In the Loupe
In the Loupe
Everything You Need to Know About the NEW ChatGPT-5
GPT-5 has arrived with meaningful improvements in logical reasoning, processing speed, and the ability to dynamically switch between models based on task complexity! The technology excels at pattern recognition in data analysis while software developers are finding new ways to integrate it into their workflow without sacrificing quality.
Mike sits down with Punchmark Back-End Developer, Andy Szoke, to discuss what the arrival of this new version means, how to balance your humanity with productivity, and the basics of prompt generation.
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Welcome to In the Loop. Two years since the last model release and this one is, of course, a huge step up and, I must admit, I don't even fully understand it. So I brought on my friend and also my coworker, andy Zoki, who is a backend developer for Punchmark. He's also one of the most plugged in guys with regards to, you know, chatgpt and the development of AI, and he stays on top of this stuff and uses it in ways that I couldn't even imagine and I asked him. We had a real nice conversation discussing what the new changes mean, what it's capable of, the ways that we use it in our own life, and I think it's just a more casual conversation, because Andy's one of my best friends and he's also my co-worker and hearing how he uses it maybe informs me on how I can use it better. If you're not comfortable with using AI, no problem. This might not be the episode for you, but if you are kind of dabbling, this, one kind of gets into some deeper weeds and maybe you enjoy that.
Speaker 2:So everybody enjoy and maybe you enjoy that. So everybody enjoy. This episode is brought to you by Punchmark, the jewelry industry's favorite website platform and digital growth agency. Our mission reaches way beyond technology. With decades of experience and long-lasting industry relationships, punchmark enables jewelry businesses to flourish in any marketplace. We consider our clients our friends, as many of them have been friends way before becoming clients. Punchmark's own success comes from the fact that we have a much deeper need and obligation to help our friends succeed. Whether you're looking for better e-commerce performance, business growth or campaigns that drive traffic and sales, punchmark's website and marketing services were made just for you. It's never too late to transform your business and stitch together your digital and physical worlds in a way that achieves tremendous growth and results. Schedule a guided demo today at punchmarkcom. Slash go.
Speaker 1:And now back to the show. What is up everybody? I'm joined by Andy Zoki, my good buddy and also back-end developer at Punchmark. How are you doing today, andy? I'm doing pretty good. What's up, mike? Doing so well. Really cool getting a chance to have you on. You were on when we were talking about VR and you've always been very tech forward when it comes to, you know, I guess, adopting new technologies and kind of. You follow the state of AI very well. But, big news, it actually happened yesterday when we were recording this. But when this releases it'll have been a few days, but GPT-5 just released. Can you give like a pseudo overview on what GPT-5 is for people listening?
Speaker 3:Sure, yeah. So GPT-5 is OpenAI's latest iteration of their chat, gpt, llm, large language model and it's you know. You've heard of AI, you've heard of all these things that it can do. Gpt-5 is the latest iteration, looking at the initial rollout, and this is bleeding edge. I literally just got access to it this morning, so I haven't had too much of a chance to play around with it, and that's going to be coming over the next couple of weeks, but it looks like it's moderately better at coding tasks. It's slightly better logical reasoning Maybe not as much of an exponential rise as some people might have been hoping for.
Speaker 3:One thing that we've seen with the most recent releases is it's just taking a lot more time and money than people were hoping for. So it's one barrier that they're actively working on, obviously, but, yeah, it's just a little bit of a better thinker. One thing that people are saying off the bat that they aren't necessarily fans of is the personality is a bit drier and, uh, it could be more curt. Um, I've heard, uh I saw one person on reddit describe it as a overworked secretary. That's just kind of exasperated. Talking to you, it's maybe not that bad, but it definitely has a little bit more of attention to that than uh its predecessors, uh gpt 4.5 and 03 yeah, because so there was.
Speaker 1:There's different gpts, uh, that are tailored to different types of tasks, like there's 03, and then there's 03, mini, and then there's, uh, there's four. Um, I have to be honest, because we were talking about this probably about a month ago and you're like, oh yeah, you're, you're using four, you're not even using the advanced version that you're paying for. I was like, oh, I didn't realize you had to do that. Apparently, with gpt5, it will dynamically switch between the models, uh, depending on what your task requires. So if you need a deep thinking one, it can do that, and if you need a you know, just a quick answer, then it'll do that as well. Do you switch between models, or were you switching between the models when you're using it?
Speaker 3:Yeah, I've always been a big fan of O3. I think that's just been the most capable model for most complex tasks. I use it as a developer. I know lots of developers use ChatGPT. You've probably heard vibe coding, you know it can be an insult. On the far end it's just telling ChatGPT to write everything and then you just copy and paste it into your code base and you ship a million bugs and, you know, make a lot of people unhappy. We would never do that, of course not. No, and we don't.
Speaker 3:Obviously, the correct way to use it is almost as if it's a colleague where you have ideas about how you want to do something and you say I have these classes, I'm trying to put this architecture together, but I want to optimize it for low cost, low latency, that kind of thing.
Speaker 3:It's really good at taking all those different pieces and churning through them and putting it together, and 5 is a little bit better at that. There are still a few more models that you can split out. So if you're on a paid version, you still get the model picker at the top left where you can open GPT-5, it says flagship and then for other models you can pick between uh, or if you're a pro user you can do pro. So it does split it out by cost a bit, um, but all of them are a bit faster, a bit smarter and, uh, the base one, the gpt5, uh, non-thinking, it's super fast and it's still very good at thinking. I'm impressed. Like I have my, I send a prompt and before I pull my uh finger off the enter key, it's already started writing the first response in some cases. So it's crazy.
Speaker 1:I think it's been really interesting the way that I've been using it. Is it used to be that I would go to ChatGPT and I would like, oh this is something you could help me with, and then I would kind of interface with it and now, like an oracle, you know, I'd have to go to it and I would ask it and then it would answer me. Now what I do is I just have it downloaded to my desktop. I just keep one of the windows open. I have a dual window set up in my workstation, so I have a laptop, a second screen. On my second screen, I have Slack for work, I have ChatGPT and I have Spotify. Like. Those are the essentials at this point, and things that it's good for are drawing conclusions and drawing inferences from data sheets. Especially is what I've been having really good success with. I just did the episode before. This one was very much helped by chat GBT, where you know, oh, you're the one that built me the leaderboard exports. Remember that back in back in the day. Oh, yeah, the finance. That's right For the e-commerce performance reports, and what's super funny is I can look at it and, you know, draw inference on how e-commerce is doing.
Speaker 1:But there's you know however many columns there's like 70 columns in that thing and then each column has like 120 rows and you know, blah, blah, blah. There's all these things. It's every single month. I can only draw so much analysis from it, just because my brain has like a speed cap on it. You know it can only do so much analysis from it, just because my brain has like a speed cap on it. You know it can only do so much.
Speaker 1:But if you export one of those as a CSV and you feed it into this thing, it is so good. If you just give it a prompt like hey, I have this report, this is the industry. Here's the relationship between the columns. Can you give me some feedback on it? Then it does. And then you can just go one step further and be like can you draw some correlations that I might not have thought of? And it does? And the one that was really cool it was in the last episode, but it was about the number of logins correlates very closely. It correlates at like 0.77 correlation, which is out of one. It correlates between number of sales and also larger sales. So you could see that as people log in more, they're probably using their website more and they are making more sales, and I thought that was really cool, because I never once thought to correlate that column to one that's completely unrelated to it, but it was able to see that and I think that's what a robot is better at doing than the human mind.
Speaker 3:For sure, and that's where the biggest and, to your point, that's the biggest selling point I think, of these higher GPT models is their ability to pattern recognize Because, like you say, you can feed it, these csvs with tens of thousands of cells, and you can feed it across multiple months and you can spend your time going through each individual client and looking at, you know, doing the month over month. Even if you, you know, have those analytics broken out, it's still going to take you, you know, a good chunk of your morning and you give it a chat gbt and it does the work for it. And obviously, obviously, you know you have to have privacy concerns. There is a setting where you can say don't train future models on my data because you obviously don't want it. You know GPT-6 to start spitting out customers, e-commerce data.
Speaker 3:But that's one of the things that is architecture lends itself to super well is it's literally, it's a neural network. Well, is it's literally, it's a neural network. It's built out of all these neurons and they take the input that you give it and they process it and they feed into other layers and when these layers light up in a specific way, the gpt model sees that, oh, this node is lit up over here. What is, oh, this node is the month over month node, and it just does all that internally. Um, so it's. It's crazy. I mean, we're at the point where, uh it even the lead developers aren't 100 on how it picks up some of the patterns that it picks up. Right now it's just doing its own thing what?
Speaker 1:uh, what do you when you're talking about how you're using it? Uh, because, as I've started to talk to people, it's very, it almost feels very personal to ask like, hey, how are you using this new tool? But to to me, it's so sandbox right now that I think we should learn from each other. But no one seems to be talking about it, and the people who are talking about it are the kind of people I don't want to listen to right now. You know, like people that are way too into it, and so, as a result, I'm like asking my friends, like what are you doing? So here's what I've been using chat gpt for and I'm going to read, you know, like the, the summarization plots. Uh, on the sidebar you know I'm talking about for the different chats. So here is like the last couple uh, rewrite product data copy. So this is, I have it. Write a lot of copy for me. Basically, I like take bullet points, I put them in it, reformulates it. Email regarding vendor removal we removed a vendor. I didn't really know how to like formulate that thought without sounding like too casual or too serious. It's like okay, can you just write this for me.
Speaker 1:Grilled jalapeno poppers recipe All hands. Summary I fed it all of the bullet points from all hands and had it write a paragraph about it. It was kind of interesting. I probably won't do it though. Sharpening a single bevel knife. I had a question about like what degree should you sharpen a single bevel knife? Percentage calculations that's a big one for me. I'm not very good with math and, as a result, I have a hard time with percentages A lot of the times. I you remember one time I fired off the alarms. I was like something is wrong.
Speaker 1:This number is totally bad. And then Andy was like oh yeah, you still have to multiply by a hundred on that one or something like that. You need to move the decimal place, and it's like. Those are the kinds of things. It just fact checks me now. And what kind of things are you using for both at Punchmark and maybe in?
Speaker 3:your day-to-day Sure. Yeah, so for Punchmark, that's like I mentioned. Gpt-5 and its processors are super good at taking, especially for coding, taking large amounts of data and figuring out how to process it. I mentioned you can talk to it as a software guy. You can talk to it about ideas for architectures and it'll kind of roast you if it's a bad one or help you build it up, and it'll kind of roast you if it's a bad one or help you build it up.
Speaker 3:And between that and there's a bunch of just day-to-day like I'm trying to put a little couple of commands together to say, copy this file from one server to the other and then change these perms on it, do whatever. And I could definitely sit down and think about how to do each and every one of those and look at Google and get the exact syntax right for that. Or I can just say, hey, gbt, give me the commands to run. And again, you don't blindly just run it and take down the prod server or something. You look through it and make sure that it's actually doing what you want. But just those little things add up to a decent size serving every day of savings, just not having to do that kind of low level stuff Is it?
Speaker 1:does it know the punch mark code base, like? Does it know like a substantial amount of like, because it has to have that relationship to the source of truth? Is there, like at one point did someone have to like, you know, in like a private instance, share with it like, hey, here's the architecture for this space. That way it knows how to answer? Or is it just kind of guessing?
Speaker 3:So the reason we haven't done that so far, besides the privacy concerns well, I guess it's mitigated if you all agree to do that setting, which I think we all have at Punchmark. But it's just a ton of code, right? I mean, you look at our code base. It's, I think, in the gigs range, so it's way beyond what you can just give in a casual prompt to ChatGPT and ask it to tie it together. One way I am using it, though, is similar to that.
Speaker 3:There is something called IDE. If you're a software guy, it stands for Integrated Development Environment, and it's basically just a fancy term for the fancy notepad that you use to do all your coding. So it's basically a text editor that will help you autocomplete lines. It'll show you if your coding syntax is messed up. It's basically what most enterprise-level developers use to do all their coding.
Speaker 3:There's a new one that's come out in the last few months called Cursor, which I've been playing around with, and that basically does what you're talking about, where you install it on your computer, you load it, you load it up, you load in the code base like you would for any other IDE, and then on the side it has a little bar where you can say you can drag in like specific files. You literally just drag and drop it from parts of your IDE into like a little side panel and you say hey, this file is giving this response, this file is not liking it, blah, blah, blah. And then it'll go and it'll think and it'll actually change it in your IDE, right in front of you, and it'll basically just at the end say do you approve or not? And then you can say no, fix this. And it'll fix it. Or you can say yes, looks great, Now let's move on to this. So that's kind of the new way that AI is getting into. Coding is through those IDE plugins, Really interesting.
Speaker 1:It's so it hasn't really made its way into design yet. Just for example, I have an XD file here, adobe XD. That's what we design interfaces with and I'm trying to work on this, this new design for the vendor portal. And what's really interesting is like I could feel myself being, like I wish he could just put me on second base and basically let me start further down the road than me. Like right now, what did I have to do? I had to go and like frigging, draw things on a piece of paper to organize my thoughts. I had to meet with Brian. We had to bullet out all of these you know, key features and interactions and things like that and then start designing them. And then we're going to go through like know, uh, review and I kind of like wish I could just be like, hey, what is this interface supposed to look like? Can you give me ideas? But it hasn't really seemed to get there yet. But the functionality it does seem like there's a right and wrong way and that's why it can access that. All right, everybody. We're going to take a quick break and hear a word from our sponsor.
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Speaker 3:Oh man, that's going to take some digging to find that. All right, no, just kidding. So yeah, just some of the more more recent. So I'm a little bit of a hobbyist investor. I like to buy stock in some companies I believe in. So there's a lot of grunt work that goes in that. You have to look at their books, their cash flow, pl statements, earnings calls, see what the market thinks of them. All that yada, yada. Obviously that's super easy to automate through GPT-5.
Speaker 1:They can book for that. They can do all that for you.
Speaker 3:Oh, that's really interesting and that's what some of the. So one of the big problems that AI is trying to get past is called hallucination, which is where it just makes up something completely out of the blue. That's completely not true. You've seen some, you know you can have some benign example of that where it just you know gets whatever hat on something. Like if of that, where it just you know gets whatever hat on something. Like if something happened on some day and actually happened on another one, you're like no, it happened on saturday. You're like, okay, but on a big scale.
Speaker 3:Like there's some lawyers that have tried to use chat gpt in like filing their legal briefs, like paralegals, and it just makes up court cases out of old cloth sometimes. Um, I like some of the earlier ones. So, yeah, there's. You know, every industry has its version of vibe coding, I guess. So I guess that's the legal professions. But the most recent versions have something called a chain of thought, which is where it actually it gives itself a little internal answer to what your prompt is, and it'll, if you expand it, while GPT chat GPT is thinking, it'll say something like okay, the user is asking blah, blah, blah, and it'll talk through itself, thinking it'll say something like okay, the user is asking, uh, blah, blah, blah, um, and it'll talk through itself and it'll search the web and it'll find uh citations for exactly what it's saying and then it'll add it in line.
Speaker 3:So, uh, it doesn't completely solve the problem and it definitely makes it a lot slower, so you can't use it for everything, um, but yeah, yeah, exactly almost like a little wikipedia thing'll have a like the name of where it pulled it from and you can click on it and it'll take you right there. So as far as things that are very sensitive to like, I don't want you to hallucinate what their PNL statement was like it'll, if you want to double check it, and it'll bring you right to it. So it's definitely gotten a lot better in that respect.
Speaker 1:So let's just let's just talk about one of these examples. Can you pull one up? And I'm very interested in how you're formulating a query, because people have given me examples before but sometimes they don't. Like I'm curious, like what does one actually look like to someone? For example, for mine about this episode, I said I'd love to talk about GPT-5 on my podcast and highlight the main differences from four to five and new features and use cases for GPT-5 and how the wider public might be able to leverage it, but also make it interesting and tell me what I should be focused on. So that's like I'm just I don't know anything about GPT-5 yet. So it's like OK, give me like a, put me on second base, and I think that's kind of how I formulate my queries. What are you kind of starting with? Sure.
Speaker 3:I mean I won't recite my entire opening prompt because it's pretty long, but I give it a bunch of.
Speaker 3:I kind of give it a background about what's going on in general.
Speaker 3:I'll say kind of what's going on in the world the geopolitical side, the macroeconomic side. I'll tell it specifically to do its own research and put its own model together about how it sees the world. So there's a bunch of consulting companies out there that'll publish reports on something that's their opinion and I basically tell it to discard all that and build its own internal model from scratch so it has its own idea about where the world's at and where it might move. And then I tell it to think about how all these different factors in the world might interact and how these interactions might have impacts that are knock-on effects that impact other sectors in the future, have impacts that are knock-on effects that impact other sectors in the future. And when I say that the GPT neural network is very good at handling all that information and processing, it is really good. So it's obviously like I said, you don't want to vibe code your way through finance, obviously, but as far as just to use your term get you on second base, it's very strong.
Speaker 1:Do you think it is effective? Is it working for you? Because sometimes we talk about it, it's very strong. Do you think it is effective? Is it working for you? Because sometimes we talk about it it's like oh, and this is what I use it for, but no one tells you that it's like, it's not. It's definitely not perfect, but what about for this use case?
Speaker 3:It's very good, like I said, but what I'm using it for, which is doing the deep dive in the background, I'm not asking it to go out and make me $100,000. I'm coming at it with an idea of hey, I think this opportunity might be here in the market. Just give me a quick read, see if it's worth pouring more investment in and if it's something I want to look into.
Speaker 1:Yeah, I guess one of the examples that we had talked about when I was like, hey, do you mind coming on and just chatting about this with me? Was a couple of years ago, I think it was in 2020. In 2018, or 2019, I wrote a story. I tried my hardest to write a book and the big reason being I read so many books but I've never tried writing one. So I was like, okay, I should try this out, and this is obviously a while back, and my goal was I just wanted to write 50,000 words and it eventually got to, I think it's. I just pulled it up like 75,000 words or so at this point and a an average size book is like in the, you know, 90 to 150,000 word range. And what's funny is I didn't finish the book but I wrote enough of it that I felt pretty good about that and I thought it was a really interesting exercise. And I wrote it over the course of a year and I thought that that was like a fun experiment.
Speaker 1:But since I'd never finished it, I one time was like, should I feed this story into GPT, like chapter by chapter? So feed a chapter one, be like, hey, what are your thoughts on this and then go chapter two all the way to the end and then be like, well, that's the end of the story. I never wrote the rest of it. Here's the outline in the story sculpture. Can you write me the rest of the story? Do you think it could do that and match, like, my writing style? Or do you think it would hallucinate and like completely get off off target, or what do you think the result of that would be? Cause I'm tempted to try and the only thing that's stopping me is, like you know, ethics.
Speaker 3:Yeah, those pesky ethics. Yeah, I mean I, I would say if you, if you wanted to do that, it would probably do a very good job. Uhaders may or may not be able to spot the difference from when you stopped and when GPT started. That being said, we're moving to a place in the world where so much of everything is AI. You know the term AI slop is out there for just stuff that people create that just sparks engagement on the internet and you know people profit from it. But there's so much AI content out there that it's actually kind of interesting.
Speaker 3:Reddit as a company is valued very highly right now because it's a place where obviously, there's a bunch of bots but there's a bunch of people and the people are interacting. Their end goal is to use that and train AI models off the people interacting, which is to say, there's just going to be more AI stuff on the internet and out there, right? So I think there's a special dignity in not just waving away the ethics side and saying I want GPT to finish this story and it'll probably be a good story, but doing it yourself, putting it out there, going through the creative process and you're a creative guy, I mean, you're an artist, you understand all that, but I think using it as an editor more than a co-author would be the best way to do it.
Speaker 1:Yeah, I think that that's definitely one of those personal journeys that you have to go on, and I definitely know that some people do not have those scruples. I'm sure that there are so many books out there that have already been published and people are profiting off of it that were written, you know, maybe entirely or primarily by a bot, but yeah, I think it's kind of. There's something special, I think, about the tactile nature of human error. You know, the fact that it's like it's, it's pretty real, and that's what I always think about with my paintings is I think that people don't even really care about the image. It's more that it's on a piece of paper and if you hold it up close enough, you can see where, my like, paint bled into something else and in the errors in the pencil markings, and I think that's almost what people value more than they value the actual image of itself.
Speaker 1:It's that it was. You know it was paper and now it's a painting With development and coding. There is not necessarily that. You know there is no like this older form, this innate like source of truth. What do you see? Is it just like a like? Where do your morals kind of come in and prevent you from using Chachi Petit to run, like you know, the wider part of your life. Is that something you try to keep it at arm's length for, like, yeah, like what you should eat for the day.
Speaker 3:Well, I do use it to spin up a decent amount of recipes, so it does tell me what to eat for the day, but in general, yeah, I think it's it's not healthy to get super plugged into it. You hear stories of people with AI boyfriends and girlfriends and with ChatGPT 5 just getting rolled out. They pulled out all those old models that people had their boyfriends and girlfriends on, so they're probably not having a good time right now, but I think it's important, especially as, I say, more AI is going to. Ai is just going to keep exponentially rising more and more and it's definitely a temptation and a risk to let it run more of your life because it's it's so efficient and it's so optimized and it it's not necessarily wrong when it tells you how to handle your problems. But there's a risk that you and the GPT personality just kind of merge right and then you know you start talking like GPT-5 on the internet and we're already seeing that. How many MDASHs have you come across since GPT-5 rolled out? I mean that's a.
Speaker 3:I still. I'm at the point now where I smile a little every time I see someone with a typo in something that they write because I know it's written by a human being.
Speaker 1:It's isn't that so interesting because the m dash in particular so good people listening, uh, insight, the m dash is, if you, if you go dash dash, it usually forms into a longer one, but it's a hallmark of something written by um, by a bot. And what's really interesting is, uh, for a really long time I actually didn't know how to make an m dash and and I was like, so if I don't know and I write on the internet all the time, I'm pretty sure that this random person didn't know and this is something that they just copied out of somewhere. And I just think that you know, there's the whole you know dead internet theory. You know, with like, we're just there's only so many people on the internet and we're just reacting to information. That's not that was, you know, created by bots. And it's just like no one is actually on the internet anymore. We're not even talking to each other. But I'm not about you're a bot, exactly, people. It's something I've been thinking about. It's kind of funny.
Speaker 1:Why do we have this episode? Chat tpt5 came out, but to me it's just. I think it's a reasonable moment to check in and have us have like a real like, let's look at this thing. You know that whole. You were the one that showed me the south park episode about uh chachi vt and that was back. I was back. Uh, remember we were in raleigh when we watched that. We went and, um, uh, went to that event.
Speaker 1:Yeah, that was a bunch of years ago and at this point it's so crazy to think that that is however many models ago you know things that this thing is able to be way more complex. I think it's reasonable for people to just have a moment to analyze their own usage in relationship with this, with this tool. You know, if you only got a hammer, you're going to look for ways to use a hammer. So it's about being a little bit of having a little. It's about being a little bit of having a little bit of touch and a little bit of I don't know creativity with how you're using it, and not to lose the humanity of it all. You know what I mean For sure.
Speaker 3:It's a tool like any other. You know, it's a tool that's developed a lot quicker than I think most people were expecting, even people who thought years ago that AI might be coming soon. I think it has caught a lot of people off guard with how quickly it's gotten here, which is kind of how the last few innovations happened. No one had a smartphone in their pocket until everyone did right. No one had an email address until everyone did, so it's just one of those things where it's just it's here now. No one rode a Lime Scooter until they dropped those by the hundreds in cities all over the place.
Speaker 3:But yeah, it's a tool. It's not one that you should throw your entire life at, even if it's tempting. Use it for its purpose of helping you figure out searches. Help it analyze whatever your business need is, but don't give too much of your personality away to it. And also be careful what information that you give them, because even if you tell them don't train my information on future models, there's no guarantee that they're not going to do other selling of your information to advertisers or their own internal analytics. I wouldn't be surprised if they had a GPT that combed through everyone's account just to find the fun little nuggets of information to pull out. So be careful with that side. But yeah, if you can do all that and you can use it as a tool and be effective with it.
Speaker 1:I think it'll be great for you. Yeah, more power to you. Yeah, just, buyer beware, just be smart, andy. I think maybe that's where we'll end it Just kind of maybe a little more of a kind of a thoughtful, introspective episode. Normally I'm doing interviews, but sometimes I just think it's kind of fun to kind of, you know, muse about something and kind of think, but, andy, I really appreciate it. I'll let you get back to the end of your day. Thanks, everybody. I'll see you next time. New episodes every Tuesday. Bye. All right, everybody. That's another show. Thanks so much for listening. My guest this week was Andy Zoki, the backend developer at Punchmark. He's also one of my best friends. This episode was brought to you by Punchmark and produced and hosted by me, michael Burpo. This episode was edited by Paul Suarez with music by Ross Cockrum. Don't forget to rate the podcast on Spotify and Apple Podcasts and leave us feedback on punchmarkcom slash loop. That's L-O-U-P-E. Thanks. We'll be back next week, tuesday, with another episode. Cheers, bye.
