How Anthropic Builds And How Engineering Will Change Soon | Thariq Shihipar

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35:16But when it's kind of prompting models to do beautiful or tasteful work, it's kind of not always, it's pretty much more hit and miss. And so, you know, how do you best instill like a very particular style you're going for or particular taste in the model's outputs when it's a much more subjective domain, maybe like front end? The way you do it is sort of like you stay in the loop. I think you give it references, right? And I think the more references you give it with data, the better. So like it's better to give an HTML file than a screenshot, right? It's better to give a Figma file than like a raster image or something, right?

35:56Because now if Claude wants to know the border radius of this thing, it's like, oh, what's the Figma component border radius? And let me just copy it over. And so I think giving it a bunch of references, ideally in code is a really good way, right? Of like getting it to stick to this. I think if not, you can then ask it to, if you don't have like, let's say you're not a designer there's probably step one is being like okay i'm not a designer there's a lot i don't know about design you know and like there's a lot i don't know about iteration i don't even know what good looks like right and i think this is like part of the art of working with the designers like they will just know what good looks like and they'll be like this isn't good enough in this way right and they like prompt it and that i think is also a skill that will keep getting valuable and even more valuable over time is just like what is good output what is worth doing right like i think uh for example with the uh the reeman hypothesis jared prompted it but he had no idea if it was correct until like lev who was like you know one of the world's best mathematicians so it was like you know okay like how do i is this correct right and he worked with it and he asked like tons of follow-up questions and we could not follow that at all we had no idea what he was saying right but he was like really intrigued and and so i think more and more being that like high taste user and like knowing a lot about a problem in a domain space is how you get good outputs right that's how you solve these problems uh otherwise like maybe claude did solve like physics or something but you just wouldn't know it right like you're like uh you you don't know enough about it And so I think when you're talking about design, the first thing you do is how do you become more tasteful with design, right?

37:44And so you can ask Claude that as well, right? Like you can be like, hey, I'm not a designer. I want to be better at design. I don't even have the language. First, maybe let's find some reference sites. And then maybe you pull some reference sites and then you're like, this is what I like, or this is what I don't like, right? And then you sort of build up those references and you give Cloud it. And now maybe you tell it, hey, let's do some exploration. This is sort of my taste. And then it'll do like a few different mockups, right? And I like to do these mockups all in HTML because it's all self-contained, easy to edit.

38:16And then once you have that reference, now it's a reference. So now you can make a new session and be like, hey, this is a mockup of a design I want. Start implementing this. And, you know, it will have all of it in code and you can start getting there. But I think that, like, the really hard part is just knowing, like, oh, when is something good enough, you know, versus like, when can you, you know, push harder. Right. And you see this with a lot of the math proofs, too. Right. And when like Terence Tao is like, OK, enough with the half complete theorems, just do the full theorem, you know. And so I think like it sounds simple, but it takes a lot of domain knowledge and expertise to get to the point to be like, OK, like it seems like you're smart enough to have done that.

39:02Now do this. when I was a software engineer there was a lot of um I guess it was like glue writing work kind of where you you finish some work and you write a launch post or you are part of some work stream and you got to post an update every two to four weeks or maybe you have a direction doc or design doc and all this like writing around the software that you actually write and curious your thoughts Thoughts on if that's changed at all at Anthropic, how much of that is written by LLMs and how much of that is human written still? My rule of thumb is like, if I would be happy to show someone the prompt, I would send them the output, right?

39:50And so a lot of times the prompt is just collecting context is the most common one, right? So, for example, before every one-on-one with my manager, I asked Claude to, you know, read every Slack message and GitHub message and, you know, or read PR and compile, like, you know, a report of what I did. Right. And that's context that my manager doesn't have because, you know, they haven't been literally reading every PR or something. And so I don't feel bad if, like, you know, like my manager could also run this command, but it doesn't have my context. and I don't feel bad with them knowing that this is the prompt I used to generate this command.

40:31So I think likewise, if you're sharing updates or something like that, you might want to prove that you've read it. I think this is important. And sometimes little edits are ways of proving that you have also understood this work. And so if it's just a data readout, maybe you're sanity checking the numbers make sense and these are all the numbers you intended to include. And as part of that, maybe you format it differently or you add like a little sentence on your behalf, right? But I think ultimately it's a data readout. Everyone knows the prompt you wrote is like, hey, like generate a readout on this feature based on this and you're fine, right?

41:13But like, I think if you're pitching like a new concept or a new idea and your prompt was like, help me come up with a new concept for, you know, this product, right? Like you probably at least people want you to know that want to know that you've like believed in it. Right. And so like even if you think Claude's idea is incredible and just verbatim, you wouldn't change anything. What I would say is like I'd be like, hey, Claude generated this. But I think it's great. You know, like I or I did like 100 different generations. And I think this was really good. And here is like something, you know, that I want to send you.

41:47right um and so i think that like it's good to be up front about it i think right because i do think what people don't like is when they feel like they've been like misled a little bit like oh like you we thought you were doing this work but you know um it's really clawed right and i think that like um writing sometimes can have a lot of like there are some parts of writing where individual words matter you know like funnily like tweets are i think an example of this where like the individual tweet matters right so um you like more and more you can't use claude to do that because it's like like every word has some thought that you've put into it and some intention that you put into it so like you know yeah a pitch or an essay or something like that we do a lot of like internal essays at anthropic being like hey this is why i think we should do this and that's generally like all human ridden it's very like looked down upon i think to have like claude like your essay written by Claude you know what I mean because like every word is something that you like are intentional about so it sounds like the proportion of the writing that's all that boring route to writing like the data readouts the the one-on-one updates the work stream updates that's increasingly becoming AI but always reviewed by a human and then the novel thoughts novel direction is still very human written and feels like it should remain that way even if the models were a little bit better too yeah i think it's like if you're you know so like writing is also a way of thinking right and so like maybe if you need to think about the data stream or data readout more then maybe you need to like summarize it you know and and so um but yeah i think like especially gathering context is one of those things where no one will ever like hold it against you kind of right like uh oh like you know you did a bunch of research and you know claude did this but yeah like i don't want to ask my agent to do the same research like you know it's a shortcut but like just acknowledging it is good someone else i was talking to they had this thought of it would be valuable to have almost like a git blame but it's like like a prompt blame of because it would be nice to reverse look up what was the prompt that generated this change to kind of debug things do you have any sort of meta version control on the prompts that generated the software or is it still very vanilla you know git history yeah that is a little bit tough because again like you know what goes into a prompt is not just the prompt but also like context and skills and things like that.

44:29So like maybe, you know, a prompt might seem basic, but isn't. I think it's kind of hard to judge, but I do, you know, like going back to like, when I'm giving a PR, I don't think a PR at this point is any different than an artifact or something like Claude is doing basically all the code writing, right? So if I send someone a PR, I usually also attach an artifact of every prompt I sent to Claude, including failed, like approaches and things like that you know um so that they can see like okay i've considered a lot of other things you know and if i haven't if this is just a one shot i just tell people i'm like hey this is the one shot example this is the prompt i used right um and uh i think that's like usually impressive and interesting to them as well because they're like oh like it's cool that claude could one shot this um but the worst is when you get like you know you just i'm just trying to avoid cases where I sent in like this 10 ,000 line PR.

45:29And they're like, did you like, how much have you like read this? Or like, you know, like, how much do you work with cloud on it? And if I'm doing like a large PR, I am going to like, show my work as much as possible. On maintaining code, because AI can generate such high volumes of code at this point. Do you have any tips on what's worked well at Anthropic for code ownership and maintenance? I do think you have to revisit what is important with code maintenance. And so I think that there are some things where naming used to be really important, because it was how you as a team thought about this abstraction and feature.

46:10But I think naming is becoming less and less important. A lot of stylistic things in code are becoming less and less important. And I think that this is not the same to me as maintenance. Right. So I think that like if you you might want to sit down and be like, OK, like what things really matter now? What don't what opinions do we have that don't matter? That's one. And then I think on the second on the maintenance side is sort of like having good scaffolding. Right. So I think that it's like having a good verification harness, having a good like sort of skills. is we use the simplify skill a lot.

46:49I think that like, you know, sometimes even from a model perspective, like it might do a lot of work. And then like even just giving it permission to be like, hey, I think this is the right idea. Let's simplify it. Gives it that permission to do it, right? But like you actually don't want a model to by default, do work and then simplify, right? Because maybe it's not correct, right? Like you don't want it to simplify work that's not correct. It's like you're wasting tokens, right? And so I think this is also how humans think, right? They're like, you know, you think generatively, you try and approach and then maybe you like simplify and abstract a little.

47:26So I think there's like some work inside your own code base or like setting up those skills and that for those practices where you're like, you know, you're not just submitting like the first take, but you've like simplified it and tried it. And then like, yeah, having a really good verification harness where you feel like you're catching, you know, like you have a good belief that Claude is like testing every part of it. Like, you know, when you submit a PR to Claude code, you get a recording back of it using the feature and testing it as an example. Right. And you can just get really, really creative with different ways to like test stuff.

48:05Like, I think you should basically have on the order of, I'd say more like a hundred times more testing code than you've ever had before. You know what I mean? So like you should have fixtures for everything. You can just pull production code and create fixtures and mockups on the fly for databases. You can have storybooks for front end and things like that. And you can have all these different ways of testing and verifying your code. And that I think is really valuable for maintainability, right? It's like just having like all these ways of verifying it. And then, yeah, of course, like there's just like the human element of like, where do you want your code base to go?

48:44If you know that's the case, probably you start thinking about how you'd replay and undo and redo becomes really important, right? Just that sort of stuff. But if it's single player only, that actually matters a little bit less. The average user is not going to undo a hundred times or something, right? And so many single player applications, undo stop working pretty quickly. like, you know, after like four or five times, right? Just because it's not that important, but in multiplayer, the ability to compose different things together is really important or compose different operations together is really important.

49:21And so that's just an example where like, if you know the direction of your code base, there are things you care about and you want the models to know. And, you know, you can include that in your skills. You can also just like, you know, like that's sort of what maintainability means to me is like having a vision for what your code base is good at, where you're going, you know, keeping it in line. um i do think the models are getting better and better and better and like almost every code base probably i think will have this moment where you're like do you just ask the model to rewrite all of it you know um and like because now you're like oh like i can do it in the most performant language i can mix and match like you know like there's not a reason that every software in the world shouldn't run in web assembly in the browser you know i mean there's not a reason why i don't know like your xbox game can't run in your browser actually right like the x but like the hardware like the consoles are much weaker than your average like macbook right now you know i mean but it's just like the code base right um but we could like and so i think probably over the next year or two like everyone's gonna need to think about that right and so i don't think you want to spend too much time like worrying about maintainability in this like way that might not matter anymore i'm not saying maintainability doesn't matter you just have to update your mental model of like what does it mean for like code to be maintainable you know i was talking to this friend um who was saying that he leaves tons and tons of tech debt leaving around because the next you know the next iter why why waste time fixing that now when the next iteration of fable is going to one-shot all this tech debt and refactor this for me so kind of funny yeah i don't think that's completely incorrect it depends on the circumstance right like i think this is also just a classic thing in startups right where you're like you know even in normal human engineering you always have this problem of like um hey do i refactor do i do tech debt or do i deliver more customer value would refactoring help me deliver more customer value right now i do think that like just generally i think you should think on your projects on shorter time scales so you're like okay how do i deliver value over the next month or two and if the project you're talking about is delivering value over six months or 12 months you know then maybe yeah maybe like wait for the next model a little bit you know and then like that like just deliver value on like the short time scale, make sure it's really good.

51:56And if the models are not quite good enough, they might get there soon. It depends very much on the specific case. And I'm not saying this is true of everything, but just something you should keep in mind. I've talked to some friends who work at big tech companies like Google, Facebook, those types of places. And then as they've become more and more AI pilled, one thing that people have noticed is there's a lot more incidents or SEVs in their usage. And it's natural in those organizations because they read the code less and there's more code flying out. What countermeasures have worked really well for Anthropic to prevent breakages given that the code velocity is so much higher?

52:41Yeah, I think this is something that is a byproduct of moving faster sometimes. And we have to figure it out. Like, I think that, you know, I don't think our uptime is exactly where we want it to be either. But also as a company, we're a little, like almost six years old, I think around, right? So it's like no company has grown this fast before. And a lot of that is because we've been able to like create more products faster than ever before, right? And so you can use Claude to make your uptime better, right? And I think that like the way we think about this is just like really good. What's the dream testing environment?

53:16through dream like you know deployment environment like can you like you know take requests and replay them across like you know mock databases and fixtures across everything can you chaos monkey everything you know in my personal workflows i have so many more custom random tools and scripts that just make everything faster and just curious you know on your team metanthropic for instance does everyone have a set of miscellaneous tools that help them you know get random things done yeah everyone does for sure like i think part of this is the job like i think that sometimes uh what we try and do is we play around with harnesses like sometimes some people on the team build their own harnesses for a little bit to figure out like oh is this like useful or not you know and then they they figure out if it works and if not they like integrate it right so i think there is like that's part of the job uh in some ways um i think like other examples of like sort of like misc stuff people will do a lot of people have like uh unique claude tag setups i think claude tag is one of these things where like you know you can have it like i have it scheduled my calendar advice right and so like if someone wants to like schedule something with me that i'm just like hey you can just like tag claude here in this channel and i'll accept whatever it like puts on my calendar you know what i mean so um i think there's like some stuff like that i know like a lot of people use it for like email i think that um i've seen like some people do like interesting like multi-clodding sort of like t-muxing like setups right like we're like what's the ideal scenario for you to like display like 50 different cloud codes and you know what's the best way to for you to figure out what's going on at any one time so um yeah i think there's a lot of different ways and we're trying to make cloud code more hackable as well so that like you know more people can uh sort of like even uh make their own version of cloud code like more different and everyone might have their own little twist on it your role at anthropic is really interesting because of the external visibility that you have and I think a lot of people, when they give career advice, visibility is a good thing, but they don't have this level of external visibility.

55:42And so do you recommend to software engineers like they should be posting on Twitter and X? And, you know, if so, what advice would you give in that sense? Generally, the thing I say to people is that you should share your work externally as much as you can, And especially, I think within certain companies, like you might not be able to, but like maybe you have side projects or something like that. I think just before I joined Anthropic, what I did was like, I spent a bunch of time working with different companies, building stuff and writing about it and talking about it. And like, this was really valuable because it like increased my surface area of luck, you know?

56:24And so I think that like, it's really like the bar is much lower than you think like basically whenever someone asked me for advice I'm like okay I'll sit them down I'll be like I know statistically I tell this advice to a lot of people and almost no one does it and everyone who's done it is like either in a job that they're pretty excited about or running their own company and there are reasons why you're not going to want to do it but like this is it I just can tell you one like I don't care about your resume like like you know don't do that um you have to choose like an interesting project to work on you have to work really hard on it you have to like lock in and then you have to ship it and write about it like you have to do it you can't like there's gonna be so many reasons why you don't want to it's like not good enough yet or like you haven't like you think the write-up is not very interesting or something but you have to do it and you can't get discouraged you know Maybe the first one might not work, but you have to do it again.

57:22And maybe Twitter is not the right place. Maybe it's Reddit. Maybe there's a specific Reddit or Hacker News or something like that. Part of what you're trying to do is you're just trying to find people who like what you're doing. But I think that people in general want really... We consume more content than ever. You know this. I think that people want really high-quality content. content high quality content as you know is a lot of work and so i think going back to like what we said before about like would you show someone the prompt you did right like i think a lot of times people are like oh what's the shortcut like oh like should i just ask claude to manage my twitter account and is that how i like grow in and i'm like no like like you should not do that right like you have to sort of engage authentically um you have to like post like you know do good work can talk about it and I think like build up networks and things like that but I think that as long as that's one of your goals and you try hard at it I haven't seen anyone not succeed at it but it is really hard it's kind of like saying like oh I want to like go to the gym every day or I want to like lose weight or something you know like there are simple things that you can do that take a lot of discipline and are easy to get discouraged with and um but like worth doing if you do it.

58:39And I think like posting or more specifically, like writing about your work is like, I think really, really valuable. You mentioned luck surface area. Do you have an example that kind of illustrates the value of expanding your luck surface area? Yeah. I mean, okay. How did I get my job at Anthropic? I did a fellowship with a company called Goodfire where I did like some applied research. And so they're an interpretability the AI company. And I was trying to figure out like, how do I use interpretability to, in like, to make better products? And so I learned about their research. And I, like felt, I want to work on a project and it was really important for me to like, share it.

59:24And so like, I, when I agreed to work with them, I was like, that's my goal. I want to like, share what I'm building. I think that's good for you as well, because Goodfire is a startup and, And, you know, people, I want, they want people to learn about them. And so this is something I'm going to do. So I built this, like, interpretability visualization. And I shared about it. This was my first, like, big post on Twitter. But it was only 500 likes or something. Like, now, like, you know, that's, like, not very much to me. But, like, it's, like, back then it was, like, a huge post. And several people saw it.

59:53And, like, some of them DM'd me about it. and then uh like i then got an intro into you know like uh into a role here and so um i think that like i spent like a month on that project i think in particular so it wasn't like you know crazy um and uh yeah it just like showed people that i could like do interesting work and um And I got paid for it too. So it wasn't like I was doing it for free. And there's plenty of examples of like, I think people are happy to do that sort of thing for you, you know, like if you like sort of show that kind of initiative. But yeah, you have to like, it is like you really have to like do interesting and novel work and work, work hard to be proud of your work as well.

1:00:44You know, there's not like a shortcut to that, I think. but if you do i think everyone is always looking for interesting work and wants to support you and you know wants to hire you or um yeah give you money like uh lots of good things i see this tagline going out a lot with some of the stuff that anthropic's been um maybe like i think it's like boris went on some podcasts and the tagline was coding is largely solved you know should people still learn to code if coding is largely solved? I think being technical is really, really important. Knowing how do computers work? How does like, yeah, how does, how do computer programs work?

1:01:27How do languages work? Like what are the hard things and like what's a backend service? Like what's a cache? Like what's, like, like, you know, what, like what is memory allocation? Like all of these things are actually kind of really important to learn. I do think it's hard to motivate yourself sometimes to do in the same way that like you know doing math by hand was not that motivating to me you know but some people just love math and did it um i i think that like that's probably something that people have to figure out i think it is really worth it like being technical is really really important like we talked about at the start of or like earlier we're like oh the only way you can tell you've solved you know the reaman hypothesis or like made progress or whatever is like or the jacobian conjecture is like if you're a great mathematician right and in the same way the only way you can tell if you're like built great software is like if you're a great software engineer um i think that like how do you do that is hard but like we've talked about some of this stuff before just like staying in the loop like you know like put like uh like putting like reflecting on your process and and getting better and you can use Claude to learn as well and sort of explain things to you.

1:02:40So like treating it like a thought partner. But learning like truly, I think like, you know, Kaparthi says like learning should feel like effort, you know, and I think that's like one of the hard things is like a lot of times, even if you ask Claude to explain something to you, you might just like nod along and you're like, oh yeah, like I learned it, but you didn't really because you didn't put any effort in, right? So I think that like it is really technical. You should learn. It's hard to learn. And sometimes like what school forces you to do is to learn that. I don't know truly, like I'm not learning programming from scratch.

1:03:11So I don't know exactly how to do it now. I think if short of better ways, I would still like type out and build programs and run them and learn them. You know what I mean? There might be better ways that are more cloud informed as well. But I think it's really important. And I think when Boris says coding is solved, I think it just means like, you know, we don't get stuck in the same ways that we used to before. Like, I think coding used to be this very high variability thing where you're like, oh, like, could this bug take a day or could it take two weeks? You have no idea sometimes, you know.

1:03:47And I think like on the whole coding used to be like in real terms, like something that was very rare for something to go well. Do you know what I mean? Like very few people in the entire world could write software and they were very, very rare. And even if you got them all together, there were so many other reasons why it wouldn't work. Right. and coding was this like one of the rarest things in the world where like the chance of software project going well was like on absolute terms very low you know uh and if you were like hiring someone to like make software for you for something that's not like a huge product like you're hiring someone to make software for your car dealership you were almost certainly not going to get the software you wanted you're going to get like essentially scammed you know what i mean not because anyone was trying to scam you just like software is really really hard and you know it could only be spent on like the most important scalable things in the world and now that coding is solved i think what we mean is that like you can use coding to do all these other things that we've not done before but that's not to say that like that's not a lot of work still um it's just like it's not this like incredibly rare difficult thing that mostly like just doesn't work and you have to spend like eight hours a day locked in to do well it's really insane that shows the difference in expectation is when i used to write software i would be shocked if it worked on the first try i was like whoa wait why is this working and you you expect to kind of bash your head against the wall a little bit and then it works even if it's just like you missed the semicolon or something like that and now i almost have the flip expectation where when it doesn't work i'm like wait what why did claude what what happened here usually i expect it to work almost uh the opposite like on the first try it's crazy immediately yeah yeah i think humans get really used to abundance right like there was this like um article someone shared recently about like going through a modern apartment and talking about all the like wonderful things that we have now that people could not have imagined before like something that can play music on demand that's suited for your mood you know like before you'd have to like hire a musician you know to like go write like you know incredible music right um but i'd say on the whole probably more people are getting paid to make music now than ever before right like um and i think that like music is reaching more people than ever before and i think probably the same thing will happen with software will happen with math, what will happen with all of these things where, you know, when you get abundance, people are like, great, like I want more abundance.

1:06:33I want my software and everything, you know, like I want my music everywhere, you know, so yeah. Yeah. One potential other data point from this conversation saying that maybe people should still be technical or learn how to code is I think earlier in the conversation, we talked about automating knowledge work and you mentioned that people who are technical had kind of a leg up because they could kind of understood how to coordinate Claude to do a variety of things like you're calling FFM peg to automate some video editing and like I don't think someone who is not technical would have that thought so it does seem like even in this case where models are doing a lot there's still so much value in being technical knowing how computers work you know in the same way that like look probably like the most technical CEOs are like the best CEOs are technical, right?

1:07:25Like Zuckerberg, Elon, right? But like, you probably haven't written like a line of code truly in a long time. But you know, they understand how systems work, they understand, you know, constraints and things like that. And that's really, really important. And so, you know, even if all that work has changed, I think like being technical is really, really important. And then last question for you is, if you could go back to when you just entered the industry and give yourself some advice, knowing what you know now what would you say they're like kind of like two wolves sort of i think like you have to believe in yourself you know i think like this is really important and i think that like at least when i joined in the industry it was rarer to believe in people when they were kind of younger like i think that was like the whole point of why combinator or something was like believing in young people early on to do really great things and so i think that like you know even going back to like the intern discussion we had earlier right like i think that like thinking of yourself not as like someone who's like being trained to do something but someone who can do like something incredible right away i think is really important you know and um i think i wish i had done bigger bolder things that i'd written and shared about i think there were lots of ideas where i was like wow like i think i think i had like i thought i had done original work that i wish maybe i'd even shared in some form but maybe not like form that like survived the internet you know and it wasn't like a like goal of mine and so i wish i had like sort of been bolder and like you know done and shared some of this work but at the same time you also there is a lot to learn from people you know what i mean and like i think that um you like i think when you're young you're like you know you tend to fold fall either you're not bold enough or you're you're not like uh you don't like learn enough you know or you're like you're not like you don't like you're too bold and you don't like figure out what people have done before and figure out why it's not working right um and there's this balance and i think uh you everyone has different failure modes but i think like uh i think i probably didn't take it enough advantage of like you know mentors and people who had learned a lot.

1:09:44And I think I probably had to like, relearn a bunch of things as a result. So there's probably not universal good advice, but just things to think about as you're, you know, as you're entering. Awesome. Well, thanks so much for your time, Tariq. I really appreciate it. Yeah, of course. Thanks, Ryan. It was fun.

1:10:12please drop a comment. Guests like Barbara Liskov, Mike Stonebreaker, Mark Brooker, these were all people that I brought on because someone left a comment. On another note, aside from the podcast, I'm working on building the ergonomic keyboard that I wish existed. Here's a glance at the prototype. It's a split keyboard. So there's two sides. This is in the case. But yeah, we launched on Kickstarter and we hit our goal within eight hours of launching. I really appreciate it if you were one of the people who grabbed one of the early units. we're now working on the long journey of building the tooling now and so if you still want to pick one up i've left the late pledges open on kickstarter so you can grab one there i'll put a link in the description thank you again for watching the podcast and i'll see you in the next episode