energy into the the stuff outside of work then obviously that thing took off because no one else is doing that.

9:57 And by comparison that becomes you being able to choose your own boss, right? Like most people when they have a job they join a company they are assigned a boss they assigned a team. Most of most of the time you don't even know if like the team is good or not like whatever and then you find out it's not good. You're stuck. when you learn in public you actually can choose your own boss you choose you like work for yourself choose your own boss all those things so it's very very good I think the fast forward to laten space that was created when stable diffusion happened this is before chbttt

10:29 yeah

10:29 When Stable Diffusion happened, I was in a startup that was not going very well. Uh, it's called airbite. It's still doing okay today, but nobody would call it a rocket ship. That's just...that's objectively true, and I would say that to the founders. But because I was like, "Okay, I have I...I did like some machine learning courses, but I'm not an AI expert." I am so interested in this field. There's there's only one way for me to get into the field which is to learn in public. And so that's what I did. I started a blog and I started um analyzing and learning and like writing up my learnings into a blog. And at first nobody will notice. But then eventually, if you start talking about people's things, like uh literally, Immad Mustak who's the CEO of Stability AI, which created Stable Diffusion, which is the the reason I started the blog read the blog post analyzing Stable Diffusion, and he said, "This is good."

11:16 And I think, like, that work was basically me learning AI, like the past, like, 5 years of, like, just grinding and and and writing about that. And I think that is really the, you know, like, you are not qualified. And I'm still probably not that qualified today, but I'm a bit more qualified than I used to be 4 years ago. So that's good. And I think that's the only way you can learn. Like I think um especially in Asian cultures, there's a lot of emphasis on credentialism.

11:46 Yeah.

11:46 Like right like you need that piece of paper. You need like some qualification. Like if it's not if it's not a degree, it's a certification. If it's not a certification, you must have had a job uh to do it. And how do you get the job? You must have a degree. like it's just like a infinite loop of things that basically mean that when you're 16 you need to decide what you want to do in life. But like I think life is a lot more flexible than that. Uh and you can choose to pivot if you want to. Uh you just have to be really persistent and also uh realize that just because you worked very hard, you're not entitled to win.

12:19 You have to work very hard and be good. I think a lot of people try, a lot of people fail and they're like, "Why didn't it fail?" Well, you're not good. Too bad. But some people try and they they worked and and they had judgment. Uh they really did uh work on substantial things rather than insubstantial things. Uh and that's what that's generally what happens with learning public like um

12:40 so so yeah that start they started lspace and then uh very very interestingly lspace was just a blog. It was just

12:46 stars was just a blog. Yes, just the blog and I had no other no other idea apart from this is swigs writing about AI that's it but we happened to host some events like some gatherings like oh

Defining the AI engineer to build a movement

12:57 like you know chat came out like obviously the most exciting thing of all time

13:01 and then we wanted to host some hackathon so we hosted a hackathon and at the hackathon that's where the idea for AI engineer came about

13:08 which is the realization it actually was this uh woman that came up to me and said I'm I'm all in on AI I'm nontechnical what can I do and I realized that the simple answer is based compared to an engineer she can do nothing. Engineers are about to be so much more powerful than the non-engineer because engineers can control 100 AIS at once and program it

13:32 whereas the the maximum that a non technical person can do is prompt better. Then I was like oh like I think I have seen this before. So my my career throughout my career I've seen like professionalization of roles that are nonp prestigious. So what do I mean by nonp prestigious? It is not prestigious to be a prompt engineer. The prestigious thing is you train large language models. You do pre-training, you do post-training, you have to go through a PhD, you make fancy algorithms like GRPO, you know, and and you you do manifold hyperconnections, which is what Deep Seek does.

14:05 That's prestigious and that continues to be prestigious. But I think the overcorrection that people have is that looking at everything else that is not that ML research that is worthless. Uh that actually was untrue. You actually do want to build harnesses and harnesses do not require you to know advanced advanced math or have a lot of experience in supercomputing like actually you just need to be a very good software engineer that is open-minded enough to understand how to put AI into traditional software code which is a harness. M

14:36 we didn't have the word for harness at the time but it was very clear that engineers would be able to do things like this that normal people cannot

14:43 And they would be in demands, and there's not only that: companies are trying to hire this kind of people, and developers want to become this kind of people they. want they want a term to call themselves, um, something. And so, all you have to do is figure out the right term which, is the simplest one is "AI engineer"and make it a industry, make it a discipline. And so, that's what I...actually, I can share with you a side story in China, is that at the time when you you just mentioned, um the, the event of Stable Diffusion, the open source of stability fusion. It was actually at the time that, you know, right now the largest AI community in China which is called way to AI actually, that was also started from a bunch of people who are, uh, ambitious or lovers of those stable diffusion technology and want to transform into different, like, images generation, and also it become the foundation of the Comfy UI. You definitely familiar with that comfy UI.

15:40 Yes. Confidence is we've had him on the podcast.

15:42 Yeah. Yeah. Yeah. and in China as well. And then so

15:45 do they use company UI?

15:47 Yes.

15:47 Oh wow.

15:48 And also, and also then they like gradually invite more people to uh learn in public and contribute more contributions on online document which is on the Lark, which is facial on the B, which is on the L. So everybody contribute their knowledges, share their use cases about uh stable division com UI, and then become larger and larger. I think right now the online community has around a million users learning together and several million users like learning together. So become the largest AI community in China as well. So that's also I think that happened at exact exactly at the same time I think you you start to feel like you need a we need a new word for for this type of engineer and then as which is you just published the essay of um the AI engineer. Yeah. I think people so here are some of the alternatives. I think you you can best understand it by the alternatives that people were trying at the time. So there was AI tinkerers which is another significant community.

16:49 I I know Joe and Alex uh well

16:52 and then there people were saying LLM engineers or applied AI engineer or all these all these other terminology. And I think basically you have to focus

2 Highlight · Connecting with developers through professional identity

17:02 on the job title that people want to have. And I think that for us that was very key. And I think I picked this up from the James Clear. Is it James Clear that wrote Atomic Habits? I think so. Um I I forget I forget I forget the authorship relationship, but I think it's James Clear. Basically, if you want to deeply understand or connect with somebody, you have to connect with them not on the level of their job,

17:27 not on the level of their activities or hobbies or whatever. It is their identity like who are you,

17:35 right?

17:35 Uh what what do you aspire to be? If you can give them the path towards being the better version of themselves, then you can build a community around that. Uh and so a lot of non AI people wanted to be an AI and what is the path for them? Um well you give them a job title that pays money like yes then they will be loyal to you.

17:55 Yeah. Yeah. Yeah. Right.

17:57 So so yeah now there's a lot more AI

17:59 engineers in the world.

18:00 Yeah. And to follow up just to my interest as well. So I know that there are just lot of works or um to do all right as a AI engineer. I know you mentioned harness a lot of developments happen in the AI. So do you think the role of the world AI engineer has been evolved as well or is different from what you just uh mentioned like three years ago once you started this work?

18:25 Honestly it hasn't really changed that much. I think that what's hot within AI engineering has changed but the job title is pretty much correct.

18:33 I think there are people uh in the early days it used to be rag and managing context and all that. Um and and then more recently it's been coding agents, it's been harness engineering, it's been uh maybe loop engineering or whatever.

18:50 There's also other disciplines of memory and all these things. So for those who are interested in all the fields of AI engineering in AIE World's Fair, which is the the the flagship uh biggest conference, we have 30 different tracks of what it means to be an AI engineer. Um and eval is part of that, multimodal is part of it, you know, all that stuff. So I think it has shifted over time. Um, I think agent engineer maybe is is one of them, or AI architect, you know? So, AI engineer is like the individual contributor version of this, but who is like the company level, companywide boss?

19:22 And uh, AI architect is uh seems to be the emerging term for for that that person that decides this is how everybody in a company does AI. Yeah that's AI architect. So and then like there's there's all the all the other like AI designer AIPM all these things. So, uh, it's just like who does that work and who writes code and who is responsible for checking that code? If if something fails, are you responsible? No, you're not an engineer.

19:45 You know, if the person who wakes up in like 4:00 a.m. in the morning to go fix it, that's the engineer.

19:49 Yeah.

19:49 Right. And so, we want to serve those people. And that's the real core of it. The other problem with AI is that there's a lot of There's a lot of talking heads who have never coded a single day in their lives, but they are very big picture. They're very, very senior. and they're like, "Oh, I'm CTO of blah blah blah." And but they have they don't touch code.

20:08 And so a lot of AI conferences and communities focus on those guys because they have big fancy titles. But then they all sound the same. They all like h my timeline into AGI is like 2 years away. You know, all of you are going to have not going to have jobs in the future. You need to prepare for what's next. Conveniently, whatever is next looks like their job. So it's very self-serving. And I think that that's one of the reasons that AI engineer works is that we try to focus on the lower level engineer that usually doesn't get the spotlight that actually did the work and is able to talk about all the war stories and share with their fellow engineers around what they're doing. And so, I borrowed this idea from other parts, other conferences I've seen in my career, like GDC, um, and CubeCon, and JSCON, and Pyon, and all these other conferences that I've spoken at, where basically, uh, it is engineer to engineer, and they are the decision makers for the tech stack, and they are the people who

21:12 create and innovate the new things, and they're not necessarily the most famous person, but they are definitely, definitely correct when it comes to the engineering. Uh there's no right? And I think there's a lot of in the other things.

21:25 Yeah. Yeah, you know, and then it comes to the the first AIE summit that you had organized in like 3 years ago, and then now it's actually a 3-day full summit with over 7,000 um people joined this year. Just just for the audience who are not that

Scaling the AI Engineer summit into a global franchise

21:40 familiar with what this event is, and different kinds of contents that or workshops or the topics you actually AI engineer is caring about, and then how did you actually bring this like small event to this such a big scale event this here. AI Worlds Fairfare is basically uh a similar industry flagship conference similar to the ones that every other industry already has. So, gaming has GDC, 30,000 people in San Francisco. Security has two, security has RSA, security has Black Hat. If you're in the cyber security field, you go to one of those things

22:14 and that's that's where you learn. I I really like the gaming one because gaming is very similar to labs. You have AAA studios. They work on the hardest games in the world. and it is extreme engineering and they're all top secret. They don't do anything else but one time a year they come to GDC and they will share like this is how I did game of the year and that's the only way if you're trying to be a game developer and you want to work at aa game studio this only way you learn.

22:42 Yeah. So I think that now the model labs are similar to game studios. They have a lot of money. They're working on very very big major projects. There's a lot of smaller companies that are, you know, trying to compete with them. But the labs are the important ones. And you want to learn from the labs. And where are you going to learn from them? You know, they they do like very small conferences where they like they launch like Developer Day for OpenAI or Code with Cloud for Anthropic, but those are super small and like very selective and mostly for customers, and they're not for engineers talking to other engineers. And then there's like 50 other labs that are not openly anthropic that also they have something interesting, right? So they usually every industry needs one big like everyone comes here and then you just walk around the room and just talk to everybody and then they can talk to each other.

23:31 Yeah.

23:31 Which is very interesting because especially for Chinese labs

23:34 some of whom are on the entity list.

23:36 Is this something that you guys talk about?

23:38 Yes.

23:38 They cannot officially take meetings with you.

23:41 A lot of American companies cannot officially take meetings with you. They're not allowed. They don't even respond to you. It's not because they don't want to. It's not because they're They're not allowed. But if you're in the same location, you run into each other, right?

23:52 And I think that's that's kind of interesting as for me to create opportunities for for magic to happen. And it's like people get hired, people find a co-founder. I have one couple that started uh dating and now they, you know, they're they're basically married. And like uh yeah, that is my number one KPI. Number of marriages and babies that I've created.

24:12 Uh and so so I I I really like that. I I think that uh we can create that kind of highquality community and you know we we're aiming for 6,000 people this year. We managed to hit 7,000 plus 1.5 million online watched our talks. So there people who cannot afford to come don't live in San Francisco, don't live in the US. They can still watch our videos and catch up on all the content. We publish every single talk, every single workshop. And like I said, it's like 30 different tracks. Um, there's too many tracks to name, but uh, you can see on the website. But I, I basically think that I really try to focus on things that are working, that you can make money, there are clear role models for you. Like, if you're trying to learn this field or you're a startup trying to build something, there's somebody who has probably talked about your thing at EIE.

25:00 right

25:00 that becomes a very valuable resource for anyone looking up anything. So, another thing I've actually recently done that I haven't really been super public about is I transcribe everything and I catalog everything. So, you don't even have to watch the talks. You can just take all of our website and feed it into an LLM and then you can teach you whatever.

25:20 Oh, are you actually creating a CLI based on

25:23 everything is is MCP.

25:24 MCP um everything has been transcribed. Uh it's available as a data set if you want to train your LLM on it. Yeah, go ahead.

25:31 Uh have you published yet or?

25:33 Yeah, it's uh it's on agineer/data. Oh, nice.

25:36 Which also yeah shows the shows the MCP and the data sets that you can download. It's just depends how you want to consume it. You know, we transcribed everything. We also deep research every speaker and every organization. So, whoever has ever spoken at AIE, you will you have a profile and we'll basically try to make the Wikipedia of AI.

25:54 Nice. And just one last question to follow up the AI is that when did you actually bring the AIE or TI to global like different markets? I know. Yeah. Now this year we have Singapore but I think um few years ago Paris is the first one.

26:08 Paris is the first one. So how did how was their journey end?

26:10 Mostly that is basically exactly following the JSCON model. JSCOM is the number one JS conference.

26:16 Yeah. And uh it's a very simple model right like I will never reach every country in the world but every n country in the world will probably want to do some AI. So obviously their country deserves to have a leading conference. They can either make their own or they can borrow our brand and our YouTube channel and our social media.

26:34 So basically we just set up a partnership program. Paris was the first to apply.

26:38 Okay.

26:38 Very fun fact the organizers of AIE Paris got acquired into Mist.

26:43 Oh.

26:43 So now now it's run by you know France and Europe's leading AI lab is runs AIE Paris which is very cool like I want that for every single you know country to like Yeah. You you have AIE India, you have AIE Japan. Yeah. So I'm working with all those those companies now and it's very cool like I will never know that region as much as them but like they of do they deserve a good conference? Yeah, absolutely. Yeah. And then they can do business and and hire people and all that all that stuff, right? Yeah. The world is very big. So um we we follow that model. So basically it's the idea that you have there's there's three things, right? Like one, you agree to not abuse the brand name, and like we, you know, um, we'll have some sort of, like, uh, revenue share thing. Two, you're publishing everything that you're, you're, you're doing. And then three, you have a code of conduct where, like, if, you know, if, um, someone is, uh, being abused or mistreated, there's some way of of, of resolving that. I think that's mostly an, an ethical thing rather than anything else. So we take a

27:44 lot of risk by doing this, because we're sharing our brand with people that we don't work with, and so what if they throw a bad AIE.

27:51 Yeah.

27:52 So far, it hasn't happened.

27:54 So far,

27:55 yeah, because I think like uh mostly we are we're careful about who we want to work with, but then also uh the the kind of people that are drawn to us anyway are pretty enthusiastic and organically interested in like yeah, especially for Singapore, AI Singapore. Yeah,

28:11 first of all, I'm Singaporean, but that actually did not matter at all. The current top conference in Singapore that is an AI conference is actually a crypto conference

28:21 which turned out to be

28:22 a lot of crypto people want to be want to be AI and yes it is super AI and I think they know that I don't like them

28:28 And so, like, they're like, "This is embarrassing for my country. You're telling me this is the number one thing in my country? We need something better." And so, yeah, now I think AI Singapore is is up there; is at least competitive and maybe, maybe better than Super AI. And uh, I'm very proud of the team for doing that. I, and I didn't organize any of it. So I think that is the important thing for every country in the world to have it and we can support that. Funny thing is that because I saw you went to Singapore for the first first AI event and I cuz I knew Lei very well and I asked him that, "Hey, AI came to Singapore for the first time, when when do you go to go to Shanghai or or China?" And then he told me that he is working with you.

29:12 Yeah. So, China is the tricky one, right? Because I'm not a I'm Singaporean citizen. I'm a Chinese and obviously there's a lot of restrictions between the US and China. So, that is the main tricky part that which is why I needed Lei and his team to really own the whole thing.

29:28 Yeah.

29:28 Because I like I cannot even set up a local entity in China, right?

29:32 There's a lot of controls. I don't want to get in trouble because my main business is US, right? So, I cannot get into trouble with the White House. But if you want to share the brand and run it as your own thing and it's a franchise, whatever. Okay. Like there's lots of franchises as far as we're concerned. I'm McDonald's and you're McDonald's China.

29:49 Yeah. Yeah.

29:50 Like Okay.

29:51 Yeah. Happy we can bring it.

29:53 There's KFC KFC China. Yes.

29:55 Great.

29:56 Yeah. That that's great. Sherry and I

Coding agents threaten mid-tier B2B software

29:58 guess next topic is something the contest you just share like few few weeks ago about the Q my sauce.

30:04 Okay. the I really like that show because um yeah just tell us something about behind the curios and

30:11 okay I'm wondering how many of your listeners will care about this okay you will only care if you own a business

30:17 uh because most developers do not own businesses they're like not that interested but if you aspire to own a business someday you will be better care

30:25 and also you know um because you know SAS was a very hot topic like several years ago just

30:30 oh yeah SAS is dying

30:32 and dying and you know been discussed a lot this year.

30:36 Yeah.

30:36 And so uh I found out that this this show is very interesting and

30:41 okay let me introduce the the the overall context.

30:43 Yeah.

30:44 My budget for running a conference is somewhere between 3 to 10 million depending on the size of the conference. Uh roughly about 300k of that per conference is software. I'm paying like that's like 10%of my budget. That's like 10%of my margin that I could be

31:00 getting back. that is to just somebody else's software that is shitty, slow, uh ugly, not exactly what we want. And you know, so I'm paying 300,000 maybe calling paying 1 million a year in just like SAS like like you want this, you want that to do your work. Okay, okay, okay, okay. Like as the boss like my employee comes to me and wants to use this thing, they say it's important for their work. Yeah, I'm going to say yes.

31:25 But like when it all adds up, like it's a lot of money. And then like and then I use it and they use it. They're like yeah it doesn't give me what we want. Like it has it's slow like they request like as a customer of a SAS what happens is you are in a queue for support right you want this feature and they're like okay

31:43 6 months from now you know we'll do we'll put you on the Q3 road map. You are very important to us

31:47 like it's you know we are an AI conference company and this is 2026 and

3 Highlight · Cloning mid-tier SaaS with coding agents

31:52 there's coding agents right like we can do this. So, uh, the idea was I took a $40,000 SAS that my employee was proposing to pay and I said, I will pay somebody $10,000 to clone this whole thing. It's open source and it's exactly what we want. And from here, we can use whatever coding agent, Codex, Cloud, Coding, uh, Devon to just customize it, whatever. Right? And we did it. We, you know, announced the competition. We had 69 submissions. When you have a competition like that, you offer free money. Uh I I've offered to cover everybody's coding agent subscription, right? So you have a lot of bad submissions and so I just like this is obviously stop like I didn't I didn't give money for that. But um we had 69 good ones and most of them were like usable about five I would say that we would pay for like it was just like good like it was done in one week.

32:45 Yeah. Yeah.

32:45 As a owner of a SAS business you have maybe like 50 customers all them paying you 40k. Imagine if all of them realized this and they just they just turn away.

32:54 They just they just turn away in one year. Your your business is gone. You went from earning $20 million a year to nothing.

33:00 Nothing. Yeah.

33:01 Yeah. That's uh it's very scary, I think, uh for a for a business owner. And I think that's

33:07 the tricky thing of of owning a SAS, right? Like like I own a physical business, so that's not going away anytime soon. Robots are cool, but they're not they're not organizing conference. But like people who do software B2B who own this like mid-tier SAS Salesforce is fine like nobody's worried about Salesforce but like the mid-tier SAS where like you know a lot of small mid SMB do you guys call SMB

33:33 SMBs they're going to really struggle uh or they are going to pivot to something that's better and I think they they really better figure it out now because all of us business owners who are their customers we also can code

33:46 and it doesn't take that long time actual competitors to to their own software right now.

33:51 And by the way, the models are very good at clicking through every screen of your software and then replicating it in independently. Oh yeah. Right. So the moment I have access to your software, I can clone it. So good luck.

34:04 Um and so I think that is the the reality. I would say that if you're a SAS owner, nobody knows that the right answer. I think that you basically end up having to pivot to being an agent builder. So you have to become like the US equivalent. It's like Harvey or um open evidence or Yeah. Yeah. You you own a vertical and you're the top agent in that vertical

34:26 or you own some specialized data and you're basically a data vendor. Anything in between, someone else is going to just code their own thing.

34:34 Yeah, probably. Can I follow a question because you already answer my first question? Yes. you already give some advice to those those

34:42 I'm more interested like so I'm not I'm

Business owners can build custom workflows with agents

34:43 not so sympathetic to the the SAS owners right SAS owners they they're big big boys they can figure it out uh actually I'm more I'm more keen on advising the business owners

34:51 a business owner

34:52 yeah I I run a small business I'm SMB

34:55 yeah

34:55 there's a million people like me they're all trying to just I I you know I make an honest living I pay employees I pay my taxes and it's a good life

35:03 it can be better if you viol

35:07 and like my customers are happy. My employees are happy. I'm happy. It's a cool story to tell. Uh yeah, you know, SMB is I think is a golden age for us. If you do anything in the real world that is you're just trying to do your job and there's a lot of shitty software between you and your your your intended outcome, you can suddenly shorten

35:27 buy your cloud and

35:29 Yeah. Yeah. Yeah. I mean, like, you know, $40,000 worth of cloud is a lot of cloud.

35:34 Yeah. It's a lot of cloud. I can spend 10,000 and like have a lot of money to like do whatever I want.

35:41 Yes.

35:41 Uh so I think uh uh that's why I I I call this is a business owner problem not a developer problem. Developer problems say like oh $200 is a lot

35:50 you know like like I'm a business owner. I understand the productivity benefits of having 10 of my employees work together well. Like 10 of my employees I'm paying 1.5 million for them. Right? Like if if they work together 10%better that's 150k the potentially it's not it's not 10%better it's like five times better

36:11 right that's like 7.5 million great and that is all the agent work that is being done on on my behalf that people used to uh say like well okay I'll you know I'll come back next week with a proposal no I want it this afternoon

36:25 yeah

36:26 my phil is that once you created so many softares yourself would that the maintainance uh the work will something you know difficult or

36:34 yeah it's it's real right it's not zero

36:36 you have to use it like

36:37 it's not zero but like we have coding agents

36:40 oh yeah maintain self self-maintaining

36:42 Yeah, and a lot of it is this is why I say like mid-tier SAS you're not Salesforce, you're not Google, you're not AWS, you're not this like missionritical 99.999 uptime thing, right? You are just like a database where people type in their thing and they get that something out. Yes. So like, yeah, okay, it goes down for a day, like whatever, and you can fix it in a day.

37:06 And there's a lot of coding agents where, like, I think I I would argue I would take that downtime for, in exchange for, like, I can customize, I can customize anything. That's amazing, you know and? and so my team is so much more productive, you know? Uh, I actually put this in the episode in "Kill My,sass" one of the favorite features. Let's say I have uh, so for example, for AIE Code my, my next conference next month.

37:30 I I have 1,000 submissions and I have 25 seats. Okay, I have to go to 1,000 people to get 25. And in the current SAS that we use for that piece of software, we have to click one by one by one by one by one. Every screen click click click click click click click. And so in the kill my SAS competition, one of our contestants just changed everything so that you can sort of reorder in one table. This view doesn't exist in that SAS. Okay.

37:54 To in order to get this view, we have to request for 6 months

37:57 but

37:57 and they're just cloning. just request whatever you want

38:00 and like ah now I can do I can see all everything in one go.

38:03 Yeah.

38:04 Okay.

38:05 That's so quick.

38:07 So I I am uh for listener you know if you're thinking that this is a stupid example it is uh I'm simplifying for audio.

38:15 I mean I find out that the top one uh winner is someone who can manage all the speakers lineups and that that's a

38:22 and it's good UX. they are testing it from the point point of view of humans

38:27 and I think that there is a lot of difference between the average submission and the top submission. So, uh, that is true that today, in 2026, if you're a business owner and you decide to hire the youngest kid with, like, you know, that looks vaguely technical to, "Hey, if I quote this test for me, please," maybe they're not going to do so well because they don't have any training. But just give it one year. Watch a lot of AI videos

38:51 and then you'll pick on it.

38:53 There's a skill level, right? Like a a lot of it is slob and you don't want to use slop, right? Your your employees deserve better. You deserve better. And actually sometimes buying from a tried and tested SAS is going to be better. It is going to be better of course.

39:06 But for us uh we want to be AI forward as a company. We will be more cutting

Software contests surface better ideas than rigid specs

39:11 edge.

39:12 Yeah.

39:12 And one last thing to follow up because like uh you just said it in the podcast that uh you have AI judge and actually judges uh the judge of the AI was quite different from the the winners that you picked by your team.

39:26 Wow. You really listen to the podcast.

39:28 Oh yeah. because I'm interested about the whole process. So I just wonder why why

39:31 Oh yeah. So that was uh partially on purpose and partially not the goal of the judge. The judge was purely did you submit a valid submission, right? Did you qualify?

39:43 Uhhuh.

39:44 But the judge was not aimed for is this the best among the whole court.

39:48 Oh, okay.

39:48 Right. Obviously there's a difference.

39:50 Okay. So,

39:50 so it's for your your purpose or your team's like conference purpose to pick which is more useful rather than just

39:58 because we didn't know what we wanted. So, I cannot make an AI judge for for things that I don't know what I want.

40:03 But once I see

40:05 70 different examples

40:06 and then you're going to obviously the one that is

40:09 and by the way fun fact the Len Space logo if you you see the logo for this podcast in this room outside the here.

40:15 Okay. That was through a a website called 99 designs which is uh very interesting. Are you familiar with this?

40:22 No.

40:22 Okay. When you want a new logo or you want any design whatever you pick from like you have maybe you ask your friend for like hey who's who's good at design and they give you three names and you pick one of the three names and then they give you a logo and that's it.

40:35 Yeah. 99 designs. You put up a contest and I got 400 different ideas

40:41 for a logo and then I award the prize to the the logo that we got which is it's a very good logo.

40:48 It's so much better, right? You want diversity and ideas.

40:51 So actually this idea of like do contests

40:54 and which I can do because I'm an influencer most people cannot do because they don't have the audience.

41:01 Okay. But I think that there is such a thing. 99 designs is a very good business because there's many designers. It actually doesn't take that much to create a design, right? You just need it's more about the quality of the idea than the amount of work. So you just need high quality ideas and it and like you just need to be able to to spray it over to a lot of different contests.

41:22 And so 99 designs is like that. And I think there could be a lot of 99 designs for SAS, which is something I'm thinking about. You know what I mean? Basically, I had to create a 99 designs for myself for saying, "Here's the $40,000 SAS. Here's the specs. Here's the judging criteria. Here's the blah blah blah." Even right down to like, "Here's how we pay you money when you win." Everything had to be worked out by me. But would I pay some other person to do all this for me so that I just tell them what I want and I get 70 different versions and I pick one?

41:51 Oh, yeah.

41:52 This is all the admin for me, right? Yeah.

41:54 So, there should be a 99 designs for uh for SAS and for cloning all these things because as again as a business owner I honestly I'm only doing this because it's good content. It's a podcast. You're interested in all these things.

42:05 But like if I didn't have a podcast, I probably wouldn't do it.

42:08 It's a lot of work.

42:09 We took like 2 months to eval everything. partially because I'm busy but uh also it's just it's a lot of eval like uh just there's five roles for this particular SAS

42:20 because it's about like organizer speaker attendee sponsor vendor

42:26 they all have to agree on what the conference organization looks like.

42:30 Yeah. So you have to create an account for each of the, in order to test, you have to create account for each of things and you have to do some data entry here, and you change accounts; you do some and you read and data entry here. You, change, change, change, change change change change change change change change change change change change change change change change change change change change change, change, change, and so that's why it's like complicated. That's why that's but that's what the mid tier says is that's why I pay $40,000 for this, cuz I don't want to do it.

42:49 but uh now that you can it's very fun job and problem to do

42:54 yeah sure yeah I mean it's a good experiment and because we are also running conference in China as well like also over thousand uh attendance before. So I can echo you so much about

43:05 but then like think about the rest right. So uh I used to pay uh kalani. Do you guys have kalanly?

43:11 I don't but

43:12 but you know what I mean like like a booking link like that's how we that's how we got to this meeting. Yeah. Calendarly is like a $13 billion business.

43:19 And yes you can vote Calendarly.

43:21 Yes I know.

43:21 Of course I have I have my own I have I have two versions.

43:25 You you already your uh like make your own

43:27 calendar. I I have my own calendarly. I have my own Google Drive. I have my own GitHub. I'm serious. I have my own Dropbox.

43:35 My gosh. I have my own Slack. All of this is because I have money and I can I have people and I can I can assign them to do things. But I do think that you can build software for yourself for audience of one or audience of one company

43:52 and that's okay. And that the fact that you can do that now is something that has never existed before for any business owner.

Open-source alternatives beat commoditized enterprise tools

43:58 Yeah.

43:59 Which is amazing.

44:00 Yeah. Yeah. Yeah. Yes. Great. Great. Great. Yeah.

44:02 Yeah. Okay. You do some investing, right? And you're you're you've you've raised money.

44:06 Uhhuh.

44:06 So, you know, Docu Sign.

44:08 Yes.

44:09 $10 billion company.

44:10 Yeah.

44:10 Or maybe seven now.

44:12 Yeah.

44:12 Uh what is Docu Sign? You you send a PDF. They say like, "Oh, yeah. Signed." They give you a certificate. Oo.

44:20 That's it. Yeah. Right. And they they send they charge you something like $10 per perfature or something for envelope. They call it, you know,

44:29 and like Yeah. I there's an open source docu sign and I hosted it for myself and you know what's the difference like because I have my own drive and I have my own docu sign the moment that the docy sign is signed it goes straight into the correct folder on the drive

44:43 oh yeah because you integrate together

44:45 yes and that does not exist in the docyign

44:48 right right yes

44:49 right so like my data room has directly the doc signs or everything that I didn't have to touch cuz it already has

44:56 right

44:56 everything my one thing special about docu sign is created like because it was built long time ago and it creates a network effect. Everyone joins the network, everyone using it. Are you still thinking it's a mode for this kind of software? no.

45:10 No, no. Electronic signatures are legally enforceable everywhere

45:14 and is docuign has no patent on it. I can do I can do my electronic signature. What the the network is the email address.

45:21 Is it like it it is so stupid and like I can keep going about why I made each of each of those things. It doesn't matter. It's not like I'm encouraging everyone to do this. I think that whatever problem you face in your business or your life, you really can find open source version of it. Host it for yourself. Customize it.

45:38 Integrate. Okay, I want this plus this. Boom. They just work cuz I use them all the time. I copy here, paste there, copy here, paste there. Inside of every 1 million copy paste, I think there is a fantastic startup and product to be built.

Jev and System 1 models embed AI in code

45:52 Great. And uh I guess next question or next show I'm actually quite interesting about your conversation with Dieago from Jeff cuz also it was actually a really also a very hotly discussed topic and product.

46:05 Yeah. What what is the Chinese developers thinking about it?

46:08 I think it just you know um just you know creates a new way of thinking about using like LMS from a totally different angle. Yes. And then I even heard that you know one podcast podcaster from China she didn't know anything about coding but she she used Jeff to judge you know the clips from their podcast whether it would go viral and then Jeff gives you know gives the answer and and then he will post it on

46:36 on the network. So I found so many great use cases based on Jeff. So I just wonder what's your take with with there and what probably

46:45 Yeah, so uh for, the those who didn't listen to the podcast, we were the first podcast with him the first one because I, I forced him. Because I have friends with him for 4 years and say, "If you don't, if you don't give me the first, I'm going to kill you." No, he's, he's, he's obviously like very, very accomplished. He was the co-author on, on uh the instruct GPT, which became chat GPT.

47:07 and I think the interesting thing about Jeff is that it is kind of the original vision of AI engineering for me which is that instead of right now AI engineering is is what we talked about is a big harness

47:19 yeah

47:20 around a model

47:21 and it's like I'll do a bunch of work and then I'll hand off to a model and

4 Highlight · System 1 models place AI directly in code paths

47:25 say please god model give me the right answer and then you can take 10 days to think about it Jev is like well no models are for us we don't work for the model

47:36 right

47:37 and so I will reduce the scope of the model to only one thing which is to make choices or to estimate probabilities and I will I will put it in the line of path of my critical work. So if you think about what is the failure mode of of what the LM current LM paradigm is is that you have the big traditional SAS and then your LM is this window that is a chatbot.

47:59 Mhm.

47:59 Right. That is basically what everything is or you are you look like codeex or chatbt or cloud and it's like chat window here menu here that's it

48:08 for what Jeff represents and what system one models represent this is why he doesn't call it decision model he calls it system one models

48:14 It is that they are in the path of code you write. It as casually as you write an if statement inside of a normal programming language, and I think that is really what he means by smarter software, which I really, really endorse, which is like you swear should just be at every point smarter instead of at one point smart and then everything else is dumb.

48:36 That's really dumb.

48:38 Yeah, I think the the speed stuff is almost

Non-traditional backgrounds drive AI breakthroughs

48:42 secondary to the reliability which is what he really is trying to say. That's why the company is called Typesafe.

48:48 But yeah, the speed is nice.

48:49 I just found out that Dieago himself also a very you know social character and and he's really passionate about what he's been doing. So I just wonder, you know you, you've talked to a lot of, like, researchers and developers or, you know, uh, AI engineers. What do you think? Why was Dieago, that made the Jaff, was it something special or different from other kinds of, um, researchers or people that you've, um, talked with? Cuz I find it quite special about, about him talking to the what he's building and what he's believing.

49:22 He has a nontraditional background himself. He didn't go to like Stanford PhD and all the kind those kind of things. So he has that sympathy with a regular developer but he also worked on Chachib.

49:33 Mhm.

49:34 And I think that a lot of people who maybe they went through the traditional ML researcher path you go to a top university and then you work on some interesting paper and then you get hired into a lab and you work on a lab. They are in the big models cult. everything will be solved by making our model bigger by having more more flops in our training run and more parameters and more more more more right

50:00 um and so it takes someone who doesn't come from that mold to really say well actually there's another way to do this which is smaller stuff that is sprinkled everywhere instead of one big one

50:13 and I think that is by the way Diego was not the first to do that there's been thousands of people who have tried to say smaller model's good,

50:22 right?

50:23 Faster, cheaper, better, whatever.

50:25 But somehow Dooo worked

50:26 one because he has the credibility of OpenAI.

50:29 Two, he made it into a System one versus System 2 thing, which I think was makes the communication very clear to the point where you can play Doom or whatever it was what there's some game demo that he that he showed in the launch post that was very clear like, there's no way you will ever use LM to do this. Mhm.

50:47 And I think that showmanship that he wears the pink jacket, he he's so passionate and he's talking that showmanship plus the technical capability is again like similar to the learning public like I'm a small version of that, right? Like I'm technically capable and I can talk. But for him, he's like 10x on both dimensions and I think that really comes through in when you talk to him. And also I guess my next question is about your your roles

Technical founders must integrate GTM early

51:12 on advising other startups spec just you mentioned I'm just very curious you know for for us as as advising role like u exactly what kind of advices that you are working with those startups and

51:26 how I can do I'm also curious what can you for your listeners and for me yeah

51:30 what do you do for other companies? Oh yeah. So we are actually a community that started three years ago. That we found out that a lot of uh Chinese based founders want to go global, and then uh I think u they were pretty good at building uh or ship products quickly, but they found a huge gap between uh you know go to market, marketing, and understanding the market.

51:53 Okay. If you're a Chinese founder trying to make it in the US,

51:56 you suck at this and you are very good at your tech and you suck at marketing and you better talk to someone who's good uh because you cannot do it yourself. Yeah,

52:06 that's it.

52:07 Yeah. Yeah. Yeah. Right. Yeah. So that's that's how actually found out that there's a huge gap between you know understanding the local market and you know um and then ship the product correctly and find your PMF.

52:19 Yeah.

52:20 Yeah. So that's basically we hold out a lot of meetups, and then working with some advisors here, and then try to provide different camps, workshops, and adversaries to those founders really start to find a little bit there, you know, on the right track of BMF, but still lack some talents and, uh, you know, help from, from the go to market side, eye.

52:40 Yeah. Uh it's interesting I we also host meetups. So so do actually before he launched uh Jev uh he was actually here in this in this room. Oh, okay.

52:49 Uh, we hold this like sort of um writers meetup thing where people can show their work and I will give commentary on on it.

52:57 Um, and so the sort of type safe manifesto came out of that. But I I think it's very similar to to that except that I would for some pe some of them I'll do it for equity.

53:07 Most of it I do it for free and then some of them they want to have a like a recurring call um or they or something they then then they offer some equity. It's just easier to do that and it turns out it's worth a lot of money if it if the company does very well,

53:23 right?

53:24 So I think that is interesting in terms of like a job because it's you cannot eat equity and like maybe they never sell like data bricks is like whatever 15 years old and worth $200 billion and this like I have my equity like what is it? But um I think it's it's very useful to be able to test your theories on a number of different companies. So when you work as an employee in one company, you only see one example and your advice only works in one company. But now that I have done 30 something 35 36 different companies,

54:00 I can really see the universal truths among all of them and I'm I'm better as an adviser to all of them

54:07 because I've tried everything,

54:09 right?

54:09 I talk to everyone. And I like, and I I understand the different scenarios of like, okay, my advice is not going to work for you here because I tried it at this other company; and and and you know, your situation is like clearly very different. And like I I I feel like actually almost all domain subject matter experts like I happen to own developer marketing, right, that's my thing but if you work in, I don't know, your strategic finance, or you're working in like GPU compute acquisition or whatever, and you and you are trying to be a global number one in that, you kind of have to go through a tour of duty of just advising everyone.

54:51 so you can just take test everything

54:53 some of it doesn't work

54:54 but some but sometimes I mean some of them is clearly going to work

54:58 and then you will learn and that's the only like your sample size has to be more than one and most people sample size is like five but like you know if you can get it up to like 50 then like you probably are one of the top in the field anyway

55:11 and I can share with you some you know some something that I find it quite similar in in those you know go global Chinese founders because right now more and more came from engineering background even research background and

55:22 yeah

55:23 they they think that they're building

55:25 The best products because they have like best harness skill, or you know, technical skills and knowledges, etc But actually, there's still sometimes a huge gap between you know what the customer actually wants, that the skills at products you offer, and sometimes like different local markets have even have different you know demands, and have seen a similar things on those technical founders, research founders, because I there also a lot of

55:52 founders can from the same background. Yeah,

55:54 there's a bunch of ways to to survey this or to tackle this. Uh the the most important thing to recognize is that if you are if you have something smart and like you think it's valuable and you're global number one really like you are world best at one thing like that's the most important thing. So everything else is uh I always call it

56:15 dining,

56:16 right? Like you have the long. Okay, I will help you with the ting but like you have the long. That's the you know and most people don't have the long,

56:23 right? So like that's that's good.

56:25 Um I think that there are some percentage of people who don't even have the long and they think they have the long and like then this like okay it's like a arrogance ego thing, right? But let's assume that you are genuinely have a very good product.

56:37 And I think the the important thing actually here is that you should not treat marketing as the last mile of like, hey, I did everything. It is the last night before the blog post. Can you review my blog post and change it? There's nothing I can do. Like you already did everything. But if you involve marketing earlier in the process right down to like before it's really built or speced out, like what, what is the way we're going to pitch, what part of the segment of the market we're going to go then you have more GTM built into the product in the first place. And I think that a lot of engineer or researcher defined audiences don't have that GTM brain that early. They usually put it all the way at the end. Yeah,

57:18 that the most junior part of the company is this GTM organization is like some interns from like some 22 year old person who is like running social media. No, like actually try to be serious about your the who what customer is supposed to use this thing and how where do they hang out? What problems do they face? What words do they use to describe their problems and how is their life going to be better after they see your thing? Right? uh and so uh very simple things most researcher engineer founders have not thought about this but if they have a GTM partner I think that that is often very useful um I think the other thing that I and then it comes to more to develop developer tools I find a lot of Chinese founders are robotics

57:59 right

58:00 um and robotics is also a very interesting space because it is much longer time horizon and still very early days right like how come all of these Chinese robotics founders they all the full laundry

58:14 right like unitry is the best and uh at least like but they're still unitry is still doing unitry things and

58:23 I would like them to see things that you never expected unry to ever do but right now you know the the the thing that they they just launched this week they're doing kung fu moves

58:31 kung fu yeah

58:32 But like, okay, I've seen that before, you know? Like, show me something that I haven't seen and, then then I'm really going to pay attention, you know I? I think that's that's something that, uh, is hard to show in robotics, but, um, I think with models you can do that still, cuz it's still so early days, and with, uh innovative like uh products ideas for, like, for consumer experiences, you can't do that. So I think to show the demo I think is very important which is why again obviously type safe is like very recent but also very good. It is not the do the yogo did not come out with the doom demo but the doom demo is what everyone talks about. The demo is done by dero like GTM and that that is that is something that just is a core principle in marketing which is show don't tell right like show me this thing having the benefits but don't tell me

59:22 in bullet points what this is don't give me a PDF a slide presentation PowerPoint that tells me all these things just show me

59:28 and maybe just a followup is about the taste cuz you know everyone is talking about the taste and then I think go to market and building the product also needs the taste. Yeah. Yeah. Yeah. That's probably true.

Taste is the ability to prune bad possibilities

59:41 Actually, I just have becoming a little bit hard for me to define what a taste is cuz investor talk about so I just wonder your view like how do you define the taste in front of those engineers or even founders.

59:52 Okay. I can define taste in a way that is not helpful. Taste is something where you are able to

5 Highlight · Defining product taste as rapid possibility pruning

59:59 out of a large set of possibilities, you're able to narrow it down quickly, cheaply

1:00:05 to the set of possibilities that when you look back is immediately obvious is good.

1:00:11 So you when you're at the start, you look out there's a thousand different things I can possibly do. Which one do I choose? Right.

1:00:18 Yeah.

1:00:18 The brute force, you can brute force. You can try 1,000 of them and then you find a good one. But a tasteful person can say, "Yeah, obviously these are bad. I don't I cannot explain it. I cannot explain. But obviously these are bad. This one looks this this tool looks interesting." And then at the end of the journey,

1:00:36 they'll pick one and you look back and you're like, "Well, that is

1:00:39 Yeah. What do you mean we're considering the other 999? Obviously, this was the correct one." There's many versions applications of this, but, um, the one that's coming to mind right now is the iPhone, where, uh, for a long time this the smartphone had a keyboard, and it took Steve Jobs to say "No we will do whatever it takes to have touchscreen and virtualized screen because it look needs to look like a screen that's a flat slab."

1:01:05 Mhm. And that took 10 years to R&D because there was a company called General Magic that tried to do this and failed. And but like obviously now every phone in the world looks like this. That is that is taste. In 1990 when people were starting to have smartphones you could do a number a huge number of things but it takes the the person with taste to say like yeah this is what we want and I'm going to say no to everything else

1:01:29 and my first phone I ship was going to be this. If you're looking back all

1:01:33 those AI products, could you share an example that you think uh you find it has taste? I actually think that everything that cursor does has a lot of taste because they were first to the VS code thing before and now they're they're doing Crockpot which is like a good taste thing

1:01:49 because like now now like OpenAI has to like copy them and what have you

1:01:54 and uh Claude has to copy them which like you know you have taste when other people copy the thing that you just shipped. the interesting way, you know, to go below the labs. I think it's interesting to think about like the more boring kind of problems that people solve. Uh, Lora, you know, in in the legal field, they uh they they have this sort of like document review process that's like massively parallel.

1:02:20 And like once you see that, you're like,

1:02:22 I don't want to do my work anywhere else. I I I have to do it in Lagora. Mhm.

1:02:26 And like again like anyone could have come up with it anyway. Ideas are cheap

1:02:30 but you didn't do it.

1:02:31 Lor did it. And so someone at Lorra has that taste of like we will define this billion possible things you can do. We will just define this products that that becomes the way that people do their work.

1:02:43 Yeah. I think uh coming to an end and I

Chinese startup ecosystems exhibit extreme intensity

1:02:46 think probably we have talked about the arriving arrives in Shanghai like two two weeks later. Uh I just wonder you know what do you hope to to see or to learn from the builders or the develops there? What kind of topics actually are you most interested at?

1:03:01 It's tough because it's more of a differential for me. I want to see how very different Shanghai is from San Francisco

1:03:10 because I think San Francisco has a B2B SAS bubble but Shanghai you you guys use Comfy UI. We don't use it here.

1:03:18 Okay.

1:03:19 We like our Canva. We like our foul AI.

1:03:24 Yeah.

1:03:24 Uh don't use don't use coffee. Like conf is more of like a open source tool. And same same for open call. Open call had more traction here than conf

1:03:34 but open call was really attractive.

1:03:36 Really try. Yeah. I bet you heard that.

1:03:40 Yeah. Yeah. Of course I know. But like I haven't seen that kind of energy myself. And I think it's very different like the you know for you a medium-sized community is one million people that's huge in here.

1:03:52 Yeah.

1:03:53 Well a million is already the topest in China as well. I like I've seen those kind of like you know Chinese like influencer farms like it's like all these Chinese girls like doing this and the phone like it's like the scale in China is just so different and it's so competitive, right? Like people say they do 996 in in San Francisco. They don't really like Saturday, Sunday, they're still kind of chilling, but in China they are really 96.

1:04:19 Well, it it's kind of normal in startups and also the big tech.

1:04:24 Yeah. But I think that I think that's really intense. People don't want like to and like,

1:04:31 right?

1:04:31 Yeah.

1:04:32 Intense.

1:04:33 Yes.

1:04:34 Right. And like people here don't work that hard.

1:04:37 I heard that engineers or startup founders work that hard.

1:04:40 I work that hard because I have no security. But like employees

1:04:43 employees

1:04:44 legally you cannot ask people to work there.

1:04:46 It's illegal. Okay. Yeah. I've seen some of the most competitive top tier US startups and I'm sure they're not working as hard as China. There's BAT. There's like the first generation then there's like second

1:04:58 second generation

1:04:59 whatever the thing is.

1:05:00 Yeah. I mean like those guys. Oh my god. Like

1:05:03 how did you learn uh the did you

1:05:05 They're such good founders.

1:05:06 Yes.

1:05:07 They're such good like if they they live in the wrong country. If they live in the US, they'll kill they'll kill Amazon. They'll kill like Facebook, right? The only reason they're not richer is they live in China.

1:05:19 Also the SAS, I mean the software as well.

1:05:21 Yeah. I mean, even even like Okay. So, when I did my study abroad in Beta in 2007, BYD was still like, oh, we're we're up and coming like, you know, we're we're Chinese based. We'll always be Chinese, right?

1:05:35 People love BYD here.

1:05:36 Oh, really?

1:05:37 BYD is taking over the US. It's crazy and like I would never have thought never that BYD would ever come here. It's insane. And I I don't know what I don't know what conclusion I will say this. I think that the Chinese energy and spirit and creativity and grit is something that people don't have exposure to. And then don't that's not even talking about the model labs which obviously like Deep Seek and um all those all those labs. So, I think there's many reasons to be excited about exposing that more. Uh, especially, you know, I think Chinese events, they're very, there's regulations against live streaming, but even they're presented differently than the way that Western audiences like to consume them. So, they don't have the same reach, right? Ali did like Ali Yun did like this thing where they presented the whole Alibaba road map with the Quen and everything.

1:06:31 Nobody saw it here.

1:06:32 Why? because it was in the middle of some corporate presentation presented by other people. So I had to go and translate everything for for the US audience.

1:06:40 But like

1:06:41 just do it with me, right? Just do it on the they will see it.

1:06:45 Yeah. Yeah. Yeah.

1:06:45 Yeah.

1:06:46 And also I saw that already there's some um open source like motor companies attended AIE this year in San Francisco Mini Max. Yeah.

1:06:54 Yeah. So I mean uh we we hope to have representation from everybody. Um, and I I think that there's a lot of people interested in in that cross-cultural exchange that are not interested in the politics,

1:07:04 right?

1:07:04 Like we will not do politics, we'll only do tech.

1:07:06 Yeah.

Full-duplex interaction models are the next frontier

1:07:07 Okay, that's great. And really really look for for and so I guess this all my question but I still have like three quick fire questions. Anything just first pop up in your mind. But first is, you know, what AI development or are you most excited about right now, and actually, what

6 Highlight · Full-duplex interaction and continual learning

1:07:25 actually worries you most? AI development that most excites me, I think system one models is like a very clear number one answer, so it's boring, so I'm not going to say it. So, I think the thing that people are under the radar about is interaction models.

1:07:40 interaction model

1:07:41 uh so this is something that thinking machine is doing for people who haven't who missed the announcement look it up it is where you are full duplex back and forth communication at all times. You don't start and then you take a turn. I take a turn, you take a turn. No, at at like at all times like you are listening while you're speaking and I'm listening to you while I'm speaking and I can interrupt you and you will immediately respond and adjust.

1:08:04 Yeah, I saw the demo by

1:08:05 that should be the way of AI, right? There's a corollery of that which is continual learning AI where you don't have pre-train, post-train done. you are learn learn as I work with you and that's just very that's a very interesting and important field and then the last part is world

1:08:24 models.

1:08:24 Mhm.

1:08:25 Which obviously doing very well and I don't have to explain that but yeah um what I'm worried about I think personally if we have an AI winter it is an AI summer. This is probably the longest AI summer we've ever had in human history. But the history of AI has been is about 50 years old. There's always summers. Everything's going to work.

1:08:42 Yeah. winter, summer, winter. If we ever have a winter, when is it going to happen? And am I going to go bankrupt,

1:08:50 which is a is a real concern for a conference company that relies on hype? You know, more more broadly, I think that there is a real concern about safety that all my friends at all the labs are really really worried about and that society cannot handle and adjust quickly enough. And it is not because of fake news. It is not because of losing your jobs. It is something worse. You know, right now the the way that we express it is cyber security. It's like, oh, I get hacked all the time. Every every day I hack hack hack hack.

1:09:21 I feel like there's something even worse on the horizon that we don't know about. The most extreme version of this is boweapons, right? Like oops, like I have invented CO 2.

1:09:31 Mhm.

1:09:32 Yeah. What if it's worse than that? So, so, um, the way that we phrase it in on the podcast that we do is that the default assumption for most people should be AI doom. That, uh, in all of human history, when a more advanced civilization comes along and meets a less advanced civilization, the less advanced civilization goes extinct. And this thing is evolving roughly 1,000 times faster than us.

1:09:57 And so, at some point, it's going to be more advanced. And then we have to figure out what to do there.

1:10:02 No. Cool. Yeah. And and the second question will be well just a bit light one is that what kind of other newsletters and podcasts other contents do you recommend?

1:10:11 I have a list uh it's called the good AI newsletters and podcast list.

1:10:15 Okay. Is it on the Okay.

1:10:17 It's it's on my GitHub. Uh but actually the for the more recent one you can check uh AEO.ent.space. So basically what I did was I asked every model what are the best AI podcast for engineers and it gives me a list and I transcribe it and I put it in a ranking. Okay,

1:10:32 I asked 200 of these questions. What is the best

1:10:35 payment startup? What is the best bank? What is the best financial advisor? What is the best database? What is everything every every question that I

1:10:42 That's why you call it AEO.

1:10:44 Yes. Because I'm agent optimizing for what the models answer. But it's probably a pretty decent proxy for what the people who choose the data sets in the in the labs choose and they choose laten space.

1:10:55 Okay. The the top the first one

1:10:57 it is does very well. uh is either number one or number between number one and number three and and yeah so that's that's the answer.

1:11:03 Cool. I guess I just leave the last question for you to ask me if you have any questions and then

1:11:09 what are your hosts for AI Shanghai?

1:11:11 Yeah, of course. So, I I hope to listen to more, um, topics about, like you said, some more infrastructure stuffs; for example, like, like the safety, the payments, or the things that coming to unlock more, uh, applications in the world that coming from different, like infrastructure Asian infrastructure. I, I, I'm just really curious about those topic because, uh, it's kind of a bit less discussed about in China, but I found out that, especially spending few, few weeks here, I find more people talking about and also, probably, RSI or those some frontline researchers. So, and I hope that it could be a great conversations between the east and and the western like the researchers here and then the the the people in China as well and I hope it can be a successful one and then we can car for continue to host it on next year.

1:12:00 I hope so too. Uh you know I I wish I wish the the team a lot of luck. Uh doing the first one of anything. The first one is the hardest,

1:12:08 right? Agree.

1:12:09 Yeah. I'm I'm so impressed that they're doing it.

1:12:12 Thank you so much, Sean.

1:12:14 Thank you.

1:12:14 Thank you.