Category: No-Code

  • Contextual the no-code platform for mobile and web app Digital Adoption today announces new pricing including a new Free version.

    Contextual the no-code platform for mobile and web app Digital Adoption today announces new pricing including a new Free version.

    July 3, 2023, Contextual the no-code platform for mobile and web app Digital Adoption today announces new pricing including a new Free version.

     

    New Free version Contextual Track & Guide

    The newly announced Free “Track & Guide” version allows product growth teams, Product  Managers and Growth Marketers for Mobile and Web applications Track app usage and provide entry level user onboarding walkthroughs to help guide users to their usage goals.  Contextual Track & Guide is free of charge for up to 10,000 monthly active users and provides the following capabilities;

      • User reporting and analytics on user engagement
      •  daily installs and retained users.
      • Tracking and Reporting on screens and pages.
      • Up to 2 concurrent Guides – page and screen level announcements

     Plus more 

     

    New entry level Guide & Retain

    Starting at just US$100 per month for up to 10,000 monthly active users Guide & Retain provides next level user analytics and a suite of user onboarding tools to Guide users to sustained usage.  Guide & Retain provides all of Track & Guide plus the following capabilities; 

    • Additional Field Level tracking
      • 5 Features (Buttons)
      • 2 custom tags
    • 10 concurrent Guides
      • Guides, Tips, Videos, Announcements,
      • Per page FAQ
      • In-app Feedback surveys
    • Guide Analytics
    • Feedback (NPS, questions)
    • Limited Feature Tracking

     Plus more

     

    Guide, Retain & Grow

    Guide, Retain and Grow is for product growth teams planning for the next growth inflection point.  Starting at 10,000 monthly active users Guide, Retain and Growth offers all of Guide & Retain plus. 

    • Integrations with popular analytics products:
      • Segment, Mixpanel, Amplitude, Webhooks plus more
      • API Access (extended)
    • Extended Feature tracking
      • Screens/pages
      • Fields
      • Buttons
    • 50 concurrent Guides
      • Multi-language Guides
      • Rich User Targeting
    • Segments and Goals

     Plus more

     

    David Jones CEO and Founder Contextual commented “we are really excited to be able to put Contextual’s capabilities in the hands of every product manager, growth marketer and growth teams who are aspiring to make awesome products”.

     

    About Contextual

    Contextual was designed to understand your consumers’ needs and assist them in their journey to product adoption and retention by giving them a tailored experience. As fierce devotees of Pirate Metrics (AARRR), the company’s mission is to:

    •  help your users understand your core product utility,
    •  deepen engagement by Progressive Onboarding.

    Most Apps have around 30 seconds to attract the user’s attention after downloading and roughly 3 minutes to give some usefulness to the user. Working with app developers, the Contextual team learned the hard way that without a compelling onboarding experience, your retention rate plummets.

     

    Companies tend to spend a lot of money on Advertising, Sales, and Marketing (the first “A” is acquisition), only to lose customers. Progressively improving a user’s education and comprehension of the product is a priority for the firms from whom we’ve learned. Testing and iteration, enthusiasm, and a focus on “the statistics” are all used to attain this goal. Retention, revenue, referrals, and business development are the prizes. We are here to assist you on your quest.

     

    Contextual is a product delivered by the StreetHawk company and was built on top of the StreetHawk Engagement Automation Platform. 

    Are you looking to get more users to love your mobile and web apps?  Click on the buttons below to get your 14 day free trial or contact us for a demo! 


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  • Generative AI + No-code – perfect storm?

    Generative AI + No-code – perfect storm?

    When AI and No-code intersect, what are the opportunities for product teams? Is this a whole new era of Product Led Growth?

     

    In this panel, we explore the impacts on developers and ability for apps to get to-market faster and without excessive development costs. We look at the Buzzy platform which takes a user from ChatGPT prompt to an App that is releasable in the Appstore or Google Play.

     

    A simplistic way to summarise the no-code landscape in 2023 is this table.

     

    Type

    Examples

    Glue and Engagement

    Airtable, Notion

    Zapier, IFFT, Mailchimp, 


    Contextual 1.0

    Web Builders

    Bubble, Webflow.

    App Builders

    Buzzy

    Dev Tools

    Co-pilot, ChatGPT, AutoGPT

    We can see that “no-code” really has been a category that has existed for decades of you think about tools like Mailchimp removing the complexity of designing and sending an email.

     

    With tools like Contextual, product teams can do “no-code” inApp engagement.

    With tools like Buzzy, by adding Chat commands an App creator can get to market with very few developer resources.

     

    The speed of AI growth means that the following question is not science fiction.

    “AI coding assistants such as CoPilot are only scratching the surface.. It seems totally obvious to me that of course all programs in the future will ultimately be written by AIs, with humans relegated to, at best, a supervisory role.”

    Matt Welsh
    https://cacm.acm.org/magazines/2023/1/267976-the-end-of-programming/fulltext

    I posed this and a few other questions from Lex Fridman, Sam Altman, Chris Lattner – all people who are trying to figure out the positive and negative impacts of AI on the programmer landscape.

     

    You will be surprised at the responses.

     

    The questions are in the deck below and the video and transcript are at the bottom.

    https://youtu.be/V2nVYmcCeSA

    Do you want to get more users loving  your mobile and web apps?  Click on the buttons below to get your 14 day free trial or contact us for a demo! 

    Get Started Get a Demo Contact Us

    Transcript

    okay so my esteemed guests tonight so so James you might as well start since

    you’ve got the mic so James from Deputy hi uh I’m guest slash

    uh venue host Tonight uh so I’m James staff software engineer at Deputy

    um and for those who don’t know Deputy is a uh sort of workforce management

    um platform time in attendance and fostering scheduling and things like that for

    shift workers and businesses around the world and you’re mostly an Android guy

    yes I don’t really pitch and call myself at Deputy yes but in

    the past I’ve done Hardware interfaces apis desktop apps

    mobile great very good thank you and Adam Adam is the CEO and founder of

    buzzy oh cool thanks thanks David

    um yeah Adam from Buzzy uh founder what do I call myself uh husband father gig

    Surfer um founder of Buzzy Buzzy’s a no code platform I’m a geek so I created a no

    code platform um we use generative AI to take an idea

    to create turn it into a brief into a data model into a design which is a

    figma file and then turn it into a working either responsive application

    full stack by the web or native in about 15 minutes

    so we’re all about accelerating things and making it easy for you to climb the

    mountain and I’ll talk about that a bit later very good so IOS and Android

    the um yeah so we used react native under the covers for the native ads so

    both IOS and Android and who knows what other platforms whatever supported whether we do TV and windows and stuff

    down the road but yeah at this point of time just IOS and Android right very

    good so um the folks who are online with muted you so

    um we get a clear run but if you want to put your hand up then we can actually go to questions at some stage so

    um I think internally here I think we’re kind of you look like a pretty orderly crowd so I think what we’ll do is we can

    take take any questions or or you know comments on the Fly because that’ll that’ll make it richer and um hopefully

    we get a bifo somewhere along the way right so so best just um next slide please

    this was this was really a dodgy thing I just did quickly just to kind of like frame up the different types of things

    that have been happening as I mentioned there you know there’s a bunch of tools that have been around like notion and their table that are actually allowing people

    to get a lot of stuff done and even prior to that you know whether it was if this then that or

    um you know zapier there’s a lot of stuff that’s been you know around sort of doing things without having to write

    code but in those in that case you know they’re just connecting different systems and using apis so

    didn’t want to sort of focus on any of those sorts of things MailChimp is would you ever think that

    mailchimps like no code well kind of like back in the day used to write HTML code and uh that allowed you to do not

    much at all because then you have to figure out then how to actually get it into a SMTP mail message and do all that

    and then when tools like MailChimp came along that actually turned that into a consumer usable thing or even better

    than a power user so that’s that’s an example of that and my company contextual is a little bit like that now

    for in-app engagement so the version that we do at the moment we allow once

    our sdks inside our iOS Android or web app then you can actually do

    guides and tips and tours on the fly so we’re not trying to be a no-code platform for developers or to displaced

    developers we’re trying to free up developers to push things that just like with mailchimpings you know instead of

    actually getting the dev to do the hard coding of HTML in this particular case instead of getting the div to do the

    hard coding of Engagement inside the application tool tips you know Pop-Up Videos targeting that it particularly

    uses particular points on that Journey you can use us as the platform for that and I’ll talk a little bit about that

    later on then you’ve got the web Builders which I mentioned briefly bubble and Diplo Etc

    public everybody fuzzy in there as well so well I put you down there which was

    absolutely what we do wear this one oh you do web as well okay my apologies

    um so and then we then we get into Dev tools as well too and I probably missed some other some other categories but

    that’s where we start to start to see you know obviously the the AI is starting to bleed in as the as The Iliad

    so definitely Adam’s on the front end of certainly Ai and no code that’s that’s

    great to have him here tonight and we’ll also talk to this chap here I’m sure you’ll have a few pointers on that and

    at least you’ll provide some more color on copilot and things like that as well too so

    is everybody okay with that does anybody think I’ve missed out a massive category that we should be talking about

    right cool all right so let’s have a look at Adam’s uh value prop is a some dude on Dick

    clock I’m allergic apparently you can just ask AI to build apps for you so I’m using to do that is

    Buzzy dot Buzz it’s basically just lets you turn figma designs into full stack web or mobile apps and it even generates

    the figma designs for you so you really don’t have to do anything Buzzy will even give you these giant component libraries that the AI can use to work

    off of and then you just go over to your app here there’s nothing here right now and you go to plugins and download the

    Buzzy plugin I have this AI assistant right here and I’m just going to ask it really quick create an app to host local

    basketball competitions I’m going to send that and it’s going to start generating me a brief and boom it’s done

    generating it’s finished it called it hoop Zone which I kind of love and then it gives a whole list of functions user

    roles team captain admin user functions schedule games scores tons of stuff let

    me go over the data model and I click generate data model and boom would generate a bunch of stuff different uh data models for standings scores games

    competition types things like that and we go over to markup and we click generate app design wow okay it

    generated 52 screens 70 components 150 Fields all of this completely automatically and then I just go over

    here and I’m gonna click publish and back behind it on the actual figment page you can see it just generated a ton

    of those screens all that completely automatically it’s wild Publishers do a QR code and I can just start testing it

    my dad this is crazy like everything just works there are Fields there are forms

    go to games oh my gosh that’s awesome if you want to give it a try you can go into the link in my bio it’s a little

    workshop website you can go to the tools Tab and you’ll see a link to it

    what we’re doing is we start off with the user prompt currently we’re using uh chat GPT IPOs GBP tool we then use that

    to generate the brief which think of the brief it’s like a functional spec you can iterate on that you can change it

    within take that and we generate a data model so one of the things we understood like we’ve had our figma plug-in that

    can be converted into working either web or native for a while we understood that

    designers and ux don’t always understand or find it hard to do things like the data modeling and then we take that

    um we take that data model the brief and a UI kit that’s in figma that is a best

    practices UI kit that’s responsive and everything and then we’re using AI to define the application or the app

    definition which is everything about that application but we’re not using AI to generate the code so the benefit of

    that is that once we put that into the Buzzy runtime we can then turn that into a website or into a react native

    application on the fly so we’re not using chat EBT to do the actual coding

    as such but we’re using it to describe the application and that just means that

    as a somebody who’s creating the app you don’t have to maintain all that code you do need to pay us to keep the runtime

    there but so it’s not for everybody but it’s massive speed of helping you know

    if the goal that’s what I was saying before the goal is to help you climb to the top of the mountain

    um some mountains are small we might get you all the way there some some mountains like let’s say if we’re going

    to go to Kosciuszko maybe we’ll get you three quarters of the way there if you’re mounting that you need a prime is

    Everest maybe we’ll get you to base camp but you better bring the Specialists and your

    pickaxes and everything like that to get to the summit so and by that the

    Specialists I mean that’s where you do need to bring in your developers and people to do stuff so it’s on a case-by-case basis so let’s let’s just

    kind of sort of um look at this practically so I want to do an app that actually

    shows me the locations of vivid David Sydney spots

    how would I how would I start I would actually describe give me a map based application yeah I would start with that

    prompt of you know create me an application Google and we should try this out

    um and you know these are the things each of the location perhaps has an image

    um it’s obviously got an address it might have times that that showing is going to be on

    um you also might want to provide things like reviews so allow people to put in reviews and then that will be your initial

    prompt and from that we’ll create that functional spec with a bridge but then you can add it and go on is that

    literally going and looking up a bunch of templates that you’ve got or is it actually describing the data model and

    you’re working backwards from the data model so so we were actually kind of Blown

    Away by what chat GPT could do and understand that we asked it that really

    it’s just clever prompt engineering under the covers so we started this journey we built the Buzzy Tech over

    several years um and a couple of years ago we put the figma wrapper around it and then for us

    because of the way that we just really trying to get to this data this app definition point that we can then turn

    into something um we really looked at how we could use um the llm to generate help generate

    that app definition so once we go that functional spec um

    the the llm was like insanely good at defining a data model like scaryly good

    so and you know it really surprised me I didn’t think it would like it sometimes gets stuff wrong and there’s subtleties

    in in you know how you name things like in data relationships and sometimes it gets confused but in general was was

    like you know I I did a Computing science degree and I can look at an application and break it into a data

    model in my head but for a designer who wasn’t trained as such or doesn’t think that way that’s quite a challenge and it

    could do an insane job of of generating ultimately the metadata so you can ask

    it for a data model for a lot of different type of applications and you can say you know give this to me and

    Json or SQL or whatever it is it does a pretty good job so James have you seen anything similar

    around that’s that’s basically going super nuts can I say that

    nobody knows I have no idea beginning to end yeah so you go right up to

    publishing stage right yeah yeah and that’s because of that history you’ve had building it before

    and so when you were building a you were building a an app creator platform then

    at some stage you said okay let’s take a from figma to that and now you’re using the GB team to go yeah so we’ve always

    been about how do we get like we started with life as like an ugly no code platform it was predominantly used by

    business people for creating apps in a matter of minutes so there’s like ugly back-end apps that you could say Hey you

    know you would go in and you would drag some Fields onto a screen and say I want to capture this data so people doing things like

    um mapping applications for field reporting and stuff like that that you know you see the people wandering around

    like reading meters and things like that um we did we started with life like actually doing things like sporting apps

    and all stuff like that um so we’re already we what we were

    creating was basically a platform that went all the way from concept through to

    actual live deployment um so now what we did is we now allow you to generate an app and then that’s

    deployed into like an Enterprise scale architecture so until kubernetes infrastructure that could be scaled

    horizontally vertically um there that you know it’s all single tenants so your own database cluster

    that again can be scaled separately you can break things into microservices um if need be so

    um yeah so right like we’ve been doing a lot of work with people around and we show them what we’re doing and they said

    they’ve seen people doing bits of this with AI um maybe you know generating the design

    into Sigma component has been no way going all the way end to end and actually getting something running on

    the cloud in a short period of time

    yeah I guess yes and no um as Adam said I think there’s a lot of

    people that have been doing bits and pieces of this for for quite some time

    um and yeah I I yes I have to assume that there’s

    probably a few um people out there who were as excited as you guys were like we’ve

    been building this thing for however long and now suddenly llms are just going to make our life

    so much easier like they augment what you’re even doing a really great sort of um

    no pilot I guess to what you’re doing now that’s exactly like we’ve always just seen it as an accelerator

    um like we’re seeing applications that are getting built with this that like I said if you’re climbing a big mountain

    we’ll only get you part of the way there you need to bring in the heavy lifters and your developers to complete things

    because no shying away from that I think we’re a long way from AI being able to

    do absolutely everything you need somebody at the home who’s driving this thing and directing it and prompting it

    and doing the coding bits to plug the gaps so I think that yeah so I think

    that’s what we’re saying it’s not a it’s not one size fits all and you can’t do absolutely everything with it yeah I

    think the probably the super interesting thing about all this to me is you mentioned

    before how MailChimp changed um the

    like exactly what a product person could do and then what they needed to hand

    over them into a development to get them to take the reins from their MailChimp shifted that

    um and over the years we’ve seen more and more products and I think from my maybe naive maybe not you but I

    think for me this is just another one of those big shifts in that direction

    um where I don’t think it’s gonna magically take away the Need For

    Engineers overnight um but I think like what an MVP looks

    like now is much different to what an MVP looks like five and ten 15 years ago because

    of how much you can get done without needing to bring in Specialists so

    and I think what’s radically changed too like not that I’ve made a study of MailChimp but I would thoroughly expect

    them to move away from templates to to generative stuff as well too and I think notion seems to be doing is there

    anybody a notion fanatic here the notion seemed to be bringing a bunch of stuff in really quickly which is unfortunate

    for me because I’m still on Evernote but such is life yeah so yeah you see a lot

    of augmentation that are actually in things Beyond just content creation it’s certainly around the design side of it

    and so it seems like these guys are on the front end of that so what’s what’s really been super compelling for you

    what are you seeing coming through as a developer and I’m going to ask I’m going to ask a bunch of questions in a second

    just in regards to the landscape but um yeah what are you seeing that’s super cool for you as a senior developer

    what’s super cool for somebody who’s uh you know a junior developer and what’s

    cool for people who don’t go we already know we’ve already heard about it I’ll start with Junior I think for

    junior developers it’s probably something that’s very exciting if you

    are cautiously using these sort of tools I think

    we all know chat jpt makes things up it’s just the nature of ROMs that’s

    always going to happen I don’t think that’s going to change anytime soon um so

    I think as as these models can take larger context windows and you can feed more real-time

    data into it things like that they will become a little bit more truthy um but I think the danger to me for yeah

    for a junior engineer or someone without a com site background or something is

    you you can be led astray and it seems so legit what it’s saying

    um so that’s one thing but I would absolutely recommend a junior to be used

    in this sort of tools because they’re exciting and then as you go further and further I think to me it’s a big

    multiplier on just how quickly I can get work done because instead of spending 10

    minutes Googling um some part of a standard library that I use

    I’ve been using for 10 years but I only have to use it every few months and kind of forget tiny little details so you go

    to a quick Refresher um so instead of spending 10 minutes now I spent 10 seconds get it and then I

    know it’s live because I’m like that’s that’s wrong yeah you can spot with hallucination exactly and I I think the

    where the tools really really shine is sort of the more Scene you get probably

    the more you could output from it because you don’t need to double check and you can tell it that it’s a bit

    dirty layer yes right yeah all right so let’s let’s go to the next slide

    the one that I oh not him again

    all right okay so this is a guy this is a guy called Matt Welsh and uh you know he’s

    he’s been pretty lazy he’s LED teams at Google and apple and he’s a professor or

    was a professor at Harvard of computer science so you might know what he’s talking about I don’t know

    um but anyway uh he says AI coding assistants such as co-pilots are only scratching the surface it seems totally

    obvious to me that of course all programs in the future will be will ultimately be written by AIS with humans

    relegated to at best a supervisory role okay so

    um he’s I’ve included the link there to the original to the original text so it’s it’s not like it’s a puff piece or

    just you know an opinion it’s literally a guy who sort of knows what he’s

    talking about so have you guys kind of agree with that and you want to dare to make a bet on a timeline or any of those

    sorts of things I won’t make it better on a timeline um but in I guess in many regards I kind of

    agree um I just think that the timeline is maybe a little bit further than what people were assuming I think everyone’s

    very excited about chat um but I think that

    if you think about what he said there you know my the owner of the company from my first

    job he started programming when with Punch Cards Right Punch Cards and for

    him he went right up to he’s probably still programming today but but him it’s

    just each thing is a new language and I think that natural language programming is just

    another new language I’ll be at a very cool one and it makes it a lot more accessible to everyone but I think that

    there’s always going to be people that don’t care about tech they just want to

    live their life do other things and they don’t really care to do the programming side of it so

    yeah well I agree with this but I also think that the supervisory role maybe is

    not the best way of putting it I think that it’s just going to be a different type of programming

    Adam might argue that we’re already you are already turning people into supervisors here it sounds yeah I don’t

    know if I agree with that statement um I think like having played around with

    you know the technology and sort of understanding that you do need humans in that supervisory role

    I think one of the biggest challenges you know that I see is that specifically like with code generation and app

    generation is when you need to debug something

    it’s damn hard now if you’re looking at co-generation um if you generate

    you know thousands of lines of code and then you need to enhance it without

    understanding that code that’s a huge challenge that I don’t know how we’re going to solve that

    now like I can I kind of look at it from a point of view have you ever had an argument with Siri

    we’re going like okay please call David I’ll be calling Mary no David

    oh what what time did you want to do that and no David called David and it’s

    like I think that if you’re giving instructions to the AI ultimately to get to set a goal for it to create an

    application at some point of time you have to have granular control over what that application is either to enhance it

    or to debug it so I don’t know how that’s gonna like to say that everything is going to just be created by Ai and

    you’re going to be able to issue some instruction doesn’t the instruction then just become the code

    like like I think the coding level will go up but you’re still going to have to have a way to granularly control those

    elements like you know maybe today you’ve got co-pilot and you know that’s going to help you to a certain degree

    and it right so if we’re using copilot for our developers and it’s it’s awesome um you know we talked about the the

    figma file becomes the code for us in our applications but that’s still the code

    um and then if we take it up a level and if so we’re busy we’re adding a new feature at the moment that you don’t

    need the figma file you just write the prompt and it creates the app for you how do you change that like oh no I just

    want to move that button over there move the button to the left and it’s like you know at some point in time you really

    just want to take that button and just move it there or there and change its color and and change it becomes cloning

    so I think coding will change um I don’t know if all coding will be

    done by AI um I do think this will need to be regulated um because I think there’s a lot of

    other reasons for that but that’s kind of maybe I don’t fully understand where he’s coming from and he’s way smarter

    than me but yeah but look I think regulation is a really

    tricky topic and I’ve lived in to you know you can say at one level it’s

    the cat’s out of the bag and you know I kind of look at it like knives and

    nuclear weapons you know they awesome Tech um that can be used for a lot of good

    and for a lot of bad um and there are rules out there that

    say okay right you can’t carry a knife of this particular size and you know on your body or whatever bring it into a

    class in school it’s got to be regulated so I think AI is incredibly powerful this is just my take by the way you

    don’t have to agree with me but I thought he was going to talk about regulation of coders but yeah so I want

    to and this is the kind of unfair unfun part of being a moderator of this

    stuff particularly with the AI ones that I’ve done I want to keep it on topic just in terms of practical things because there is lots of side topics

    that are super important but it’s being beyond the scope of this particular thing so I don’t know what what you’re

    asking me but just what we’ll do is we’ll we’ll just stick on the code side of it for now if that’s okay so

    um so Lex Friedman sits with Sam Alton

    under two and a half hours that feels like three thousand hours and asks a question wouldn’t that mean that

    there’ll be needs for much fewer programmers in the world and Auckland says I think the world is

    going to find out that if you can have 10 times as much code at the same price I don’t know what that you’re saying

    um you can you you can just use it to write even more code I think there is a supply issue and I was asked the

    question today doesn’t that need more code bloat let us know expand it’s not about more bloat inside an existing code

    but you can basically solve more problems on the planet before maybe we off the planet as well so just that that

    kind of question there so throw it to you guys you agree disagree I’ll jump in I’ll listen to a podcast

    recently um and there was an analogy about lawyers and there were there was a

    village somewhere in the US and there was a lawyer and he was kind of not very busy and another lawyer moved into town

    and all of a sudden things got really busy so I think the way I kind of look at that analogy is that everyone was suing

    everybody and I think if the more ability that we give people to write applications there

    is a finite resources of of coders that exist at this point of time I think the last time I checked was

    something like 0.03 of the world population the more ability for people to create

    applications the more requirement there are going to be for coders to come and fill the gaps I think

    we get to do the really fun stuff and not the boring stuff that’s my take

    mine is boring because it’s exactly the same as yours I think um yeah totally agree I think it just

    this whole thing is going to just change how

    it’ll kind of just free up people who are doing um work today in software development

    that tomorrow will be done by AI it’s not that those people disappear and

    have to go find new careers I think they just get to start solving more interesting problems um and they just kind of shift into I

    mean there’s with every new technology there’s always going to be some limitation right and then the Builders

    of that technology live sort of on the edge of those limitations and listen to

    feedback from from their consumers think okay how do we improve this how do we expand upon all that sort of thing so I

    think that that’s yeah I think that’s where it’s that’s the direction so I

    kind of feel as though you two have kind of um contradicted yourselves so you said

    before that the debugging’s hard but in fact at the moment the AI all that’s really

    good at doing is generating code that it’s seen before and debugging is not part of that so we can assume that and

    maybe it won’t be llms to do this but we’ll we so we’re seeing so Palm 2

    down to from Google allows you to have your own instance allows you to absorb

    as many tokens as you will say there are limits but we will get to a particular point with the more tokens could consume

    your code base and then you could actually have have the AI doing maintenance so that’s

    where I was getting to you know maintenance debugging that’s the boring stuff and you would hope that it’ll be

    able to do that but you said okay well maintenance and debuggings are the hard bit so that’s the unfortunate boring

    part of most development jobs particularly if you take over somebody else’s code um I’ll I’ll take this to start with and

    then I’ll put it over but I think that in my mind right it’s I don’t think that

    these tools aren’t going to be able to handle Depot and things like that I think that’s coming very very quickly to

    be honest um I wouldn’t be surprised if um Pope pilot can handle some pretty

    impressive refactoring and debugging issues by the end of this year

    um but I think again going to like what’s the edge of these tools and their

    limitations I think it just means that okay you’re no longer going to have to debug this one particular thing and the

    tool will do that for you but there’s another issue over here the tool does not knowing how to debug that and

    then that’s and I think that’s what I mean by we just will have to start solving more interesting problems and

    new problems that we probably can’t even comprehend right now um yeah

    yeah that kind of this is a complex topic um but I think

    I kind of look it a bit like like a repo so if you’re coding and you use like hey

    repo on GitHub or whatever it is you get it from um you kind of expect that code to work

    and hopefully you’ve never had to debug it there’s a few times where I’ve had to get into the repos and debug stuff and

    that’s really hard so I think like what I see what I was trying to say before is that

    we kind of like what is doing is providing more and more out of books the similar concept to repos that you can

    then just tie together with specific code that you will still need to debug and hopefully not have to understand

    what’s in those repos I think there’s different ways starting to like react native plugins for your stuff yeah there

    could be plugins there could be node.js or there could be whatever language that you know whatever whatever repository

    that’s out there on GitHub or or in other that you use um it’s just like that thing is like a

    black box that you hope Works per the spec and I think

    what like whether what I was talking about in terms of the fun stuff and the debugging like I’d rather talk about

    okay right how do we get that one that one that one side together with some code whether you’re using AI to help tie

    that stuff together or you having to use your own um coding skills I think that’s where it’s going to get you know really

    interesting um from a point of view of um there’s just so much capacity that we

    have to understand a chunk of code and I

    agree with you I think that that AIS as they increase the window size and everything will have more capacity but

    the question is how do you tell it what to do how do you tell it that there’s actually a bug over there and how does it then

    work that out I think there’s a huge challenge doesn’t it generate unit tests based on

    [Music] testing but um I think that yeah like

    I don’t know if I trust it this may be part of the part of the part

    of the problem like I’ve seen like I went in and I’ve grown okay right go and create me an application for this in chat GPT and it’s going you know out

    comes the application now write this for it and then I’ve gone okay is this code robust and he goes no here are five

    things that it does that it needs to add in I said can you please add it in he goes no find a developer no really yeah

    so and I’m sure it’ll get better at closing those games but I think it’s kind of like you get into the situation

    where it’s just creating more and more code and then eventually we need to find a developer and you’re going oh my God

    like there’s now 20 lines of code over here that I would never know when the world has ever seen except the AI yeah

    and it doesn’t we don’t know the instruction to give it to tell it to fix that particular bug yeah it kind of gets

    into an interesting conundrum okay great thanks next thanks best

    oh okay so this is my proposal which is sort of to

    do with you know if you’re going to write more code um then if you’ve got a if you’ve got

    off a lot of offshore developers and if you if you do if you’ve done a lot of offshore assuring like I have over the

    last 20 years you kiss you kiss a lot of frogs and most of them are frogs um every now and again you get lucky

    um you know a thousand offshoring companies you know are always getting my email and and Linkedin and so on and so

    forth they will be the big losers out of this because you’ll actually get a lot more done

    um without without having to sort of go through the offshoring process until until you get to that kind of like base

    camp issue or further halfway up the mountain issue am I completely wrong on

    this statement I have I have some thoughts on this

    um that feels like the intuitive answer

    that they will lose out in this but actually who’s to say that

    companies that run these um like offshore software houses choose to say that they’re not going to use

    um or the generative AI tools to upskill their Engineers

    um and end up producing some pretty amazing stuff exactly and not just that

    but like communication which I know many companies that I’ve worked for have

    tried offshoring at various sizes and one of the biggest problems was

    communication lines miscommunication with specifications code Handover things

    like that um if generated AI can solve a lot of those communication problems

    maybe they’ll maybe these guys become winners um yeah just that I have no idea what’s

    going to happen that’s just yeah I just thought maybe that’s an interesting point we did an interesting exercise recently

    which is we were hiring for Dev and we basically said you kind of must used you must use some

    sort of AI in the process you know we didn’t want anybody to sort of create a

    an uneven landscape so we just said you know really you must do that but we’re still able to figure out who were the

    who were the more intelligent developers because we’re asking them to it’s like the old open book exams in the sense

    that you you I kind of that’s the right terminal but you know you’ve got all the enough information but how you apply

    that particular Implement and so that’s again that comes down to offshores or Junior devs who are intelligent enough

    or understand enough of the you know the molecular level stuff or the macro in order to apply it at an application via

    anyway that’s just not