Talking Drupal #523 - Pantheon, Google & AI

John: This is Talking Drupal, a weekly chat about web design development from a group of people with one thing in common. We love Drupal. This is episode 5 23, Pantheon, Google and ai. On today's show, we're talking about Pantheon Drupal ai and how Google is getting into the mix with our guest, Josh Koenig will also cover AI image alt text as our module of the week.

Welcome to Talking Drupal. Our guest today is Josh Koenig. Josh has been working in the Drupal ecosystem for over 20 years. First as a volunteer for the Howard Dean Presidential Campaign in 2003 to 2004. Yeah. Then as a founder of Chapter three, a Drupal shop in San Francisco. And since 2010 has co-founded a little known, no, I'm kidding.

Pantheon, the WebOps platform for Drupal. Josh, welcome to the show and thanks for joining us.

Josh: Yeah, thanks for having me. John, Nic Hayden, it's it's great to be here.

John: I am John Picozzi, solutions architect at EPAM returning. I know I wasn't here last week. Martin, thanks for filling in. My co-host today are Hayden Baillio, head marketing dragon at Hero Devs.

Hayden: That's right. That's right. Good to be here. I got the baby in the background, so, just know if I'm on mute. It's because he's crying. There

John: you go. And last but certainly not least, Nic Laflin, founder at nLightened Development.

Nic: Happy to be here.

John: We're happy to have you, Nic. And now to talk about our module of the week.

Let's turn it over to Martin Anderson-Clutz, a principal solutions engineer at Acquia, and a maintainer of a number of Drupal modules and recipes of his own to talk about our module of the week. What do you have for us Martin?

Martin: Thanks John. Have you ever wanted to use AI to help content editors create alt text and image fields?

There's a module for that. It's called AI Image Alt Text, and it was created in August of 2024 by Marcus Johansson of Freely Give io. It has a 1.01 version available, which supports Drupal 10.2 and 11. It is actively maintained, has security coverage, and there are 19 open issues, seven of which are bugs.

Which is pretty good considering it's officially in use by 4,249 sites according to drupal org. Now with a module installed after a user uploads an image into an image field, they will see a button labeled generate with AI before the alternative text input. Clicking that button will send the image to an LLM to suggest alt text, which will be used to populate the alt text input in the settings page for the module, you can adjust the prompt use to accompany the image and choose which AI provider should be used.

The module creates an image style that will scale the image to fit within a 200 pixel square and convert it to A PMG for maximum compatibility. You can alter the image style if you want, or specify a different image style in the settings if you prefer. There is also a setting you can enable to auto generate the alt text as soon as an images uploaded to save users step.

With that enabled, you can even hide the generate with AI button, though that would make it harder for users to regenerate the alt text suggestion if they weren't happy with the first result. This module uses AI to make a suggestion for the alt text, but ultimately it is the responsibility of the user to validate the result and make changes if needed.

This aligns with the principle of keeping a human in the loop when using ai, which is definitely a best practice. It's also worth noting that this module is included in both the D-X-P-R-C-M-S and Drupal CMS site starters. So if you're planning to start a new Drupal site with one of those, you'll have this capability available.

But let's talk about AI image alt text.

John: I love this module. Do you use

Martin: it?

John: That's it. I, I just love it. Yes, I do use it. I use it on my my personal blog because I am lazy and looking at, you know, images sometimes writing all text, I'm like, ah, what would be helpful here? And like, you hit the button and it goes, Hey, this is what could be helpful.

And you go, well, maybe let me adjust this a little bit. 'cause that's a picture of me and, you know, I need to add a little bit more context, but kind of like, I don't know. It it, it helps you get, get that first draft out there and you, you can kind of iterate on it if you want. And, and sometimes it actually gets it totally right where you're like, yeah, this is, this is good.

This will describe this image perfectly. So, yeah, I love, love this podcast.

Nic: I'm curious actually. I mean, I. The idea behind alt text is for accessibility, right? To make or, or by not just access, well, I guess it's still part of accessibility, but, or if the image doesn't load describing what's in the image, right? I wonder if anybody's done a full blown analysis yet from an accessibility standpoint of these descriptions, right?

Because a lot of it is subjective, right? An accessibility audit will flag missing alt text, but that's not real like an automated accessibility scan will will flag it if it's missing, but it doesn't really evaluate the quality of it. Like if you have a car with something happening and it just says a car or period, right?

There's an alt text, an automated scan's not gonna catch that. Or if it's a decorative image, you're not supposed to actually have an alt text at all. So I, you know, a lot of the times when. Where when we have a client and they do an accessibility, a, a true accessibility audit, they'll look at the image and say, Hey, you put 150 words here, really you should limit to 120.

And this isn't really descriptive as to what's happening. This is how you want to do it. I wonder if somebody's taken a site where somebody's u been using AI and evaluated the qu because, you know, it's one thing to be like, yeah, that, that matches it. But is it matching the purpose of the alt text or is it just putting something there there that kind of satisfies its need?

And I'd be curious,

John: you you wanna know, you wanna know like a percentage of sites that use ai alt text like how effective that alt text actually is?

Nic: Yeah. Is it, and is it making them actually more, because one thing we know about AI is it's verbose. Is it helping? You know, and like you said, John, people are lazy.

So if you're no,

John: no, I said I'm lazy.

Nic: Okay. I generalized that because the generalist as well. And the truth is sometimes that's a benefit because you're, you'll be more succinct, right? When you're describing something and Yeah. There, you know, a, a screen reader getting a book on every single image, just driving well, so I don't, it doesn't,

John: it definitely doesn't, or at least in my experience, I should say, I shouldn't, I shouldn't generalize for everybody, but in my experience, it doesn't go like super long.

So the sub prompt that, that, that button is using or the, the, the instructions that it's giving ba based on the also adding the image must, must be, must be saying, Hey, this is gonna be alt text. Keep it short, you know, do, do your thing, right? But, I don't know. Part of me is like, hey, if, if pressing the button provides some sort of a description for an image, some description is better than no description.

Right. I also agree that like, to your point, if, if you're like, Hey, it's a picture of a car, but if it's a car on fire, like, you know, you definitely wanna like add those details in there. Or if it's a blue car or a red car. Right. So like, I don't know, I think, you know, as Martin described and as Drupal is, is moving to like a human in the loop.

Like, yes, we're lazy, but hey, if I can analyze the image and it can pull out the key facts and I can add a few more Yeah. A few more that I think are important. Like, I feel like it's a good, a good solve.

Nic: Yeah. Like, and, and I'm not advocating for not using it. I'm, I'm just more curious about the quantitative aspect of the, of the Yeah.

Accessibility side of it. 'cause at some point. We need to see if this is making this situation better or worse.

John: I feel like that's, that could be a good study of like, Hey, listen, we generated all the alt tags on this site using ai. How many of like, as a percentage, how many of them are actually useful to the people that are using them?

Or if the, if the image doesn't load.

Martin: Well, I will say that I noticed that there was one of the issues that, that was actually in the issue queue for the module was posted by Mike Gifford, who's been on the show talking about accessibility. So he's probably a pretty good person to sort of weigh in on that question of whether the, the suggestions that are being generated are actually good quality or if potentially there are opportunities to improve maybe even the prompt that's being used so that we actually get better suggestions back.

So, you know, if he or any other accessibility experts who listen to the show and have tried out the module want to weigh in in our channel, it would be great to, to discuss, you know, that question specifically around what's, what's sort of the subjective quality of. Those suggestions.

John: And now calling, calling in from hi, from his home.

Mike, Mike Gifford. Let's join. No, I'm kidding. Yeah, it would be great if we had that, that kind of pull, but we don't,

Hayden: I have a question. Are you able to, to kind of train the, train the module to like, for, so I see the accessibility route obviously, but from a marketing side of things, oftentimes images can be used in a lot of different ways for marketing SEO in particular.

So like, would you be able to train, are you able to kind of train this, this this AI to kinda say, Hey, I want a description, but I also want you to tag the title and maybe short description of the actual article within the alt text as well.

Martin: So you can definitely use AI for those purposes. But there's a different module that's actually part of the core AI module that, that can do those kinds of things in terms of like, suggesting let's say the summary or you know, the title, those, those kinds of things as well.

Can you

Hayden: Yeah, but I'm talking about in the alt text though. I'm literally talking like, oh, I see, see what you're saying. To add that in context, editing, editing, like the prompt in the article in the, in the article that it was written by John Zi on blah, blah, blah, because he's lazy type of thing. Right? So could you add that to this alt text?

Because oftentimes alt text is used for SEO purposes for marketers, not just accessibility. It's like, yes, obviously accessibility is a huge deal. No, but if, if I can have my image show up when someone, you know. Up a C then I, yeah. Then I'm gonna put the CV number in the alt text as well.

John: I know a lot of what the, the ai, AI team and the AI module does.

You, you do have the ability to kind of rewrite the prompts that it uses. I don't, I would have to look to see if this module allows for that. I don't know if you know off the top of your head, Martin.

Martin: Yeah, off the top of my head, I'm not sure that you can sort of put in tokens that correspond to other fields. But that's something

John: you could look into because the AI wouldn't necessarily have that information because you're only providing it with the, with the image. Right?

Martin: Yep. Theoretically, there's probably other ways to do it, but yeah, it's an interesting question.

John: I'm looking at the image, a alt ai settings now. Oh. So yeah, you can, you can add.

You can edit the prompt if you would like to, and, and this prompt is I mean, what you, what you would expect. But yeah, I don't see any token replacement where you could add in like a title or, or have it look at other fields. So I think you're probably spot on there.

Nic: Yeah, I'm, I'm sure, I mean, that's probably something to raise with Marcus, and I'm sure they've been, it's been discussed, but they, they probably have to have some sort of dynamic hook system for like respon taking responses and or prompts and modifying them before or after they come back.

And, and if there'd be it's dynamics, you can do it per field or per font type or something, that'd be great. But so who knows if they've integrated that yet?

John: So, Nick, to answer your question, i'm not gonna read the whole thing, but the prompt starts with, you're a helpful accessibility expert that can provide alt text for images, and then it goes on to say you should follow these instructions and take these considerations into account keeping.

The alt text short, inde descriptive under a hundred characters is the first. Is the first one. So

Nic: can you, can you copy that into the show notes? I think that'd be,

John: I absolutely can.

Nic: Awesome. We don't have to do that right now. I'm sorry.

John: I, I was there, so I just did it. Well, Martin this was a very interesting and an energizing module of the week.

If folks wanted to connect with you or suggest a module of the week, how could they go about doing that?

Martin: We are always happy to have lively discussions about candidates or, you know, past modules of the week in the talking Drupal channel of Drupal Slack. Or folks can reach out to me directly as man clue on all of the Drupal and social channels.

John: All right, thanks Martin, and we'll catch you next week. See you then. Alright, Josh, thanks again for joining us. So you are you know, kind of, kind of helping to run, run the show over there at Pantheon. Right? And I imagine that Pantheon is doing a lot with ai because you know everybody, everybody is right now.

But I wanna take a step back and, because you're, you're in kind of a leader leadership role within a company. I, I, I'd just like to understand how are you personally using ai, anything interesting, useful time saving that you're, you're doing that you're like, oh, well I'm using AI to do this.

Josh: That's a great question.

So my use of AI is fairly. Discreet. I use it to juice up presentations quite often. Like, I like the quality of stuff you can do just creatively in real time around like image generation and other stuff. I find that to be super useful mostly for internal purposes. Like if I'm gonna go do something external, we'll like maybe start with a concept that comes from ai but it really helps to like enliven internal communications.

And you know, whether that's come out with something clever and fun or inspirational or aspirational. I find that the utility of the tools there to be pretty good. I also use it for, deep research. So, part of what I spend my time on is is market research and analyzing our industry mm-hmm.

To understand trends and where things are going. And so that's like one, like whenever you're doing research, and, and trying to, you know, pick apart what's happening. The, the right way to do it is to triangulate between multiple points of view. So like, when I'm looking at what's happening with the web, you know, part of what I'm looking at is, you know, what are the, the traditional analysts saying?

That's one, one angle. There's what can data tell us? There's some cool public data sources that I leverage to analyze the web at scale. And, you know, another is like in my network, like what's going on with practitioners, what's going on with people I know that are actually doing the work? But then AI has actually become a nice like fourth angle where you can, leveraging some of the deep research capabilities.

I mean, it's kind of just doing meta analysis across all those things, but it's gonna cover a lot more ground than I'll be able to by reading white papers myself. And then sometimes it can, you know, you'll, you'll see something pop there that didn't. Echo something that you heard elsewhere and it's like, oh yeah, where did that come from?

And you gotta dig into it a little bit more to, to figure it out. That's been interesting.

John: So you, it sounds like you're taking it with a grain of salt. You're not just like, Hey, chat GPT, tell me about this thing. Okay, it told me all this stuff. And like, Hey, this is what I'm gonna now believe and start telling people.

You're kind of like cross-referencing and doing your own fact checking as it were.

Josh: Yeah, that, that, that's right. I, I would say my use of it in that context isn't even so much like cross-referencing, fact checking. Like, I have colleagues who use it, like to help with copywriting. I'm just as a, I'm a writer by, by heart, so I actually don't find AI helpful.

As a writer you know, I like to do my own drafting. I, it's really helpful for other people, but for me, a a kinda like low quality first draft doesn't help me get the finished product done faster. But like I know a lot of people that use it for copywriting and that's where you really have to be careful 'cause stuff can slip in there that you're, you know, you gotta really check to make sure that there isn't some inaccuracy that like that you wouldn't wanna post.

But what I'm using it in a research context, what I'm really trying to do is, again, triangulate with multiple other sources and 'cause you don't really necessarily even know what's true when you're doing market research, you're trying to infer the best guess that you can, so you can make smarter decisions and put yourself in a better position.

John: Do you find that you're providing it those sources, like, Hey, I'm looking at these three things, you know, correlate this aspect of these, of, from these sources.

Josh: So I don't like that specific prompt is not one that I've used where I'm asking it to do correlation. Like the way most of the, the deep researching prompts work is, you know, you're asking it to look across its knowledge base for for things on this topic.

And like, it's, it's much better at, at, you know, providing at the right kind of keywords to, to t tra through and so forth is, I see is, is obviously important. I have, but you know what, it's a worthwhile thing. I should actually maybe give it a try of saying like, Hey, here's, here's. Here's some things that I've found kind of like the idea of like preloading or, or precon building with the model and having it do its own like meta analysis.

I see. So you're,

John: you're, you're, you're going more of the like research assistant path where you're like, Hey, I need help finding information on this, and it goes, here you go, here's like six sources.

Josh: Yeah. That's, that's been my experience is that overall, like the way I've personally. Found AI to be useful is in giving me the equivalent of like an intern.

And so like that could be someone to pull together some like clever clip art or it could be someone to go, you know, read 25 analyst reports and give me a summary. But I'm still gonna take it like, as the, like the work of some, you know, sort of at that level because there's no, there's, there's no domain knowledge.

It's, it's just really Yeah. Like, you know, mashing together all the words.

John: My, my intern is, is writing drafts of blog posts for me because I'm not a, I'm not much of, I'm not, not one that enjoys writing, but hey, you know, different strokes, different folks.

Nic: I I have a friend who's working through a doctor and they said that they're, they're using it kind of a sim, slightly similar way it sounds like, where they'll, they'll say, Hey, I need research on this topic.

Give me a list of all the papers that seem relevant. And then they'll download those papers themselves, the ones that are real. They'll download the papers themselves and then read the abstract and see if it's something that, and then at that point, they're not using ai, they're not asking it to summarize.

They're reading the abstract if it makes sense. They're getting, they're grabbing the full article and reading it themselves and setting and then reading its references, but they're kind of using it almost like, you know, a Wikipedia sources finder or like a librarian to just like find the starting point.

They're not even trying to get it to summarize anything. It's just like, here's a topic. Find all the related articles. I'll read those articles myself. so I, I, I appreciate that perspective actually. 'cause it, you know, hearing, hearing how everybody's using AI is, is, is unique and interesting, finding out where people think it works well, where it doesn't. But from a, from a company perspective, how is Pantheon using ai?

Hayden: I have a follow up question real quick before we go to the company. Like, are y'all more text prompters or are y'all like voice prompters? Because I'm a big voice prompter nowadays.

Like I like to talk to. Oh, really? Like I, I have to talk to chat, chat d bt like, I find that I'll go on for, you know, essays worth of just talking to chat DT and being, and then getting all my thoughts out and then having it execute on it. I'm a big voice. So are y'all texts or are y'all like voice?

John: Wow. I literally never thought about talking to it. Like right until this point. I've always been just like text prompting like, Hey, I need this. Go do this. Like, basically just a, a quick, a quick chat sort of thing.

Josh: I'm, I'm a, I'm a text guy. I find that the, the challenge I have is the, the lag around the voice prompting just mm-hmm.

Takes me out. I, I just find it really frustrating for whatever reason. And and so I just. Just like it's faster, I'll just type it. But I also admittedly don't use AI almost at all on my phone. I think it might be different if I was using the mobile form factor. Oh, so, so there's that. I can definitely, for my own personal use, I'm at, I'm at my desk when I'm doing that kind of work,

Hayden: I can definitely that and just clear, I don't mean like conversation, I don't mean like the AI conversation 'cause those can be fun.

I use those with my, my son sometimes when we're trying to explore a topic. But really I just use the transcript mode. It's just like, hey, transcribe everything that I'm saying to you, you know? 'cause I'm about to just go off and word vomit for a little while. I need you to take this stuff. Uh uh, yeah. I've used that quite a bit personally.

I do have it on my phone. But I do find it to be kind of like. Easiest way, especially if I have a copy paste. It's like I, I talk to it and then I'm like, Hey, I'm gonna copy and paste the transcript now below this. Can you gimme a description like you did for the last two YouTube videos, whatever. And so I, I love the voice.

I'm just, you know, I'm just saying, you know, maybe try it out. It's, it's a nice little,

Josh: Josh, you know, now that you, you mentioned that like, I, I didn't even think of this. This is, this is the kind of what, one of the things I think that's interesting, like, I'm, I'll we'd get into it more later. Like, I'm at Mac really high level.

I'm kind of an AI skeptic. But like, it is also undeniably integrating and infiltrating all aspects of our lives that's both positive and scary. But like, it didn't even occur to me when you said, how are you using AI to point out that I rely on AI transcripts and notes from meetings. I've just, that's now become a standard part of how I operate.

Like the, the Zoom meeting recap has gotten pretty good. And when I'm working with, you know, folks on my team that are talking to customers or talking to partners, you know, and they're doing those like all, we record almost all those calls just, you know, for training and quality assurance purposes as, as they say.

But like being able to have the AI transcript helped me jump to minute 41 where something interesting was said that I'm, that I wanna, you know, be able to double click on or hear the context around versus I'm not gonna listen to the whole hour long call. That has really helped me a lot in my work.

Interesting. And I didn't even think to bring that up as a use of ai.

John: Interesting. It, it's interesting you say that 'cause I. As Hayden was describing, kind of how he, how he talks, talks to the AI or, or transcribes to the ai. I was thinking a couple weeks ago I had this idea for a, a talk and was literally taking voice notes on my phone just in a document.

Like just talking in, in and having it, just write, write it down. But in thinking of it, it would've been a lot, a lot could have been better for, for me to say something like, Hey, write a talk track based on what I'm about to say. And then just kind of speaking out those ideas and, you know, maybe it would've come up with a, a little bit more of a polished a polished thing than what I, what I originally had.

But yeah, definitely some definitely some interesting, interesting use cases.

Nic: So, o other than AI transcriptions of meetings, how, how is Pantheon as a company using AI nowadays?

Josh: So I, it's different in different places. So within the sort of engineering organization, you know, we've got people who use copilot some more than others.

And within the, you know, marketing team, like I said, sort of copy copywriting, you know, sort of initial content generation, drafting that sort of stuff is definitely a use case. There's a couple people who I know have used it for like finance analysis and other things, but that's been kind of more ad hoc.

We don't have a we don't have a structured AI program per se. That's something we've talked about but have not done as a company. I think it's very like domain, sort of practice area function specific. There's how we're working on integrating it into our products, which is a related question.

But like in terms of internal consumption, I'd say the, the heaviest users are probably still in engineering, and then it, it kind of goes down maybe a little bit of a long tail out into the rest of the company. Unless there's anything else, I mean, we do, we do some stuff with we, we've done some stuff that's been somewhat successful with with chatbots.

But but we, that's, you know, that's more assisting. It is a use of ai, but it's a, it's a, it's not a replacement for customer service. It's more of a human in the loop. Let me help you find the right documentation faster. Kind of use case.

Hayden: It's interesting. So you said you don't have an AI program right now at Pantheon. Is there like on the horizon? I, I just feel like, you know, AI's becoming so prevalent. What would a AI policy maybe look like if y'all were to establish one at Pantheon? Like internally, I guess, would it be around like more about enabling experimentation or kind of guarding against the potential risk and data leakage that can come with using AI tools?

Josh: Yeah. No, so that's, that's a good call out. We, we from a risk management standpoint, we do have guidelines and policies on around, around what not to do. In particular, you know, we're big partners with Google, so we're leaning into Gemini and so forth, and we really don't want people to put company information into their personal chat GPT account, for instance.

Like, that's, that's something that we would like to avoid. And so that's in place, but that's a very, I mean, that's, that's kind of just guardrails in terms of really the, the, the thing that I think is the next step for us beyond that. Is just making the space for experimentation? Hmm. I think we, we do internally, we do an annual hackathon, which is a lot of fun.

Everybody gets together and some cool stuff comes out of that. But I'm definitely looking at ways to create more frequent and, you know, not necessarily having to have it be company wide. Like, let's, let's set aside a, a, a day or even just a half day to get together as a team, you know, co-work together on a call and experiment with what we can do with this technology and, and, you know, just see what comes out.

That's, to me, seems a lot more effective than any kind of like, mandate to use ai. I know there's other companies that do that. I have know of some people that work at those companies, and I, from what I hear, it's not, that's not terribly effective to try to force it in there. And, you know, it's, it's a, a, a mix of like.

What can we do from a productivity standpoint? What can we do from a simplification standpoint? That's one that I'm actually very interested in as well with the idea of making room for internal use case r and d. You know, pantheons been around for almost 15 years, and so there's a lot, we have a lot of systems and processes and things like that, that have developed over that time.

And, you know, from when we were a much smaller company to becoming a much larger company. Intuitively, I think there's room for AI to actually help us simplify the way we work with each other in some cases. But, you know, you gotta make time and space to actually test those ideas and, you know, look at all the implications of changing your workflow or your tooling in any kind of serious way.

John: Are you are you seeing, you know, your development teams using, using AI to develop code or, or to do like kind of automated code reviews? In any way?

Josh: Yeah. Yeah, yeah. So the, the, because we're, we're a GitHub shop, so we've been using copilot on that side for a while now. And, but again, that's, that varies from team to team.

Some, some folks are way more into it than others. There's a lot of cases where it appears to go work pretty well. Like, you know, the more boilerplate the task, the more likely it is that you're gonna be able to get some useful work from the ai. Again, kind of imagine it as like the, you know, intern or entry level junior developer that you can say, here's an API spec.

I need to go, go write me some stuff to make, you know, put requests there or whatever. Yeah. And when it comes to code review, again, that's. It's one of those things where, you know, it's kind of like linting plus yep. Which is, which is helpful. But and, and, and I think I think of that more in the again, in the, in the spirit of like.

The overall movement of shift left. Mm-hmm. Right. You, you can get, because it's available on demand, because you can get it to do it in, you know, not instantaneously, but pretty quick, right? You can get a really when you're, you know, you're in your workflow, you can get a very early feedback and if there's some obvious stuff that you've missed, you can correct that before you ask another person to spend time with it.

And so it's less about having, you know, nobody's gonna really no one's gonna say, oh, the, well, the AI said this was safe to deploy, so I'm gonna do it. But what you can do is like, you know, optimize the use of time from your human colleagues who are busy and, and relatively speaking expensive.

Mm-hmm. So that they're not correcting, you know, basic style or syntax stuff.

John: Yeah, it makes sense. And, and it sounds like you guys are kind of following along with the Drupal, the Drupal ethos of keeping a human in the loop, which, you know, I, I personally think is important, but

Nic: well, I, but before we move on, yeah.

I, I'm curious about how, as a company you're trying to solve that overload problem, because I, I see there's, there's two pieces to it. One is, yeah, you can get AI or use tools to do the Len piece, right? The, and there's non-AI tools to do that too, right? P-H-P-C-S, there's HP stand, there's rector's, all that kind of stuff.

But one of the problems in the DR community just at large is dealing with this is volume, right? E even if the developer that's gen using AI to assist their development does a first pass, the number of changes on average, and the number, the amount of churn on average is much, much higher when you're using ai.

So how do, do you guys have systems in place? Or have you thought about how to prevent review blindness or, I don't know, the term review fatigue or, right. It's one thing to review a change set that's a hundred lines, 400 lines, 500 lines, when every change now is 800 lines. Plus it's very, very easy to miss something.

And if the last five times it worked, you start to trust ai. But one of the, one of the sneaky things about AI is the next time isn't more trustworthy. Like a developer generally gets more trustworthy as they gain an experience. AI may be, perversion gets better, but for a given version, each iteration isn't necessarily just as trustworthy as the iteration before, depending on what you're asking it.

So how are you, is that something that you're thinking about? Is that something that you've seen as a problem?

Josh: Yeah, I think the, to me, there's. The, you're, you're certainly right that you know, one of the things to always keep in mind with these tools is that they're not deterministic. They're probabilistic, which means that Yeah, you know, you, you and, and they're not gonna get smarter about the thing that you're doing just 'cause they're, you're putting more code review through it.

Your point about like, you kind of learn to trust it and it becomes a crutch or a fallback, that's certainly a, a, a thing to be concerned with. I don't think we've seen exactly that problem of volume. And that may be just because of how the, the, the teams are applying it. I think we're still trying to.

Keep our, the changes we make to our core product set, fairly discreet and and targeted. We're not, that also might just be a factor of the, the kind of work that we've been doing and, and where this is you know, been used more. So like we are just getting through, releasing a complete replacement for the, the user interface to pantheon like what you log into when you use our product.

Yeah. And that's like a, been a long project. That was mostly, I would say like a good amount of the work that was done on that was before there was really even the option to rely on AI as much as people do now. Yeah. And so, so it wasn't like a, and, and because it's a complete system swap out, it's not like we're, we're we're looking at a bunch of like, kind of like gnarly change requests against the legacy code base for that.

It's pretty much we're building up this new thing to be greenfield that might come more into play as we get to you know, the next tool. But like, I don't think, you know, like I don't, we're we're, I would say Pantheon is, and, and this is maybe not to our credit, but we're like relatively light on like vibe coating style development and it's a lot more of, you know, like, knock out this boilerplate for me.

Help me. Yeah. You know, think through this problem and stuff like that, so we're not ending up with like a lot larger, like the number lines of code are not going up in as a, as a as.

John: I feel like many, many listeners are probably happy to hear that you guys aren't doing a bunch of vibe coding over there. Well,

Josh: you know, the thing is with that the one place where we, we, we have been doing more of that, and again, it's in kind of these like hack hackathon Yeah. Kind of context as we're like looking at new product development and trying to imagine things that are different than what we do today.

I will say like the ability to put together rough working prototypes of alternative functionality. Mm-hmm. And just to be able to get people to think and reason about what might be possible is a huge advance. Yeah. But then you look under the hood and you're like, great, so this is demonstrating the art of the possible, but this is not code that you'd even wanna start.

Like, I don't even wanna try to fix this code to ship it. I wanna, you know, start over and think about how to do this. Right.

Nic: Yeah. That, that's a good, that's a good point. 'cause the truth is point of con point the truth is. Proof of concepts very often become production in history that like the number of times I built something that was a proof of concept, and then you, and you get some technical debt from that.

But when it's built by somebody, especially an experienced developer, sometimes they put those guardrails in place so it can become something that's maintainable in the future. And I think you hit the nail on the head. The thing is, AI opens up the ability to create those poof of concepts much easier and to people who technically aren't as technically skilled developers or architects, which I think is a good thing.

But the problem is that concept truly is something that has to be thrown away once you've seen what it, it can, at least as of now, it cannot become something that's maintainable, especially if you're using AI to provide additional changes to it. And, and if they bridge that gap, then, you know, then architects are in trouble.

But. There's no, there's no sign of that happening anytime soon. But I feel, who knows? I feel, I feel okay about it.

Josh: Yeah, I mean, you could just track the rise of the job description vibe, coding, cleanup specialist on your favorite talent marketplace, and understand that there's a, you know, there's a limit to what the, the, the tools can do today.

And, you know. You know, it all depends on your risk tolerance. Like, I think there, you know, you can proof of concept for internal use, proof of concepts to validate market. Like when we were first starting Pantheon, we, we put together what we knew was a very limited and would not scale version of the products that we wanted to sell just to prove that people would buy it.

Mm-hmm. We got our first 150 customers on an, an infrastructure that we knew we were gonna have to sunset and burn down if we decided to do it, quote unquote, for real, then like. In a different world. Like, and, and, and you know, again, candidly, that took us like months of effort and then many, many more months of like maintenance and creation on what was like, you know, going nowhere.

For us as a business, if I was doing it all over again today, I would vibe code that part of it for sure. And then and save, save, get to market six months faster.

Nic: Yeah. I mean, I, I shudder to think what that would look like under the hood.

John: But I mean, like, the point is, the point is the same, right? Like, it, that's how, that's how companies, companies work and, and Thrive is like, Hey, we do an MVP, right?

Like, or we do a V one, right? Hey, V one is out there, people are, people are loving it. All right? Well, V two's gonna be gonna be a rebuild or v you know, MVP, we're gonna build on MVP to make it actually the platform that we want.

Nic: Well, yeah, the, the, the insidious pieces though that people, this is a general statement about companies.

Nobody, nobody here in particular, but they underestimate what that maintenance is. And I, I, I worry that the willingness to put the effort for rebuild is going down as people, as the people making the decisions. Think AI's capabilities scale up. Right. You know it. Sure. You know, if, if you, if you went to MVP using just an AI product, are you gonna wanna put, you know, developers on it to rebuild it from scratch?

Or you're gonna want them to build it using AI version two, using AI as well, because it's faster. Yeah,

John: I, I mean. I think that's where technical consulting and CTOs and CIOs are gonna come into play to say like, Hey, this is great for a V one MVP, internal proof of concept, but like, here are the reasons we can't take this to market right now.

It's insecure, it has performance issues, blah, blah, blah, whatever. Right? They're gonna like, and, and those people are going to use developers to, to, to make those points, right? So like, I don't know. I don't, I don't think, you know, I, I, I tend to agree with you, anybody that's vibe coding their final product and, and, and forcing it on people is probably not, not long for, for the wor the business world.

But, you know, I've, I've been proved wrong before. Well, I think it all, it also all depends on

Josh: context, right? I think, again, you can do something purely as a proof of concept to learn what's possible and, and understand and reason about a problem. Then you can also take a proof of concept product to market just as long as you're, you know, you're aware of the limitations and you don't deceive anyone.

Because there's like, you know, again, I'll just say from our, from our own history, right? Like when we first got to market, we didn't have security certifications 'cause we couldn't have earned the cert security certifications, right? If you tried and, you know, it's a, it's a long. Process to develop something that is, you know, scalable and enterprise grade and, you know, can can really become used by tens of thousands of people.

And as a, as a, as a startup guy, I feel like it's like my obligation to remind people that you have to start with one. You have to get one user. And if you are trying to build for 10,000 users, you may never get that thing to market. Mm-hmm. Or you, you'll

Nic: burn your, you'll burn your startup cash before you even get.

Anywhere remotely close to,

John: to profitable. Used to have a client that used to say, perfect is the enemy of good enough. Like that's kind of, that's kind of the mindset, right?

Josh: Yep. Yep. And I, I mean, and you know, Nick, you're not wrong though, that like, there's just the risk in, in the risk overall in the market.

Is that the expectation, I feel like expectations are, are like starting to like veer more towards reality though now. Like the, hopefully yeah. The, the, the, the trajectory of the hype cycle is definitely changing, and I don't think, I think people are becoming a lot more grounded in what these tools can deliver today and what, what it's good to rely, what, what, what makes sense to rely on them for versus, you know, what make, you know, yeah. Yeah, certainly mistakes are still made in the market, but the, you know, mistakes are always getting made. Sure.

John: So let's, let's, let's let's dig into that one a little bit, right. How are, how are you, you guys, pantheon advising your clients to use AI right now?

Josh: That's a great question. We.

Don't have a strong advice for our clients around the use of AI today. That's why we're making the investments that we are in, like the Drupal AI initiative and some similar stuff on the WordPress side. And, you know, we're also like part starting to move into the world of next gen, front end development with next JS and stuff.

We want to be able to give people at least like a well-lit path towards common use cases. And so this is not something, again, I'm just gonna be really honest. That's not something we do a lot of today. We can, the best thing we can do is kind of share, socialize within our customer base. Here's what other people are doing that seems to be working well.

So like, you know, we were able to socialize the, the, the case study at DrupalCon a couple years back with Yale building the Vertex database of content from across their entire portfolio to create a really useful on campus assistant. Um mm-hmm. You know, but that, that was something, they weren't doing that with Pantheon, that was a whole project of them in and of themselves, but it's still an amazing story.

Like they were feeding it all the content from their CMSs and other sources. But that was, that was really about them and their team and what they were able to put together. So that was a cool one to be able to talk about. We're working on some things to help around like slightly less grand scale use cases.

'Cause not everybody has the resources of an Ivy League University. So like, there's a lot and I think like there's stuff we can do obviously with the Drupal AI initiative from a content editor, content administrator, Drupal administrator perspective. And we're also looking at where we can help to enhance the end user experience.

We've got a project going around search which is, which is I think a, a kind of a, a one of the more obvious, but as, as of yet still untapped opportunities because, you know, we were talking about this, you know, prompting before and when you were talking about like that AI alt text model. One of the things that these tools are remarkably good at is being able to like.

Tease out intent from a, a text input string from a human you know, they're not perfect at it, but like, much better than like keyword matching, right? And so, you know, so we've gotten, we've done some proof of concept work where like someone comes to you know, like someone comes to a customer website of ours.

Like, we run a lot of visit City X type projects. That's a, that's a great use case. But they might come there and type into the search bar how to host a conference in your city. And they website, the CMS, you know, with its wonderful you know, search index that we all know and love, like Apache Solar might or might not come up with articles that exactly match those keywords.

And. If you were to instead, or rather augment that with some in intent parsing and you had a vector database that you would leverage for retrieval augmented generation, and you had the entire content base of the site available, you know, you can get a, like, kind of like your site's equivalent of the Google AI overview that might be able to do things like here's who you would have to call in order to start this conversation.

Here are three events that happened in the past that you could look at for inspiration. Here's a list of venues that we have on our website that might be good for hosting conferences, like come up with a a, a, a composite result that actually meets their intent much more powerfully than like the two or three articles that, that have direct keyword matches on their query.

John: Yeah, it's interesting. It's interesting you bring that up. 'cause at GovCon last month somebody was talking about that, that very similar thing with you know, using a rag and, and the chat bot to basically provide folks answers from, from file sources, right. And say like, oh, hey, you need to do this.

You can find this file here. Right. So I I I tend to agree with you on the, on the, you know, search, chat functionality becoming more of a prevalent use case for, for ai.

Josh: Definitely. Well, and it, one of the things that, this is kind of funny. One of the other things that we've seen though, as we started to play around with this is you, you know, the, the garbage in, garbage out problem is still very real, right?

So if you have a, a, a database of content and say like. Some percentage of it, 20%, 10%, 25%, whatever, is stuff that was written for SEO. Meaning that it's probably like actually lower quality content not necessarily full of insight and information, but you know, hits on all the keywords that you need to try to rank for whatever query is, is topical.

Yeah. Like the, the the AI will, will, like slurp that up and regurgitate it in these summaries and end up with like lower quality summaries. It's like, this was like my our, our guy at at Yale, Franz Hartle had this really great analogy around how you have to think about content in this new era, which is you're feeding these systems and you need to feed them.

Nutritious meals, otherwise their, their ability to give you strong results back is just gonna be compromised.

Nic: Yeah. The, it, it, it's one of the perennial battles that I have in general. It's always like a client will say, if I search this key phrase, I expect this page to show up. And it's like, okay, then, then why don't you modify the page that you expect to show up to have some of the content on the search phrase that you're searching?

And I, I think it, it's interesting that you mention that. It's like you're feeding it that way. 'cause I have found with RAG and with AI search and that kind of stuff, clients are kind of like just automatically thinking about their content from the content side rather than from the search entry side, which is, which is a welcome shift because, you know, I'm not Google, I don't have the resources to do individual, individual individualized, full, you know.

Rankings. So, that, that, that's, I'll have to dig in more to that. You, you mentioned you just mentioned the Dr. AI initiative and, and how it relates to search. What, what exactly is Pantheon committed to for the Dr. AI initiative?

Josh: So we're working to to help support the development of AI in Drupal.

And I'm having a, an interesting conversation with do Dominic and Kristen and others around the way the Drupal AI initiative was structured. That the, the, the way they built the program is actually hard for us to participate in as, as written for, you know, a bunch of reasons. And I understand they need to do things in a standardized way and they've got a big coalition of folks and, and that's fine.

So we're not as of today, officially part of the Drupal AI initiative, but we are sponsoring the development of the tools API, which is kind of a necessary, in our opinion, low level resource in Drupal to support any kind of agentic process or mv MCP interface. Right? We, unless there's a way to have actions that an agent would take with Drupal that are like cleanly defined and can describe themselves to the agent, and that, you know, have good Drupal practices and work the way we want them to work, like building blocks, it's gonna be very hard to make agentic workflows reliable.

Or, or scalable. So that's a key piece that we're, we're trying to help develop and drive. And we'll be talking about this at DrupalCon, Vienna got some cool demos coming out. Michael Lander is doing a bunch of that work with us right now. And then the other thing that we're doing is we are ensuring that the Google AI tool suite is a first class citizen in the kind of, you know, plug your model in here.

Part of Drupal you know, Gemini is quietly, you know, at the top of the leaderboards for both code generation and content generation use cases, which is interesting 'cause there's not one model because that is, any other single model that ranks that highly in both use cases, and Google's got a lot of horsepower to put behind this stuff.

They're not doing it in a as a loss leader, right? They're, they're not, Google's not losing money right now, whereas like a lot of the other big shops are. Their financial future is in doubt. And so I think it's really, and, and also just self interestingly, like we're deep partners with Google Cloud platform.

That's our underlying infrastructure provider of choice. We have good relationships with them and we have ways to put bundles together for customers. Like if you wanna use Pantheon and Gemini, we can make that happen for you you know, with a a package deal which is, which is neat. But, but that only matters if Gemini is a, you know, first rate, a plus provider for all of the, the Drupal AI workloads.

So we're helping to sponsor some of that development both in terms of just having the general provider module be really good, and also trying to push it all the way through with a few, few example use cases. And like the search is one, I'm like, we're hoping to be able to release a, a module that lets you kind of turn on.

AI enhanced search pretty quickly, and that's a great way to demonstrate what could be possible on your website if you were using, you know, Gemini and a Vertex database in addition to the core sort of Drupal stack.

Nic: Okay.

Josh: So, yeah, really excited about all that stuff. I think ai, this is one of the places where Drupal can differentiate in the market. Like, one of the things that has been interesting for me in my career is being able to have a foot in a couple other open source web communities, right? WordPress is moving along the same lines, but I would say they're, where Drupal was nine months to a year ago in terms of getting the core teams and architecture in place to put building blocks there so that others can build on top of it.

Like, but they're moving in that direction. It's, it's fairly clear that that's what you would wanna do if you wanna have an assistant or something like that. Yeah. The power, your CMS,

Nic: I mean, I, I think the real problem that WordPress will run into with this is, which is the problem that they always have, is they don't have a consistent API for most things, right?

There's no field API, there's no, you know, there's a CF, there's other tools, there's elements, or there's like 15 different tools that you have to integrate with. They also don't have config management, so there's no way to like have it really provide. Site-wide changes or things either, but yeah, I, I've, I've seen movement there as well.

Josh: Yeah. I mean, like, they're, they're in the same place where like we needed to find an actions framework, which is like tools API, kinda the same thing. And then it's like, how will this surface in plugins? And it's interesting, right? Like, the, and, and like the, the, you mentioned Elementor. I know the folks there pretty well.

Like, they actually just went ahead and did it all themselves. Like they have a, a pretty cool working assistant prototype called Angie that's just been trained on Elementor and all of its usage and so forth. And it has all the limitations that you would expect, but like, it's, it's showing some, some, some real promise.

And I think it just kind of like suits the different, like what they're, what they're naturally building towards is like something that can serve the long tail. It's like we wanna help people who are trying to set up the portfolio site for their wedding photography side hustle. Get that done. Yeah. Quickly and easily, and without having to like phone a friend 10 times to, to figure something out.

Like that's a, that's maybe an achievable goal, right? With this side of stuff. Whereas on the Drupal side, I think we're like, we wanna accelerate the implementation of an ambitious project, and then we want to export all the config changes that came from this work. Review them with a human in the loop and figure out if it, if it's safe to deploy, and if so, do so in an orderly fashion.

Yeah, those are really just, just very different ways of thinking about how you leverage the tools.

Nic: Yep.

Hayden: Josh is the Google thing's really cool. I love Gemini personally. Also, I, I use it honestly probably more. And VO three, if y'all haven't played around with VO three and the, the video creation tool, it's incredible.

But are, are there like more specifics like this partnership, is it a, you know, lowercase p uppercase p type of thing? Like how, how deeply ingrained are y'all over there and what does that look like? And y'all doing anything outside of. Drupal with that.

Josh: Yeah, so the it's a, it's a capital P partnership like we bundle you know, we, and we work with Google in our go to market quite a lot.

So one of the more mundane aspects of that is that Google runs a cloud marketplace. You can purchase Pantheon through the cloud marketplace. It's not like a swipe your credit card cloud marketplace. It's very enterprisey cloud marketplace. But the way that that works is when you know, you essentially buy Pantheon through Google, and then when people are interested in doing that, we're able to say, and hey, let's bundle in.

$10,000 worth of Gemini credits as part of that purchase so that you can start your Dr your, your Drupal AI journey without having to worry about the cost of the, the, the model for, you know, the first year or whatever. And you know, Gemini is actually pretty cost effective. So like, you know, we've been doing some benchmarking as part of some of the work that we're doing, and again, hoping to share some of this information in our session in Vienna.

But like, like here's a, here's a sim simple use case that Drupal AI supports today. What does it cost to run it on like, you know, anthropic versus GPT versus Gemini? I don't actually know if we're gonna be able to, to really do an apples to apples yet, but that's like a goal that I have and I think Gemini's gonna show up pretty well.

But there's lots of other things you need, like that might come from Google to make this work. Like the Vertex database for instance. Not something Pantheon offers natively today, but like Google has really good services for that. Whether you want to use like. Alloy Cloud DB and just put it into Vertex mode.

Or you want to use our dedicated vertex endpoints 'cause you wanna get deeper into it, like same deal. We can kind of bundle that through with like your Pantheon package. So you're getting Pantheon plus whatever else you need from GCP to make the AI use case work. Work really well.

Nic: Interesting.

John: Just outta curiosity, are you, are you guys building a new AI Gemini module or are you working with something existing?

Josh: Yeah. No, we're, we're, we're sponsoring and supporting the work that EDIA is doing days like led the charge on that and we're working with them also around like kind of the, the last mile of what it would take to make that work for a search use case.

Mm-hmm. That is like one of the example implementations. Like I, I'm a big believer 'cause I think in the Drupal ecosystem we often fall victim to the developers fallacy of we made it possible, so now it is done. Versus like, working with these capabilities, I really wanna with the work that we're doing in, in terms of sponsorship and so forth, really make sure we pull it all the way through to, here's an end-to-end example of it working in a way that will.

Light up the eyes of a regular user. And so the one of the ways we're looking to do that is with this search use case. Interesting,

John: because I was I, I I use chat EPT just 'cause that's, that's what I, I use, but might be interested in maybe making a switch over to Gemini now. So that's that's good to know.

Josh: Yeah. I mean, I, again, I, I would, I, I find it useful. It's like our, also like our enterprise corporate approved tool. So if I'm doing stuff for work, it's definitely in there. But I don't have a basis of comparison. I have a lot, so many friends that like really love GPT. I imagine that it's great for some things.

I also imagine like if you have built up a lot of context with a particular chat interface, like that's hard to replace. Yeah. But if you're just looking to go and mess around and try some new things, Gemini has definitely got a lot to offer for it. And, and the, the, some of the creative tools that are bundled on top of it or as part of the suite definitely are really the video stuff is.

Is fun to mess around with. Yeah. Like it's not gonna, again, we're not replacing real cinematography or video or, or directors anytime soon because getting continuity between one clip to another is almost impossible. Yeah. But like, it is really, if you wanna just come up with some goofy videos, it's a great way to do that.

Nic: I, I, I will say I got a pretty deep dive into Gemini about three weeks ago. 'cause a friend of mine that does a lot of work, both using AI as a tool and developing AI solutions, you know, as a, as a develop, as an AI developer has said that Gemini's code generation is kind of the best in the market at the moment.

Specifically he said if you're using their interface directly, not if you're using it integrated with something like the S code. He's, he's like, I don't know why it's different, but it's different and it's garbage and vs code and it's great if you use the interface. And I'll say that in general it was better than average.

I found it very difficult to enable a way that maintained privacy. Right? Because, you know, it's a double-edged sword. Google. Google is part of my life. I can't get away from it. But I also didn't wanna just turn on Google AI systems for my personal account. Mm-hmm. Right? Or my business account, right. I, 'cause if it's my business account, I'd have to talk to every single client and see if it's acceptable that anything that they share with me is now available to Gemini, whether it's directly or a possibility.

So I ended up creating a, a separate Google account just for testing out Gemini. So there's no like, client information or personal information or anything. But I, I found it was. I expected in their context window, I think at the moment was a hundred thousand tokens. So it was big enough to get some medium sized projects in there and kind of kind of work with it.

But,

so in the end, not still not using it kind of to, to, I

John: mean, you've gotten far farther than I have Nick, which is, which is impressive. I, I got the like alert that like, Hey, Gemini's available. And I was like, yeah, yeah, yeah, whatever. Like, not now, go away and like, haven't gone back to like actually click the buttons and, and check it out.

So, Josh, recently I was listening to a podcast, another podcast, non Drupal podcast, and, they were saying something around you know, AI use amongst younger folks and kind of average consumers has decreased. But it's still really hot with business. And I was wondering if you think the AI boom for kind of the average user has fizzled.

Josh: You know, so there's there's many potentially contradictory data points you could, you could use to try to assess that. Something that pops out of certainly open eyes usage data is their stuff falls off a lot over the summer, which suggests that there's a strong school year. Component to their utilization.

And, you know, that could be a lot of things. But you know, the, the fact that it is something that you know, I know a couple people that are teachers and it's just a fact of life that you have to and I think what happened was there was a, there was a kind of a window when nobody knew it was going on, and then like, responses are very hand fisted.

And now I think teachers and students are like becoming a little bit more mature in how they use AI in the context of the classroom and homework. And and I think that might be, could be a depressing overall usage numbers a little bit. Because like you, you, like, you're gonna get caught if you try to treat it as a homework machine.

Mm-hmm. I don't know. I don't know though. Like, I think to me, I feel like the, the real challenge for the industry is just actually one of sort of fundamental economics. It's hard to see, like the, there's, there's a, there's a, the, the, the cost to deliver the service exceeding the cost that you can charge for the service for many of these providers is, is evident and it's, I don't know I don't, I don't if that isn't something that they can find a way to resolve through, you know, future iterations in models, which will need to be less about making the models more powerful, but more about making them more efficient.

Like there's clearly opt room to optimize for efficiency in all these systems. And so I don't wanna say that it's, it's a fundamentally broken model, but it does, it, you know, it's more than just an engineering challenge. Like when you've built a business around a loss leader at a certain point, if you can't access more capital to under subsidize that loss leader, you end up doing, having to make tough decisions on a business basis, which could, you know, drag drastically reduce your user base.

Like kind of cursor went through a version of that this year for sure, where they tried to like right size or institute rate limits, that gave them a path towards more business viability. And everyone got really upset because it's like, this tool's no longer useful. I, or it's timing out too much, or I've hit my rate limit for the week.

What am I supposed to do now? So I think that's like, that's the big challenge. And like, you know, Google has the scale and and, and you know, doesn't have the risk of needing to like radically revise their business model. The, the other big, you know, Microsoft, who knows what Microsoft's relationship with open AI will turn out to be, but Microsoft and Amazon doesn't have like a, an in-house ai, but they could acquire one, right?

Yeah. So the hyperscalers, the big public clouds can offer this stuff on an ongoing basis. But the companies that are kind of more popularizing it as a use case, I think they have an uncertain future. To me, that's a much bigger question than can you get utilization to go up or down?

Nic: I, I think to your point too about the scale is that the problem isn't even just that they're using like a lost leader on the lower end, right? It's not like, okay, chat GPT by default, I think is what, 20 bucks a month? And yeah, some users go over and, you know, they can try to get them to bump up or something.

But I saw a report recently that, I don't know if you know this, but there's a $200 a month plan for chat GPT, and if you pay 200 bucks a month, you can still go over. That and cost. If you're, if you're a heavy user, you can use more than $200 worth of services. And that just, that's just untenable. Like if you're paying that much for a service and they're costing more like it, that, that's not loss leader territory anymore.

That's just, like you said, the fundamental economics of that product just don't work. And it, it doesn't because of the way that it's working right now. It's not metered. They really, that's what it needs to become. It needs to become metered, right. Where you just pay for tokens and when you get towards the end of it, you top up and you kind of self, from an economic standpoint hidden.

Not, not from, I hate that consumer standpoint. I hate, hate that, Nick. Yeah. Not from, I'm, I'm not saying from a consumer standpoint, but, and, but my point is that if the company underlying companies don't move to that, they're not sustainable long term and they're just propped up with VC money and. Can you as a person or a business rely on that long term?

You know, they might get acquired by one of the big, you know, like Amazon, like you mentioned. Maybe they'll acquire a cursor or something and they'll find a way to build that into their bigger workflows. But it's an economics problem. You can't charge less than your product costs. I mean, that's why Lego almost went outta business in the two thousands.

They didn't know how much their sets were costing. They sell, they'd sell 'em for 200 bucks and it cost them a thousand.

Hayden: Yeah. When the $200, when the $200 one first came out and they came out with the, I think the deep analysis for the first time, I think it was like 25 cents for every single time you use deep analysis.

Like, and so if you did over 800 prompts in a month, you spent more than what you paid in their costs, which was just a wild amount. I am on the $200 a month. We do a lot of ai, like, I mean, we pump out content all the time and we're always using it for first drafts and stuff. So, yeah, usage based pricing is like what Uber used to be, right?

It's like you could get an Uber across town for like $4 and they were always just trying to addict you to the convenience. And now Uber costs a hundred dollars to get across town, and you're like, Ugh. So no, no usage prices.

Nic: Nick, come on,

Hayden: man.

Nic: Yeah, like I said, from, from a consumer standpoint, it's terrible, but I would argue that most AI as it currently stands, is terrible for consumers anyway.

We, we kind of need a whole, as a society, we need to kind of figure out how to frame AI so that it consumers are protected. But that's a different podcast.

So speaking of the future, even though AI has been out now for a couple of, AI in its current form has been out for a couple years now. How do you think Pantheon is going to continue to evaluate ai? As a kind of a general tool and integrate it with its product services and workflows.

Josh: So there's a couple different ways.

I mean, we have a kind of a philosophy that has taken hold in the company. Right. I'd say this is a change from where we started, which is, which is I'm proud of where we're trying to be really intentional about where we provide a, our product versus where we help people use tools that they already like and have adopted to accomplish the goals that we share.

So, for instance a really straightforward way of thinking about this from a developer standpoint is that we are gradually and inextricably moving towards a world where we're external version control service first, right? Where it's, it's like Pantheon becomes a GitHub first platform. You know, we have a lot of in-house.

Version control operations will have to maintain for a long time. But like the, the nobody, people wanna use GitHub, they don't wanna use push code to us. So like, let's embrace that. We're doing that with that's the whole spirit behind this new content publisher product, which is, you know, the real honest truth is content.

People don't sit down and crack open their CMS to create content. They work elsewhere and tools that they like better for creation. And then they copy and paste. Could we find a world where they can use the tools that they like for creation? And it just integrates into a seamless workflow. And I think that's also how we're thinking about ai, which is where are there existing things happening with AI that we just need to make a part of our orchestration and integration job?

Versus where are there places that we can tastefully. Insert AI into the, the part of the work that we're helping people manage directly so that they can get more done. And so some of that is in the, in the developer tooling world, like I was talking about before. It's just making this stuff available, honestly.

It's like, Hey, you wanna do AI projects on the web with Pantheon? We're the best place to do that. Assuming you want Google as a partner. If you don't want Google as a partner, you can still do it with us. Obviously everything integrates, but we are the best place to do it with Google. And then you think about some of the other things that we can do.

You know, we're definitely interested in the, the use of AI to, make the robots do the boring work. So like there's some stuff we've done proofs of concepts around like content audit and content migration and other things like that. That's a place where I don't think it's gonna become fully automated, but we can get the work down.

Because you were, we were talking about alt text before, like using AI to do. Meta analysis of your own stuff is, again, not, not something that you would take as a, as fully trustworthy, but it's an interesting way to say, Hey, like, look at these 10,000 alt texts that were generated. And, you know, compare them to these that were written by accessibility experts and tell us, you know, how well do they match up.

Are, what are the. What are common differences? Like those are, you can kind of, you know, build meta tools that help you use AI to assess all the information. And one of the things that we have that we can bring to bear is a lot of information about what's going on with people's web projects and websites.

So using this to help understand traffic patterns using it to help understand workflow patterns within the team. Especially for larger organizations where they're not, you know, again, they, they've got a portfolio of sites they've got maybe more than one team at play, or there's a central team and some edge teams and an agency, right?

Like being able to have an overview of everything that's happening and have AI assist with that is feels like a very real use case and a place where we could authentically add some unique value. Awesome.

John: Well, Josh we appreciate your insights and thanks for joining us today. Hey, thanks for having me.

It's a pleasure. I hope you guys have a great rest of your day. If you have questions or feedback, reach out to talking Drupal on the socials with the handle Talking Drupal or by email with [email protected]. You can connect with our hosts and other listeners on Drupal Slack in the Talking Drupal channel.

Nic: If you wanna be a guest on Talking Drupal or our new show TD Cafe, click the guest request button in the [email protected].

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Sign up for the [email protected] slash new.

John: And thank you patrons for supporting Talking Drupal. Your support is greatly appreciated. You can learn more about becoming a [email protected] and choosing to become a Patron button in the sidebar. Josh, if folks wanted to get ahold of you, learn more about Pantheon, learn more about ai, learn more about all the things we talked about, how could they best do that?

Josh: So, you know, pantheons pretty easy to find pantheon.io. But if you want to kind of reach out, I am in the Drupal community Slack. You can, you can ping me there with the dm. Also join our community Slack instance, if you like that or you know, hit me up on the socials. I'm on LinkedIn, I'm on x.com, the everything app.

So I'm, I'm always happy to chat with people in any of those places.

John: Great. Hayden, what about you?

Hayden: Hit me up on LinkedIn, y'all. I'm on I'm on the Drupal Slack, but hit me up on LinkedIn. DM me. I'll get back to you if you, if you actually reach out. If you pitch me though, I'm gonna pitch you right back.

John: Ooh, challenge accepted. Nick, what about you?

Nic: You can find me pretty much everywhere at Nicks van, N-I-C-X-V-A-N,

John: and I'm John Picozzi. You can find me personally at Picozzi.com or on the social media and drupal.org at John Picozzi And if you wanna know more about EPAM, you can check us out at EPAM.com

Nic: And if you've enjoyed listening, we've enjoyed talking.

See you guys next week.

John: Thanks a lot everyone.