How to Become an AI-First PM and Designer | Paul Adams (CPO Intercom)

do you think AI actually make PMS like lazier and Dumber cuz L for everything of lazier and Dumber yeah I do worry a bit about it even my experience the best product people not just PMS but like designers too have like deep intuition and really excellent product judgment and then like where did that good judgment comes from uh it's very difficult to build really good product judgment without having spoken to like many customers over many years in your domain if PM sits in 10 qualitative hourong interviews versus like asking you know some software to like summarize the transcripts they're just night and day different things just don't think you can build great judgment from getting AI to summarize Alles on the my guest today is Paul Adams Chief product officer at intercom when chat gbt launched Paul and intercom team blew up their road map to go all in on AI since then they built an AI first customer service Suite that can provide accurate answers to customers 24/7 Paul and I spoke about how PMs and designers can skill up on AI and get hired to work on AI products why you may not want to start with the customer problem when building AI products and how intercom blew up his road map to build an AI chatbot that can resolve 50% of support queries without a human Paul is an incredibly thoughtful product leader be sure to subscribe subcribe if you enjoy our conversation all right Paul well welcome

I'm really excited to talk to you today yeah thanks Peter very happy to be here yeah so you know we're both product managers and we both have been playing around with AI tools to start you know maybe you can share what are some like most common data AI use cases that have helped you or PMS or designers on your team save time and get more stuff done yeah probably all the obvious things you know you hear from lots of people I use AI these days a lot I use chat GPT a lot for all the things you'd expect I do research I do a lot of research there as my kind of first starting place I used to learn about technology probably somewhere ironically I use it to learn about AI how AI works you know certainly the early months of this kind of AI era and Revolution I was trying I was using exp about like how do large language vs work or you know when someone says a term like ride I've never heard before what does that mean and things so I use it a lot for research I use it for synthesis izing and summarizing you know I go to a lot these days for trying to like take big bodies of content and summarize it down into something even if I read I have a really long blog post someone's wrot written that I think is great I'll ask AI to summarize for me yeah pretty similar and when you use AI do you like give it this like very long thought prompts or just kind of have a conversation with it or both probably both it depends you know in lots of cases I use it like I use Google you know like I literally just write in seary sometimes that will give me what I need and sometimes it won't and then when it doesn't I'll try and give it more instructions you know and try and clarifi like get it to clarify or get it to like constrain itself or give it a role you know you are a whatever so sometimes I'll do that but honestly a lot of the time I'm using it at least for research and things like that in a very informal way I usually get what I need that way that like you're not ashamed to ask dumb questions to you right because it never judges you yeah that's right yeah yeah I often follow up with things like sometimes I guess I should kind probably think about I do different things but sometimes I'll write a question knowing that I probably need to ask more questions you know I'm kind of starting a conversation like with a colleague or with someone else where I expect there's more and I just start and experiment and see what comes back and then I'll adapt and change and ask follow-ups and things like that got it yeah I mean I personally use it I use chat GPT and Cloud the most and I use it to everything from like summarizing customer feedback to you know after meeting just like putting a bunch of raw notes in there and like telling you to make it more concise sometimes I even use it to just like you know when I'm trying to draft the product strategy or uh some of the higher level stuff just get a second opinion be like hey you know this is the strategy can you find some gaps alternative approaches have you found it good that could of do that well I think it's not perfect but it gives me material to work with right it gives me like a bunch of here's a bunch of options gaps maybe like half the things that I talked about are not really relevant but the other half are actually pretty good like that actually helps me improve my stuff like I almost never just like straight up copy and paste ai's answers into my stuff it's more like oh here's what you think and let me modify my answers based on what you say yeah that makes sense it's like a sounding board or like you know quality control mode as well do you think like cuz you know a couple years ago like I I personally never

imagined AI would be really good at making art and like writing poems and like doing some of the creative stuff that humans do so going back to the pro product world do you think the risk here do you think AI can actually make PMS like lazier and dumb thumber because we just rely on it for everything yeah I do worry a bit about it you know like posted LinkedIn a while ago um exact what I said but I wrote a post basically like AI will separate like even further separate the great PMS from the like average PMS or whatever and so that was a worry I had at the time I still worry about it I still think it's true and the kind of idea there was at least in my experience the best product people not just PMS but like designers too have like deep intuition and really excellent product judgment and kind of make bets whatever the turn to be good ones like you know later when you can kind of Judge them with like data or more kind of quantitative things and then like where did that good judgment comes from and often times it comes from a lot of talking to customers you know and it's very difficult to I think Bill's really good product judment without having spoken to like many customers over many years in your domain and so one thing for sure is you know think example if a team is doing a research project try to better understand the customer a problem or customer space and a PM sits in 10 qualitative hourong interviews or does ince themselves even better versus like asking you know some software to like summarize the 10 transcripts they're just night and day different things you know y night and day and I don't think I just don't think you can build great judgment from getting AI to summarize all the issues all the time yeah you know I've been mostly working at big companies my whole career and a lot of big company PMS like they don't even talk to customers right they just like there's like a user researcher that talks to customers and then they look at like a 20 Page slide deck of what the customer said and my opinion is like that stuff is useful but it never just replaces just like talking to five customers yourself you know like that's how you yeah very much agree and as I've guess moved into our senior olds over time like I run the product team now it's much harder to kind of find the time talk to customers you know and it's critical component I don't do it enough anymore I wish I did more of it I think he just there's a there's something that AI can't yet do I think in it maybe over time the be versions We can't even imagine yet where it'll do things like that but for now I think there's just you build this incredibly powerful intuition and judgment from talking to people directly yeah I mean like that that's how you built like a product sense right you don't build it by like following some 20-step framework you just like talk to like customers over a long period of time right and look at the market they you build pro process yeah I deeply believe that but like you said many people don't do it yeah I mean I think it's kind of like building a neur network in your brain a little bit like you know you just like make these connections that you're not even aware of and then you know when you try to come with the strategy or like a bu of product that you have these intuitions that actually make sense yeah totally it reminds me of I used to often say like pre AI days I used often say that I stole this from somewhere I can't remember where you every new idea thing as like a uniquely new idea like every new idea is typically a combination of two existing ideas but it's the combination that's new and so to generate all these ideas you just need to absorb and suck in more existing ideas so there's something similar it's the same kind of pattern matching that happens when you talk to like dozens and dozens of people and subconsciously some processing happening where your brain is like you know synthesizing and it'll resurface back up in the future at some stage yeah exactly what do you think about this like a lot of people on

LinkedIn are like calling themselves like aipm now ai product manager certification and I just feel like there's like a lot of noise here in this industry of the hype so from your perspective like what are some good ways for PMS and designers to you know scale up on AI quick quickly and ignore abortion actually like you know learn how to use this stuff I think at the start of any of these um changes and like you know it's a different way to describe this I think we're at the start of a new era in technology like one of the big waves you know maybe the last big wave might have been mobile but yeah these things kind of T typically happen every kind of 10 20 years these big super cycles of tech I think we're at to started one for real I think AI is going to it's going to be obiously transformational society transformationally transformational and so at the start of these things people gravitate to the words and the terms and things like that companies do it too you know becoming an AI company or having an AI product as opposed to a product or a company I think in the future the foreseeable future all companies will need to be AI companies all aipm it's just it's the new it will be the new standard and so for now I guess people are trying to differentiate themselves in the market maybe but I think it all just go away like mobile like you know we used to have like mobile first websites or like a mobile first strategy and then we had just mobile only companies SN and the already G it's the same it's going be the same so the hype will go away but like you know like you said it's a real wave so it is important to spend some more time to actually skill up on this stuff now so is it just you know reading all the AI blog post or like what's the best way to scill up or that you personally found to scill up yeah I do read a lot again like similar talk in the cious you only have so many hours in your day read more I do think reading is a big part of it I use Feedly personally and then just have a bunch of different sources going into it and I kind of B through it you stuff comes in I think a lot of it I read quite quickly just got I kind of hope it goes into to my brain and some of it sticks around and then these patterns emerge later you know so reading's a big one I read things like the rundown is like a kind of a newsletter that iates lots of different news and sources that's really good because reading the rundown spins me off into like all sorts of things that would have never found anywhere else you know so that's very good trying stuff matters too like when you could build your own GPT I built a piano teacher GPT and it didn't help me get better to piano but GI so you have to try this the products too and try the new things that come out I think that's really important just to stay of rest of like what's happening you know like one thing I haven't done for example yet but I intend to is a good example it's like all the YC companies are kind of like emerging from The New Batch and there a ton of fascinating stuff so many of them are like AI companies and by you just need to go and try their products and maybe you can sign up and maybe you can't or maybe it make sense or maybe it won't but you just got to try the thing as well for real to build an intuition for it so reading trying things is typically what I do yeah I in I'm lucky we have an AI team here see here has actually been around since the kind of mid 2010s I learned enough from talking to them to be honest like you know we different slack channels where we talk about all the latest and greatest in the world Ai and they educate me on new things how things work speculation in the industry new types models like when the latest version of Cl came out you know those discussions there about what why or how it might be better or not or you know Tech things like Tech technal things like that for example so colleagues are a big Source too yeah like are folks on like are folks like ml phds or just people who are or bit both people who are yeah both for sure yeah our team used to be call team ml back in the day they rebranded sense they had AI team some yeah some of the folks have phds they're like deep Specialists but the team has to grow like we're growing the team is you know in big ways we lots of open roles in the team like I'm sure many companies do so we're also think like retraining is the wrong word but like upskilling or other engineers in the company who want to learn much more about this world and there lots of them and so you know folks that have been there come for a while and worked in the kind of classic product engineering well are now joining the AI team and learning the learning that world too so yeah definitely a bit of both yeah so maybe we can flip this question around like as you're hiring for PMS or designers to work on AI products what kind of qualifications you looking for or like what kind of skills yeah I'll give you my kind of personal philosophy I guess you know I'm

a big believer in generalists maybe I'm a generalist journalists people who actually display like different types of attributes as opposed to any kind of hard skills so for example people who are curious ambitious people who kind of believe they can turn their hand to new things and do them and they're kind of doers and makers like inventor kind of people you people who like have made things and have built things and tried things I think those types of people can learn anything and so that for me personally like when I interview people that they're the kind of things I'm looking for obviously it helps these days if people have technical knowledge and so on but with AI it's so new to so many people and it's going to be so big we have this like massive gap between like all the types of people that we need to hire and the people with actual experience and so for the most part same as mo mobile you know I worked in Google worked in the mobile team at Google when the iPhone came out and then prior to the iPhone we were building like j2me apps like the first versions of YouTube on phones and stuff like that and at the time it was people had to like learn mobile you know no one knew how to write mobile apps no you had to design mobile apps you know when the iPhone showed up was a completely different UI Paradigm nothing like anything anyone had seen before and so there was no like way to do it so just regular people like me and others just applied our hand to it and learn try to learn it you know I think we're in the same world there where I'd much quicker hire like someone who was who didn't really have any AI experience necessarily but they're curious and ambitious and like really wanted to learn and were try like trying things like theyd built a few gpgs or they' like were reading the latest and greatest news and things like that versus someone who might have had like 12 mons experience building an AI product got it yeah you want people who have the kind of curiosity that they kind of get their hands dirty Tinker of stuff themselves right yeah and open-mindedness is a huge thing too I think like it's very easy especially people with more experience it's very easy to like not necessarily dismiss the new tech or the new era or whatever but you can definitely get caught up a bit in like trying to hold on to the skills or knowledge you had in the past and I think AI is going to completely make redundant loads of like classic lessons people think are universally true and last forever so I think open-mindedness is a really big one yeah like applying some past companies processes or patterns to a new company you know it typically work that's right exactly very R works yeah let's talk a little bit more about building AI products how it's different from a non product so you

and your team delivered Finn which I think is one of the first AI chat Bots right after chap CPD came out and I believe it has handled it's a customer support bot it has handled 8 million customer queries it has resolved 80% of them so what are some of kind of your most important lessons in building thing and like AI products at intercom yeah I'm trying to give you a tiny bit of context first us maybe when sh GPT came out literally over the weekend that after I think one week can't remember but literally over that weekend we being myself and other people like Owen or CEO co founder dad you know co-founder it changed our mindset changed our world literally overnight we were like this is one of those moments you know we are around long enough to have seen a couple of others like I mentioned the iPhone earlier it's just one of those before and after like before was I guess pre then after it's like everything has changed and we just recognize it as one of those moments I think and took a B on it and so prior to that we did have like an ml team like I said we did have a product called resolution bot it did answer queries customer support queries and when resolution was set up pretty well it did it really well but it was so manual to set up like you had to give it all the answers all the content it would suggest hey I think these are the answers to the questions and you'd have to like go yep that one no that's not right you know be very manual when it was really good it could do it could for some people could do up to 50 60% queries but no one did it you know not no one but very few people actually really spent the time curate all the content and the next thing chart GPT shows up and it's already kind of better you just by having consumed the internet and so now there's no manual setup you know now obviously since then there's tons of training that we've been doing and all sorts of fine shuning and stuff but out of the box it was really good with no setup and we were like okay this is like before and after before was most Bots are kind of crap you know honestly like pretty crappy experience because they not set up well they just not great product and after is like oh the out of the box experience of the bot is actually pretty good and so we completely changed our road map and strategy and said we must invest immediately in building a powerful llm powered bot and so we did we built it in we shipped it I think 4 months later and it's been uh transformational you know it's been totally different like all the numbers are just night and day different added the box then was able to do kind of 25ish 28% of queries just by doing nothing just by turning fit on and giving it your knowledge base content your support help content and now it's still an average and then now it's at 45% a year later so if you look at the graph like it's a bit jaggedy but it's just up and to the right we've added loads of power to it can do lots more things now but now it's at 45 48% and that's the average we've customers many customers who got 60 70% you know which totally changes everything about their customer support experience changes their customers get like instant answers and the economics all change so yeah we went all in really early we are all in now like fully all in on AI but we went in early and learned a lot early was the like the team that shipped the initial version of thing or like is working on Finn was like a small team or you just put everybody all the PMS on it or yeah do it no it was small well people he me listening to and like was it wasn't like called Hans on Deck we're doing it the whole company is doing this we have like set up incom that we' lck on some product teams that are fairly independent the teams are like you know eight to 10 people they work on part of the product and then those areas teams are grouped into groups kind of classic setup so I kind of remember honestly how many work on in it might have been two or three teams maybe so you're looking at maybe 20 people I don't even think was that big maybe 20 people on the R& D side on the product engineering side and then like it was as big a LIF in the marketing side once we wanted to Market it we were like hey we need see this property this isn't just another bot this is like an agent it's an AI agent really or at least that's where it's going and so we had a big marketing side to the launch as well which is so a lot of people ended up working on it in the end but the majority the vast majority of product engineering at the time did not work on fin initially got it well I think Finn is interesting because I think customer

support is actually like it actually is like a really good fit for AI in my opinion I haven't done a ton of customer support with like Tech products but like my customer support experience just like using Comcast or something right I calling it's like terrible man like you know like this morning I called my retirement account company and like had to use my voice to navigate and I kept on getting it wrong you know like I would tell it information through the bot that then the person that I get ask me for the same information yeah so I'm curious like well this like a bit of a side but like how did a customer support industry come to this state you know like is really devolved in my opinion yeah like I think you're appra it's fair you know I would agree with it I think customer support for the most part is pretty bad and everyone I'm sure everyone listening you know can guess resonates with most people even customer support people when you talk to them you know they would say yeah most of cust sport I experience not in my job but is bad so I think it is bad and I think it's due a revolution M hasn't seen like a ton of innovation in the last 10 20 years so I do agree with that one interesting thing is just kind of a side note people tend to think therefore that like people in CS don't really care or you know sometimes when you're on the phone to people that may feel like they don't really care but that's not really our experience when we do research with our customers sport leaders and certainly and managers they care deeply uh they're trying really hard but it's just the whole kind of thing is broken now I think AI is going to fix this which is an incredible opportunity I think it's going to transform customer support because llms are really good at what CS people do which I can elaborate on but I think it's going to change it but for now like the economics are kind of broken so there's more and more people going online more businesses going online more and more people have questions we're moving to an Era where people prefer messaging as their kind of communication channel so it's easy to message so more questions from more people but you can't just keep adding more head pen to the customer support team it just doesn't economically work that way and so teams are under pressure to answer the a lot of questions so a lot of the time delay is just people trying really hard to get through the backlog of customer questions that they have so that's like a big part of it I think Legacy software I think I mentioned earlier is another problem like just not much innovation in 10 or 20 years a lot of cluster sport teams like Comcast or whoever I don't know who Comcast use but or what product they use but just Legacy systems don't really talk to each other don't integrate well hence like oh hey Peter thanks but yeah you know what's in the back of head is the system my colleague use to ask you all your details it's not the same thing I'm looking at so I got to do it all over again you know just stuff like that has been bad and maybe the thing that's held it back whil is businesses don't see it as strategic you know they lot ofs will say customer experience is Paramount but when it comes to support team it's almost always in a p& l a cost center and something that's needs to be M costs need to be managed and things like that so it's a bunch of things got it so it's not really seeing as a revenue driver or like it's kind of hard to tie it to some sort of Revenue kpi I guess yeah like the kpis for customer support are things like you know a lot of them kind of come back to kind of you know econom unit economic stuff but like first you know time to like first time to resolution First Response Times Like These are customer satisfaction scores and customer satisfaction metrics but underneath them all is like trying to manage the workforce you know big part of the customer support manager's job is managing their team and trying to get as many of the people in the team to answer as many questions as they can really well which is really hard to do so maybe you talked about f a little bit maybe talk about how intercom holistically uses AI to solve this thing like to both make the customers happy and the customer support agents have happy too yeah so I think it's a fascinating case study by the way obviously like I'm mired in the world this world of customer support and AI but I do think it's going to be one of the very first really positive changes that would happen you know a lot of people like to talk about where whether AI is going to be good or bad for us and maybe won't do good things at times and so on I think customer service will be one of those areas where people can noticeably see how much better it is and the reason for that is like I said earlier it just turns out like you know through no Grand Design I don't think it just turns out that a lot of the things that LMS are really good at happen to overlap heavily with a lot of the things that customer support reps do like you know Converse back and forth answer questions ask clarifying questions summarize information synthesize different pieces of you know information content and so on but the AI can do this faster than a person and it can do it 247 in any language you know so suddenly it's like really good at this did this needs to be clarified that this is like for now the simple simpler questions you know customer support questions come in like different flavors you have simpler questions like you ship to Ireland or you know even things like is my flight delayed or things like that they a pretty clear yes no answer but then you have like more complicated questions like trouble shooting or like people can't really not really sure what the problem is it could be a bug or product problem or you know could be product confusion it's just really and a lot of troubleshooting like get turned

into like I need to contact the engineering team or your bill is wrong I need to ask my finance team you know so these complicated questions are still done by people but AI is answering all the easy questions and getting better and better it's starting to take actions as well like actually change things and write back to databases and so on write back to systems so it can do things like change you know oh my flight's delayed can you please change my flight yeah I can change your flight you know with the right permissioning and set up it can do actions really well and people are then left with all the hard stuff which actually is good makes the job a lot easier or like probably harder m j more interesting lot more interesting and in that world AI is going to change everything as well because all of the human reps answering the hard questions are going to have a co-pilot you know we've been building in co-pilot for the last few months and it's also transformational you know it's as transformational as the fin agent is so this whole world's going to get changed well it's take example of a hard question like you know that people that you need a human yeah um there's different flavors of them so one could just be someone might literally write in the product doesn't work anymore you're like okay what does that mean so suddenly you're into like and and the agent can do a lot of the back and forth like you know okay can you clarify what you mean or can you tell me more and it can start to disambiguate and sometimes that might result in the agent the AI agent answering the question but sometimes it's just unknown you know like maybe there's a bug maybe the product isn't working properly or maybe there's like bad data somewhere along the line or you know it's just really unclear and it takes a lot of Investigation across kind of different teams in a company a companies get quite complicated so it can take a lot of different people from different teams before you get to a resolution now like so that's an example well it's kind of an abstract example but something like my bill is wrong you know hey it's $97 I I'm supposed to be on like $43 a mon that could be a lot of things it could be all sorts of system problems in all sorts of different parts of the company and it requires like troubleshooting and back and forth and so today people use ticketing for this and tickets so today ticketing works pretty well but it's expensive and hard and over time AI will certainly get better at this and AI will help desember it'll the AI will certain to talk to all the different departments and then the finance AI with copil will talk to the engineering AI co-pilot you know and that like it'll definitely start to answer more and more the hard questions for sure I think like over time who knows how fast this will happen but it's happening even faster than we thought it would over time it'll get down to 5% maybe of questions might be answered by people and then usually that's a strategic decision like hey our VIPs always get humans or yeah there's some reason like or we hear this from some our customers like we differentiate on really personal support and Bo and like box AI agents they're not humans they're of empathy you know they don't have these human qualities and so we want people in the mix we want people talking to people and then you know the differentiate or not so we'll see we'll have to see how it plays that yeah but I think you can challenge all that too right like you can make the bot very personable too like the bot can just remember all your past conversations yeah like nothing like going back to keeping open mind like nothing impossible at this point no not at all and I do think over the course of like you know years many years is it what's that one is it two years or is it five years I think over the course of a small number of years the vast majority of customer questions so I'm saying like 90% plus will be answered by an agent an AI agent because they're just going to be faster quicker accurate and like a lot of the time customer support questions it's not like the customer wants to talk to someone you know that's just a means to an end just want a resolution or an answer and if a bot or an agent can do it like excellently

instantly that's a better customer experience just a way better customer experience so business would be like well of course we should choose the way better customer experience that our customers load and then that you know that actually I think is also great for the customer support industry it frees people up to work on much more interesting things I think rather than like answer the same question over and over again you get to work on things like hard question questions or as more and more of them get answered you get to work on designing the system you know like we already have a role here in com called conversation desire and so they're designing the conversation path like how you know how does the bot work and when does it fire or who gets what type of experience and so on so there be loads and loads of cool jobs and the B is only have as good as the content and data that it's sourcing referencing and so there'll be just really new types of jobs too on the content side the data side so I think for CS people is actually really interesting new types of career opportunities yeah I think so yeah because right now it kind of sucks being a CS right like you get yelled at by a customer you say the same thing like reset a router like 100 times yeah it's like gig yeah yeah so I do think it's win you know a lot of people talk about you know will that mean like fewer jobs and Cs and so on but a lot of people use those jobs as stepping stones into other types of careers as well so I think of the work I just fine actually and it'll be like I said a great example of like AI being applied and making things genuinely better awesome let's go back to kind of building AI products building fan other products do you have any kind of like native like principles like I buil some AI products and you know for example is it still really important to start with customer problem like what about the issue with this thing just like infinite amount of Ed Edge cases right it's very hard to be deterministic with what this thing actually does yeah we here's a funny kind of experience I've had I like

you know said I'm a generous I'm kind like a jack ball trades master like I've worked in as an IC like individual I've worked as a PM designer worked as a researcher and as a result of that kind of like doing all the those types of roles I was very much into like you must start with customer problems customers that's always the starting point and I guess I you maybe like reacting a little bit to like parts of like career in other companies where is quite used to talk with Google quite a lot I there like just people would start with the tech you know they start with the technology and like B think they were cool and that they thought were interesting intellectually interesting and stuff and like all the failed products resulted out of that like no one actually cared it was a solving a real problem so at intercom we have these three principles upon which we build all of our process I always say to people like I don't really care the process is there to follow the principles but if you follow the principles and don't really follow the process I don't really care but I care a lot that people follow the principles I only three of them and the first one is says start with the problem and the only two by way are like think big start small and ship to learn and we've changed it a bit over the years we've already one about outcomes now deliver outcomes because we were out very output focused but the first one start with the problem with AI we don't do that necessarily and I've have to like okay wrap my head around is this good or is it bad and a lot of it is around the idea that like we don't really know what's possible with AI you know and we're learning all the time we're getting new models all the time the thing is moving at break next speed and so like I giv examples with it's concrete you know we're building a new product and like for support leaders so what do support leaders do they analyze information they look at do a lot of reports insights trying to figure out how to improve their customer service through dashboards and we're like AI is good at that AI is really good at that kind of stuff like sucking information reports data generating charts like amazing but is it possible like CH GPT can generate a chart but kind of can our like CS trames you know AI model actually do it for real and we don't know you know now we've built some stuff and working back in places but we don't know and they don't know what's possible and some stuff doesn't work like when we building co-pilot which is you know a conversation you can talk to the co-pilot as a sport rep and it's basic a buddy to help you like github's co-pilot and it's conversational and it can it's really good it can help you a lot but when we're building it we built a different thing first and didn't work and we thought it was going to be easy so these days I say to people like we you know we got to be open-minded maybe we start with is this thing possible and if it's possible then we can map it to a customer problem we know exists for real so it's a bit like chicken and egg and I've always followed this like or I've always put forward this like problem first solution second but those days have changed for sure maybe it's just about can you repeat your principles again it's a start the problem yeah start with the problem I think I'm going to I might actually get people in interc will laugh at me for probably getting the name s you're WR I'll tell you what the ideas are behind them start with a problem that's basically like do proper customer research properly understand your customer make sure that the problem is real and make sure that there's high energy around it like often times you can have a problem a customer problem that's real but they don't really care you know and I've worked on many projects over the years where like we solved the real customer problem and then no one used the product then we go why are you using the product Oh I don't really care about that that's real it's good nice I like what you did it's cool I like it but I don't really care so high energy you know that's what that's the first one and then our second one is we it's now says as far as can remember think big start small ship to learn so we used to have think big start small and ship to learn as a separate principle we merg them so think big means like think big have a vision for the product space like think about what it might look like in a year but don't start by building up you know start with the smallest time solution to the problem you existed so there is some order to these understand the problem deeply and then start small like we're like we try and be rootless on scope and like get creative on the smallest possible that's the fastest to build and the fact and then ship to learn ship it maybe we got it wrong maybe something didn't work out properly maybe the research we did wasn't quite right you know so ship to learn is part of now think big start small ship to learn and then do that a lot and then you can kind of like really get good fast and then the third one now is called we changed it and shipped there and got it moved in the third now is called deliver outcomes so set some kind of success metric up front what does success actually look like I'm make sure you deliver that outcome don't stop it like we ship the feature stop it and people used it I really like how I really like the second one think big star small ship to learn cuz a lot of people online talk about like there's EX

ution and there's strategy right but like in reality the two things are like really tied together like I worked at companies where people have a big Vision they think big and they don't ship anything for like a year ship thing and they finally ship it's like a water down version of what they thought about and no one wants to you use it yeah absolutely yeah that resonates with me too so yeah to me I don't know if you agree with this like but like to me these two things are like heavily tied together like strategy and execution you're going to have a point of view but you got to execute learn cuz like most likely your point of view is probably not correct or need some adjustment yeah absolutely we I'm trying we used to have like a different saying and journey in come years ago oh it was be confident but humble that's what I used to say it wasn't the principle it was more like a value culture value was like be confident but humble what that meant was like build up the confidence to think you've done a good job like you did good research you did understand customers they were involved in the process you know and but be humble like we're probably wrong here we're definitely wrong somewhere there's no way you get you never get anything 100% right so there's something wrong in here and then that kind of gives you like or puts you in the mindset that like this is kind of messy you know it's a lot messier than people make it out and I think strateg execution similar it's a lot messier than people trying to make it out and in reality like there's a con there's is constant feedback loops you know and with our with the strategy Ducks we write at intercom at least certainly strategy I right I I'm always forever saying to people these are live these change they change all the time I know it might be a bit chaotic confusing I yes I did change it again last week and that's far way I'm trying to communicate the change but the strategy docs should always be live in my opinion and changing now like does it need to be careful to change it too much or like you of total chaos yeah but I mean in the AI World it moves so fast that these things are going to change fast yeah as long as people like just want to find a truth you know it's like some the changes are pretty obvious right because like we learn something new and like just got to it's got to change it yeah what about organization design I mean since you're like a cheap prod officer what about like when you want to make a big AI bet like a z to1 bet do you like you get the CPO or CEO to personally PM this thing or you like get like four teams to combine to one team or you just get like a small team of like really good people to work on this first yeah definitely small teams I in we come definitely gravitate to small team teams and try to give teams as much Independence as possible so we try and set up the strategy and a road map in such a way that teams are fairly free to set their own road map as long as they follow the strategy and then follow the principles so you know follow the strategy follow the principles and then we've lot and lots of individual teams even when we create new things I'm trying to remember like and I think I said was one to two teams there's the AI we are we have a separate AI group okay we were talking about that earlier and the AI group originally was like a small independent team but now of course it must be everything eventually all teams must be AI teams ultimately in the foreseeable future and so uh We've started to blend them a lot more where some of our regular folks like I was saying kind of go and you know learn about AI some of the AI folks go and work on projects outside of the AI group we're trying to like move to a world where it's much more Blended but still small teams like even if we're building a brand new product we will try and keep it to like that team or two teams which is somewhere between 10 and 20 people yeah this is why there like the thing like PM's influence with authority I'm like dude like if you spend our time influenc of authority you're not really learning from the market you just give me a yeah you know you gotta make you got to do you know D I think like directly be very close to like the work do you just like a few more questions like when you set up a small team do you give them like a okr or something or do you give them some like how do you set okr around learning or like not just like you got to get to like a million da right away like you know how do you give some R we don't do okor we kind answer this question personally I'm really big into goal setting so I kind of obsessed probably to I know it's not healthy for me but I obsessed with goals and goal setting and so like for example in my team I set weekly goals every single week I set quarterly goals and then I set weekly goals for me and all my team do it and we all set weekly goals and then teams set weekly goals so all these product engineering teams all set weekly goals and then we work in six week Cycles so I'm kind of doing this backwards actually start around but let me keep going so weekly goals lad up into six weekly goals we six week Cycles we found six weeks to be this like Goldilocks time Horizon where it's far to feted that you can predict pretty accurately what you can and can't do but it's also far the fact that you can do a lot like you can build a lot in six weeks so it's kind of nice this nice goalie locks it's not too far ahead and everything goes off track but not too short term where you can't really be ambitious and then we do a quarterly road map and a kind of a half road map the quity is kind of checkin the road map is actually these days more like six months actually so six month road map and each team has their own road map each of these individual small product teams has their own road map and so and it Lads up to the strategy so we have our kind of product strategy and then people can see which piece of it they own it's kind of pretty clear in the intercom products like there's a human support group they own all the human support size like humans answering customer support we have an automation side like all of the nonhuman answered questions like fin AI agent and things like that and we have a platform group you know work on things like Integrations and interoperability and stuff so it's pretty clear which prod they own and then from there they set their own road map set their own goals execute to the goals and that's how it works and it works really well historically we've been very good at shipping like output you know quite predictably because of the people following the principles but it's changed in a bit where I know where yeah you know we'll see yeah well see so okay so basically you're actually the teams set their own goals and like as long as you agree with them like you know like hey yeah personally I'm not involved some sometimes I talk to other like cpos or heads of product and they think I is kind of crazy in some ways but I'm not involved I have a team below me who are like a combination of PM leaders and design leaders and then research and data science they actually approve all of the road maps they're in all the road map meetings they do all the approvals and I'm operating at the kind of strategy level most of the time and then again things will bubble up or I might care about something you know more than something else and I'll dig down a bit or whatever and try and shape an opinion but you know the we try and stay at the right zoom level try and have people so the teams themselves and the group level set the goals set the road map and most of the time it works like it's very rare it happens now and again but it's rare to be that there'd be like a significant course correction you know and then I think that's just because you have to have a really clear strategy for people that makes sense yeah you don't want to you don't have too many people staying at the next three months level otherwi it's like you kind of just m micromanaging them too much yeah I think the zoom level thing is a huge if you can get it right everyone feels empowered at the right

level and yeah it just frees up people's time as well I guess last question I think it's kind of like a privilege to be like a product person when this AI Revolution is happening right is like it makes things so much more interesting again yeah do you have any closing award advice for people who are watching this or people who are re reading this to yeah I agree I think it's a it's an incredible privilege I age myself with these comments like I'm kind of like old enough just about to kind of seen kind of three of these things the internet was the first one you know when I was in school there not internet really you know and it was when I was in college that it kind of became a thing and so the interet happened that just changed Society deeply changed how Society operates M and then the next one kind of 10 years later call it mobile call it social you know but like the people forget like if you know if I want to like see what my friend who lives in the other side of the world is doing I can see in real time HD what they're doing they can video call me like check it out not that long ago you had to like take a photograph print it put it in an envelope and post it to the other side of the world you know like it's transformational societal change and this is another wave of that it's the next wave and I think that AI is going to be much bigger than mobile I think it's going to be bigger than the internet I think maybe we're talking like Industrial Revolution stuff here maybe we're actually talking about you the industrial revolution could changed how people live and work maybe we're talk urbanization you know people moved into cities and factories and all sorts of stuff we could literally be talking about like a complete change in how Humanity live and I think it's incred L fortunate that we get to try and help design that world like you know how looky are we I agree with you I think it's a privilege a responsibility too not to do itly you know but I think it's a privilege I think it's an amazing time to work in software amazing it's like the whole world's been given a new birth new energy I think it's awesome so you think it's just like being open-minded approach it from a beginner's perspective again I think so yeah like here's kind of something that really kind of when usual I think a lot of people thought AI was going to take you know like lower pay jobs and just like kind of just Revolution kind of change things but like factories and Robotics in the early in like you 50 years ago you know cars are now made by robots but cars used to be made by people you know and actually like what AI is really good at is all these like knowledge worker jobs you know us basically all of us and you know back to the I've earlier you know AI can help you be a PM a AI will be a PM and it's I think it's going to really change what work looks like and I think the way you thrive in that world is you stay yeah beginner mindset like real true maybe most of what I've learned so far is going to be Irrelevant in five years and my jobs going look completely different than it does today and 80% of the code for my product will be written by AI not by people like just all sorts of things going to totally change and you have to have that like willingness to just shed the knowledge you've built up very hard to do but necessary yeah I think so I think especially you know I don't know about you but like I'm pretty old too and like I have kids and stuff and when I was younger you know I like sometimes when I like play with some AI tools on the weekend I'm like am I wasting my time here like should I go back to write my PRD or am I screwing around but actually like this stuff it could actually be the job of the future right like the r PRD is not a job of the future it's like playing all these like music tools playing all the AI tools and learning what's possible so I think that's the important part of the process yeah totally you know the I don't know what the skills of the future look like but certainly like people I think people who make things and try things in these types of periods of History the people who actually go and make stuff and try stuff and you know hack at it like the word hack has a kind of can have different connotations but you know I think hacker culture is good and healthy and positive and awesome and you know I'm sure like 100 years ago the people who are winning were making tinkering and making stuff mechanically or whatever and I think the same is true now and I think yeah a lot of the job in the future might be a lot more that type of thing totally agree man all right Paul well thank thanks so much for chatting uh thanks for having me yeah enjoyed it