WEBVTT 00:00:00.020 --> 00:00:05.540 In this episode, I'm talking with Vincent Wormerdam about treating LLMs as just another API in your 00:00:05.650 --> 00:00:11.260 Python app with clear boundaries, small focused endpoints, and good monitoring. We'll dig into 00:00:11.410 --> 00:00:16.940 patterns for wrapping these calls, caching and inspecting responses, and deciding where an LLM 00:00:17.080 --> 00:00:22.900 API actually earns its keep in your architecture. This is Talk Python To Me, episode 528, 00:00:23.530 --> 00:00:25.660 recorded October 23rd, 2025. 00:00:44.100 --> 00:00:48.240 Welcome to Talk Python To Me, the number one podcast for Python developers and data scientists. 00:00:48.800 --> 00:00:53.860 This is your host, Michael Kennedy. 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Hey, welcome to Talk Python To Me. Hi. Welcome back. Pleasure 00:02:01.350 --> 00:02:06.200 to be here. Yeah, it's been like, this is our second Talk Python interview, I think. We've 00:02:06.300 --> 00:02:10.160 interacted before also on socials and all that, but like, yeah, second time. Yay. Happy to be here. 00:02:10.460 --> 00:02:15.759 Yeah. Yeah. It's very exciting to have you back. I, you know, I'm trying to remember, I did an 00:02:15.780 --> 00:02:18.060 blog post on 00:02:18.480 --> 00:02:20.100 the most popular episodes 00:02:20.780 --> 00:02:21.600 of last year. 00:02:22.140 --> 00:02:24.139 I think, if I do recall correctly... 00:02:25.240 --> 00:02:26.200 Yeah, the 00:02:26.260 --> 00:02:28.040 number one last year was our 00:02:28.220 --> 00:02:29.480 interaction, I think, on Spade. 00:02:29.800 --> 00:02:31.260 That's not terrible, is it? 00:02:31.840 --> 00:02:33.420 Yeah, it was a bragging right for a day. 00:02:34.140 --> 00:02:36.120 Yeah, it's pretty cool. So your episode 00:02:36.800 --> 00:02:38.100 and double bragging 00:02:38.300 --> 00:02:39.900 rights as your episode was released 00:02:40.220 --> 00:02:41.680 in, I don't know when that was, 00:02:42.060 --> 00:02:44.239 something like October or something, almost exactly 00:02:44.260 --> 00:02:49.700 a year ago to the day. And still it was the number one most downloaded for the whole year. So 00:02:50.000 --> 00:02:56.680 fantastic. And I think that might be an indication of where we're going to another very exciting 00:02:56.980 --> 00:03:01.340 topic, you know? Yeah. Like ML and AI only went up, right? So, so. 00:03:03.100 --> 00:03:08.120 You know what? I would love to get your thoughts on this. I, I'm seeing out on the internet and I 00:03:08.200 --> 00:03:13.580 want to put this up as kind of a, to counter this, this thought or whatever. But, but I'm seeing a 00:03:13.580 --> 00:03:20.640 lot of people get really frustrated that AI is a thing. You know, OpenAI just released their Atlas 00:03:21.180 --> 00:03:26.520 browser, which I'm not super excited about, but it's like their version of what an AI browser 00:03:26.820 --> 00:03:32.640 wrapping Chromium looks like, you know what I mean? And it's fine. But the comments in Ars Technica, 00:03:32.840 --> 00:03:37.060 which are usually pretty balanced, are just like people losing it over the fact that it has AI. 00:03:37.640 --> 00:03:42.060 Are people tired of this stuff? Or why do you think that's the reaction, I guess, is really what I 00:03:42.020 --> 00:03:47.780 want to ask you i mean i guess i have like a couple of perspectives but like i do like i think i could 00:03:47.900 --> 00:03:52.660 say like we are all tired that like every tech product out there is trying its best to find a 00:03:52.760 --> 00:03:58.400 way to put ai in the product like oh any any gmail any calendar app let's put ai in there and it 00:03:58.500 --> 00:04:02.580 gets a bit tiring like i wouldn't be too surprised if like fire hoses and refrigerators also come with 00:04:02.700 --> 00:04:09.439 ai features these days like it feels a bit nuts i know it's like what what is my refrigerating ai for 00:04:09.460 --> 00:04:39.260 Yeah, or like soccer ball of whatever object, like it feels like people are overdoing the AI thing. So okay, that can be like legitimate source of frustration. But then it also becomes a little bit personal, because I can also imagine if you put like, your heart and soul into like being a good engineer, and like you want to take the internet serious, like you consider it something is somewhat sacred, because it helped you so much in your career, then I definitely can also imagine like, Oh, my God, please don't turn that into a slop. Like I built a career on that. So that might be the source of all these things. I guess like my main way of dealing with it, 00:04:39.460 --> 00:04:43.500 is more along the lines of like, okay, like, this genie is not going to go back into the 00:04:43.670 --> 00:04:47.280 ball in a way. But if we're able to do more things with these LLMs, if they're able to 00:04:47.540 --> 00:04:52.420 automate more boilerplate and that sort of thing, then it seems that then I can try and 00:04:52.500 --> 00:04:56.180 get better at natural intelligence as well, instead of this artificial intelligence. So 00:04:56.280 --> 00:05:01.000 like, okay, I can vibe code all these things now. So the bottleneck is just do I have good 00:05:01.220 --> 00:05:06.020 ideas? And maybe I should invest in good ideas. And oh, maybe I can actually learn about 00:05:06.260 --> 00:05:09.420 JavaScript, but then I should not focus on the syntax, but it shouldn't focus maybe on 00:05:09.440 --> 00:05:14.860 the browser and like how does CSS work and oh I should actually maybe do a little bit of stuff 00:05:15.000 --> 00:05:19.680 with flashcards just so I know the syntax just enough so I can review okay like I try to be very 00:05:19.980 --> 00:05:23.940 conscious about it that way that's kind of my approach more and I it's easy to get really lazy 00:05:24.140 --> 00:05:28.480 right and just push the button and say do the next thing and not use it as an opportunity like oh it 00:05:28.510 --> 00:05:33.640 did something I didn't know let me have a conversation and try to understand the uh I 00:05:33.640 --> 00:05:37.320 didn't know I think the key word here is you want to be deliberate about it like I think if you can 00:05:37.280 --> 00:05:41.780 sort of say like okay i'm deliberate about the way i use this stuff and i'm also learning as i'm doing 00:05:41.980 --> 00:05:46.800 this like one thing i really like to do is i just give give like some sort of bonkers front-end task 00:05:46.940 --> 00:05:50.840 to the llm that i have no idea how i would solve it and then study the output like that's the thing 00:05:50.900 --> 00:05:56.480 i actually do once in a while um but yeah i mean i do get it that like people have mixed emotions 00:05:56.680 --> 00:06:01.140 about it and that's totally cool and fine it's just that for me in my situation this is how i 00:06:01.480 --> 00:06:07.240 deal with it yeah i think that's fair i think also i i definitely have long since been tired of like 00:06:07.260 --> 00:06:09.960 every email app having to rewrite this with AI 00:06:10.620 --> 00:06:12.160 and it usually destroys the email. 00:06:12.840 --> 00:06:14.180 You know, like removes all the formatting. 00:06:14.710 --> 00:06:15.420 And then you just, you know, 00:06:15.520 --> 00:06:16.980 there's always the cartoon of like, 00:06:17.300 --> 00:06:19.060 I wrote an email as bullet points. 00:06:19.150 --> 00:06:20.660 I asked AI to expand it. 00:06:20.690 --> 00:06:21.460 I sent it to you. 00:06:21.750 --> 00:06:22.700 You're like, what a long email. 00:06:23.100 --> 00:06:24.900 I'm gonna ask AI to summarize this. 00:06:25.260 --> 00:06:26.480 We should have just sent the bullet points. 00:06:27.620 --> 00:06:30.700 - Yeah, I mean, I do fear the amount of slop though. 00:06:30.860 --> 00:06:33.460 Like I do, it almost feels like every good tech YouTuber, 00:06:33.860 --> 00:06:35.560 there aren't a lot of good tech YouTubers anymore 00:06:35.580 --> 00:06:39.960 they're all doing AI stuff instead of doing like actual really great programming. There's still a 00:06:40.020 --> 00:06:45.300 few. Anthony writes code is like a really good one still. Like he's awesome. Definitely follow 00:06:45.620 --> 00:06:51.180 him if you want to learn Python. He does cool stuff. But yeah, the main thing, I guess from my 00:06:51.300 --> 00:06:55.520 like selfish perspective, YouTube used to be better because nowadays it's all about the AI and you've 00:06:55.580 --> 00:06:59.360 always got this thumbnail of a guy pulling his hair out like, oh my God, this changes everything. 00:06:59.840 --> 00:07:02.120 Yeah. I would love to see a video that's maybe not that. 00:07:03.060 --> 00:07:05.060 Have you heard that there's an AI bubble that's going to burst? 00:07:05.240 --> 00:07:12.820 um yeah well we'll see exactly how far i think so actually i mean we can speculate like i i can 00:07:12.950 --> 00:07:16.600 argue that it's been over invested i can also argue there's still so much potential the one 00:07:16.600 --> 00:07:21.280 thing i will say though um we have Claude kinds of tools and like we're all looking forward to like 00:07:21.280 --> 00:07:24.920 the vibe coding oh it's never been easier and that sort of thing but i would have expected an explosion 00:07:24.930 --> 00:07:29.540 of awesome apps to be going along with it and it doesn't necessarily feel like we have much better 00:07:29.700 --> 00:07:34.680 software even though we supposedly have way better tools so something about that is making me a little 00:07:34.700 --> 00:07:38.020 a bit suspicious, but it might also just be that the apps that are being built that I'm not the 00:07:38.170 --> 00:07:42.320 target audience for, because I can imagine that. Because let's say you have something awesome for 00:07:42.500 --> 00:07:46.620 dentists, they can still be an awesome crud app that you could build with Claude, but I'm not a 00:07:46.720 --> 00:07:52.820 dentist. So, you know, wow, there's a lot of new cool dentistry management apps. You're right. 00:07:53.280 --> 00:07:58.600 If a dentist can outprogram, right? Like I do believe in the story that, oh, as a dentist, 00:07:58.810 --> 00:08:02.840 you might be best equipped to write an app for dentists, right? And if they're now more empowered 00:08:02.860 --> 00:08:04.580 to maybe do some stuff with code. 00:08:04.670 --> 00:08:06.080 I mean, there's a story there 00:08:06.200 --> 00:08:07.480 that every single niche profession 00:08:07.840 --> 00:08:10.160 will have someone who can do enough clod 00:08:10.190 --> 00:08:11.480 to make the app for that profession. 00:08:12.420 --> 00:08:12.520 Yeah. 00:08:13.240 --> 00:08:13.940 Well, time will tell. 00:08:13.940 --> 00:08:16.460 It used to be that you have to have a programming skill 00:08:16.660 --> 00:08:18.900 and a little bit of, let's say, dentistry experience 00:08:19.440 --> 00:08:21.660 to build the right sort of specialized vertical. 00:08:21.960 --> 00:08:23.160 And now I think it maybe is reversed. 00:08:23.560 --> 00:08:24.800 You need a lot of dentistry 00:08:25.110 --> 00:08:27.800 and a little bit of coding skill to go along with an AI. 00:08:28.260 --> 00:08:28.380 Yeah. 00:08:29.440 --> 00:08:32.039 The character sheet used to be 80 points here, 20 points there. 00:08:32.140 --> 00:08:34.260 and now it's 80 points there and 20 points here. 00:08:34.520 --> 00:08:34.800 Yes, exactly. 00:08:35.219 --> 00:08:36.260 That's exactly what I was thinking. 00:08:36.300 --> 00:08:37.820 Like, I think maybe that's actually shifted 00:08:38.200 --> 00:08:39.039 until you said that. 00:08:39.039 --> 00:08:39.960 I've never really thought about it, 00:08:40.039 --> 00:08:41.000 but it just may be. 00:08:41.539 --> 00:08:44.260 I do want to point out for people listening, 00:08:44.420 --> 00:08:47.020 we're not going to really talk too much 00:08:47.180 --> 00:08:51.280 about like using agentic tools to write code for us. 00:08:51.400 --> 00:08:52.580 Like we have been speculating 00:08:52.720 --> 00:08:53.820 about this theoretical dentist. 00:08:55.100 --> 00:08:56.460 But what instead we're going to do 00:08:56.680 --> 00:08:58.660 is we're going to talk to you, Vincent, 00:08:59.020 --> 00:09:01.560 about how can I use an LLM 00:09:01.700 --> 00:09:08.020 like a library or an API to add functionality, features, behaviors to an existing data science 00:09:08.300 --> 00:09:12.340 tool or to an existing web app or whatever it is we're building, right? 00:09:12.640 --> 00:09:12.880 Yes. 00:09:13.360 --> 00:09:18.480 So also people might probably know it, but I made a course for Talk Python, of course, 00:09:18.480 --> 00:09:20.480 and we're going to talk about some of those details. 00:09:21.000 --> 00:09:25.820 But the idea for that course was not necessarily like, how can I use LLMs to build me software? 00:09:26.100 --> 00:09:29.260 It's more, oh, how can I build software that also uses LLMs under the hood? 00:09:29.340 --> 00:09:33.240 Like if I have an app that makes a summary, how can I make sure the summary is reliable? 00:09:33.540 --> 00:09:36.680 And basically get the ball rolling on those building blocks. 00:09:36.860 --> 00:09:37.720 That's what that course is about. 00:09:37.860 --> 00:09:41.200 That's also probably going to be the main bones of this topic as opposed to a dentist 00:09:41.460 --> 00:09:43.480 Bob and his ambitions to make a new tech startup. 00:09:44.340 --> 00:09:44.700 Exactly. 00:09:45.040 --> 00:09:47.280 We're going to grow new teeth if we just could get the software right. 00:09:47.780 --> 00:09:48.920 Now, yeah. 00:09:48.990 --> 00:09:49.860 So how do you do that? 00:09:49.890 --> 00:09:51.040 And we're going to talk about that before. 00:09:51.390 --> 00:09:56.240 I just want to give you a chance before we really dive too far into the details of how 00:09:56.260 --> 00:10:00.400 we make that work is just, you know, give people a sense of what you've been up to lately. 00:10:00.540 --> 00:10:02.940 You've done a lot of cool stuff with CalmCode.io. 00:10:04.120 --> 00:10:07.540 I can see your YouTube game is growing strong here. 00:10:08.559 --> 00:10:10.860 And you've been doing a lot of data science at Marimo. 00:10:11.340 --> 00:10:12.180 Yeah, what's... 00:10:12.420 --> 00:10:12.580 Right. 00:10:12.720 --> 00:10:15.900 Yeah, so we haven't spoken in a year, so maybe we should catch up. 00:10:16.500 --> 00:10:19.480 So long story short, CalmCode is still a project that I maintain. 00:10:19.800 --> 00:10:24.500 It's basically 99% free educational content on Python. 00:10:24.780 --> 00:10:26.520 that thing is just going to maintain itself. 00:10:27.540 --> 00:10:28.760 Super happy to keep maintaining it. 00:10:29.190 --> 00:10:30.500 The main thing I'm doing with that nowadays 00:10:30.670 --> 00:10:32.500 is just every two months I switch cloud providers 00:10:32.710 --> 00:10:33.560 just because I can, 00:10:33.610 --> 00:10:35.740 and then I can sort of see what it's like on the other side. 00:10:36.380 --> 00:10:37.100 So that's the thing that I do. 00:10:37.680 --> 00:10:38.480 From Calm Cult, though, 00:10:38.650 --> 00:10:40.080 I figured I might also start a YouTube channel, 00:10:40.210 --> 00:10:41.600 and that ended up being a YouTube channel 00:10:41.630 --> 00:10:42.980 where I still talk about Python stuff, 00:10:43.090 --> 00:10:45.760 but I mainly talk about these fancy ergonomic keyboards 00:10:46.010 --> 00:10:47.240 because I had a couple of RSI issues. 00:10:47.960 --> 00:10:48.740 In a year's time, 00:10:48.890 --> 00:10:51.080 I went from 100 subscribers to 5,000 something, 00:10:51.310 --> 00:10:52.760 so this thing kind of took off. 00:10:53.160 --> 00:10:53.460 That's awesome. 00:10:53.560 --> 00:10:55.680 I actually have sponsors now. 00:10:55.750 --> 00:10:59.980 So I actually have a couple of companies in Asia sending me their custom boards for me to review. 00:11:00.110 --> 00:11:01.640 So that's been a really fun journey. 00:11:02.090 --> 00:11:04.140 But since last time we spoke, I also switched employers. 00:11:04.400 --> 00:11:07.420 So people might have heard of Jupyter before. 00:11:07.720 --> 00:11:10.400 That's an environment in Python where you can do interactive things. 00:11:10.900 --> 00:11:15.320 And I work now for a company that makes Maremo, which is an alternative, a very likable one. 00:11:15.390 --> 00:11:16.820 It does work completely differently. 00:11:17.520 --> 00:11:23.260 One of the main things that attracts people to it is the fact that these kinds of notebooks are Python files under the hood. 00:11:23.520 --> 00:11:25.000 They're also a little bit more interactive. 00:11:25.180 --> 00:11:27.420 You can do more rapid prototyping with UI. 00:11:27.680 --> 00:11:29.240 You can blend Python with it very nicely. 00:11:30.260 --> 00:11:34.120 So I will say like all of my rapid prototyping, especially with LLMs, I do that in Marimo 00:11:34.360 --> 00:11:37.760 nowadays just so you can blend Python with UIs very easily. 00:11:38.340 --> 00:11:40.460 And there's demos on the site that people can go ahead and check out. 00:11:41.299 --> 00:11:44.800 But that's also the second YouTube channel I made this year. 00:11:45.000 --> 00:11:46.580 I do a lot of stuff for Marimo. 00:11:47.060 --> 00:11:51.720 I'm a little bit more on the growth side of things than the hardcore engineering side of things. 00:11:51.740 --> 00:11:55.700 I still make a lot of plugins for Marimo, of course, but that's a little bit more of what I do nowadays. 00:11:56.700 --> 00:11:58.800 Making sure that people learn about Marimo. 00:12:00.120 --> 00:12:02.360 You can do things in a notebook now that you couldn't think of before. 00:12:03.180 --> 00:12:08.800 I write my command line apps in a notebook nowadays because it's actually not just because I can, but because it's convenient too. 00:12:09.040 --> 00:12:14.440 So we'll talk a little bit about that later when we talk about LLMs, but that's effectively the short story of what I've been doing last year. 00:12:14.660 --> 00:12:17.720 Nice. All right. I am a fan of Marimo. 00:12:18.860 --> 00:12:19.480 Happy to hear it. 00:12:19.620 --> 00:12:47.340 Yeah, yeah, yeah. I did a data science course this year, just enough Python and software engineering for data scientists. Like, you know, what could you bring from the software engineering side to like sort of make your, your data engineering, data science stuff a little more reliable. But I was right on the fence of should I, should I use this? Because it's, I think it's clearly better. But at the same time, I also want to use what people are using. So I didn't quite go for it. But I just, the UI is fantastic. 00:12:47.620 --> 00:12:50.100 the reproducibility, reliability of it, 00:12:50.380 --> 00:12:52.320 where it uses the abstract syntax tree 00:12:52.500 --> 00:12:53.480 or concrete, whatever, 00:12:54.000 --> 00:12:55.940 to understand relationships across cells 00:12:56.120 --> 00:12:57.440 so they don't get out of sync, potentially. 00:12:57.860 --> 00:12:59.380 Yeah, I think it's really nice. 00:12:59.500 --> 00:13:00.560 I had Akshay on the show, 00:13:01.360 --> 00:13:02.220 who you work with also, 00:13:02.560 --> 00:13:03.220 to talk about it. 00:13:03.780 --> 00:13:06.660 The one thing in Jupyter that's, 00:13:07.300 --> 00:13:08.720 I mean, let me start by saying, 00:13:08.980 --> 00:13:10.360 Jupyter is still a really cool project. 00:13:10.520 --> 00:13:12.000 Like if I think back of the last decade, 00:13:12.380 --> 00:13:13.820 like all the good that that project 00:13:13.880 --> 00:13:14.820 has brought to my career, 00:13:14.960 --> 00:13:16.160 not just directly as a user, 00:13:16.280 --> 00:13:17.020 but also indirectly, 00:13:17.700 --> 00:13:19.160 all the algorithms that got invented 00:13:19.350 --> 00:13:20.940 simply because we had a good enough 00:13:21.640 --> 00:13:23.240 interactive environment suddenly, which we never 00:13:23.400 --> 00:13:24.940 had before, it's done wonders. 00:13:25.120 --> 00:13:26.840 So we should definitely be thankful. 00:13:27.230 --> 00:13:28.600 Yeah, I'm not bashing on it either. 00:13:29.010 --> 00:13:31.200 Yeah, but I do always want to 00:13:31.280 --> 00:13:33.120 make sure that I give credit where credit is due, because 00:13:33.620 --> 00:13:34.940 the project had a lot of impact. 00:13:35.240 --> 00:13:37.000 But there is this really annoying thing with Jupyter, though. 00:13:37.220 --> 00:13:39.200 Besides, you can be a bit grumpy 00:13:39.270 --> 00:13:41.220 about the file format, sure, but the one thing that's 00:13:41.270 --> 00:13:42.960 very annoying is you can write down 00:13:43.170 --> 00:13:45.160 X is equal to 10, and then 00:13:45.160 --> 00:13:47.040 have all sorts of cells below it that depend on X, 00:13:47.420 --> 00:13:50.560 You could then delete the cell and the notebook will not complain to you about it. 00:13:51.700 --> 00:13:58.320 Even though if anyone else tries to rerun the notebook, X is gone, it won't run, and your notebook is broken and you can't share the thing anymore. 00:13:58.710 --> 00:14:02.680 And nowadays, fast forward like many years later, and we've got stuff like uv now. 00:14:02.830 --> 00:14:05.720 So we can add metadata to a Python file to add dependencies. 00:14:06.160 --> 00:14:11.100 And oh, wait, because Marimo is a Python file, we can add dependencies to the notebook that makes it super reproducible. 00:14:11.480 --> 00:14:17.820 There's just all this stuff that you can rethink now simply because we have a good notebook format that is still a Python file. 00:14:18.100 --> 00:14:19.680 That's really the killer feature here. 00:14:20.759 --> 00:14:24.720 We can talk more about it if you like, but I can talk for ages about this topic, just warning you. 00:14:25.600 --> 00:14:29.140 One final thing, maybe also for the software engineering side of things, because you didn't mention it. 00:14:29.560 --> 00:14:31.340 Just to give an example of something we added recently. 00:14:31.920 --> 00:14:38.860 If you have a cell in Marimo and there's a function in there that starts with test underscore, we will automatically assume it's a pytest. 00:14:39.240 --> 00:14:41.820 So you can actually add unit tests to your notebook as well. 00:14:41.940 --> 00:14:44.360 And then if you say python notebook.py, 00:14:44.800 --> 00:14:46.940 then pytest will just run all the tests for you, 00:14:47.160 --> 00:14:49.840 even though you can also run the tests in line in your CI CD as well. 00:14:49.920 --> 00:14:52.720 So there's all sorts of these Python specific things that we can add, 00:14:53.100 --> 00:14:54.340 again, because it's just a Python file. 00:14:54.620 --> 00:14:57.940 Yeah, it's sort of the second mover advantage or nth mover advantage 00:14:58.260 --> 00:15:00.680 where n is greater than one, where you see, okay, that was awesome. 00:15:01.000 --> 00:15:02.880 Maybe this was a little bit of a rough edge. 00:15:02.960 --> 00:15:05.840 And what would we do to work around that or smooth it out, right? 00:15:06.140 --> 00:15:09.600 Well, and also we're also lucky that we're born in the age of uv. 00:15:09.880 --> 00:15:14.140 I got to say like a lot of like quality of life improvements to a notebook. 00:15:15.180 --> 00:15:17.100 A lot of that is also due to the fact that uv is around. 00:15:17.220 --> 00:15:18.600 That's definitely a huge help as well. 00:15:20.640 --> 00:15:23.900 This portion of Talk Python To Me is brought to you by Sentry's Seer. 00:15:24.600 --> 00:15:27.380 I'm excited to share a new tool from Sentry, Seer. 00:15:27.960 --> 00:15:30.740 Seer is your AI driven pair programmer that finds, 00:15:31.020 --> 00:15:35.240 diagnoses and fixes code issues in your Python app faster than ever. 00:15:35.480 --> 00:15:39.420 If you're already using Sentry, you are already using Sentry, right? 00:15:39.940 --> 00:15:44.220 Then using Seer is as simple as enabling a feature on your already existing project. 00:15:45.020 --> 00:15:48.360 Seer taps into all the rich context Sentry has about an error. 00:15:48.860 --> 00:15:52.920 Stack traces, logs, commit history, performance data, essentially everything. 00:15:53.560 --> 00:15:57.640 Then it employs its agentic AI code capabilities to figure out what is wrong. 00:15:58.240 --> 00:16:02.040 It's like having a senior developer pair programming with you on bug fixes. 00:16:02.920 --> 00:16:08.180 SEER then proposes a solution, generating a patch for your code and even opening a GitHub pull request. 00:16:08.630 --> 00:16:13.320 This leaves the developers in charge because it's up to them to actually approve the PR. 00:16:13.740 --> 00:16:17.540 But it can reduce the time from error detection to fix dramatically. 00:16:18.260 --> 00:16:23.800 Developers who've tried it found it can fix errors in one shot that would have taken them hours to debug. 00:16:24.500 --> 00:16:28.900 SEER boasts a 94.5% accuracy in identifying root causes. 00:16:29.580 --> 00:16:36.260 SEER also prioritizes actionable issues with an actionability score, so you know what to fix first. 00:16:36.760 --> 00:16:43.780 This transforms Sentry errors into actionable fixes, turning a pile of error reports into an ordered to-do list. 00:16:44.420 --> 00:16:53.500 If you could use an always-on-call AI agent to help track down errors and propose fixes before you even have time to read the notification, check out Sentry's SEER. 00:16:54.140 --> 00:16:58.120 Just visit talkpython.fm/SEER, S-E-E-R. 00:16:58.740 --> 00:17:00.620 The link is in your podcast player show notes. 00:17:01.220 --> 00:17:03.320 Be sure to use our code, Talk Python. 00:17:03.820 --> 00:17:04.699 One word, all caps. 00:17:05.380 --> 00:17:07.420 Thank you, Dysentry, for supporting Talk Pythonemy. 00:17:08.720 --> 00:17:10.500 I saw on, gosh, where was it? 00:17:10.699 --> 00:17:13.760 Speaking of Reddit, I saw on slash R, 00:17:14.270 --> 00:17:15.760 learn Python or slash R Python. 00:17:16.060 --> 00:17:19.020 One of the slash R's with a Python substring. 00:17:19.280 --> 00:17:23.060 Someone asks, what Python package manager would you use now? 00:17:23.140 --> 00:17:26.459 And it's just like, how many times can you say UV? 00:17:27.819 --> 00:17:29.200 The feedback comments. 00:17:29.400 --> 00:17:31.460 I mean, it was someone new who wasn't unsure, right? 00:17:31.860 --> 00:17:32.900 They've seen all the different ones. 00:17:33.460 --> 00:17:34.100 And yeah. 00:17:34.660 --> 00:17:38.160 I mean, the coolest comparison I've seen, I think it was a tweet someone posted. 00:17:38.300 --> 00:17:41.360 But like, definitely, like, suppose you're in the data field right now. 00:17:41.500 --> 00:17:42.780 Like, what are the tools 10 years ago? 00:17:42.980 --> 00:17:43.680 What are the tools now? 00:17:43.960 --> 00:17:46.800 It definitely does feel like, okay, before we had pip, now we have uv. 00:17:47.300 --> 00:17:49.400 Before we had Pandas, now we have Polars. 00:17:50.360 --> 00:17:52.180 Before we had Matplotlib, now we have Altair. 00:17:52.240 --> 00:17:53.700 And before we had Jupyter, now we've got Marino. 00:17:53.780 --> 00:17:57.000 You can kind of see a generational shift, not just on the notebook side of things, 00:17:57.100 --> 00:17:59.500 but like on the package manager, on the data frame library, 00:18:00.280 --> 00:18:01.980 we're all learning from the previous generation 00:18:02.200 --> 00:18:03.180 and it kind of feels like. 00:18:03.300 --> 00:18:04.000 Yeah, absolutely. 00:18:04.380 --> 00:18:05.820 It's an amazing time. 00:18:06.400 --> 00:18:08.620 Every single day in Python is just more exciting 00:18:08.700 --> 00:18:09.280 than the day before. 00:18:09.620 --> 00:18:09.780 Yeah. 00:18:10.320 --> 00:18:12.460 Although I should also mention, especially with the Polars 00:18:12.500 --> 00:18:13.740 thing, there's a fair bit of rust too. 00:18:14.420 --> 00:18:16.020 That also makes a difference. 00:18:16.440 --> 00:18:17.560 Yeah, yeah, of course. 00:18:17.760 --> 00:18:22.280 So before Flyby, I mean, you talked a bit about your YouTube 00:18:22.880 --> 00:18:25.100 channel, you review the economic keyboards. 00:18:25.420 --> 00:18:29.680 you have for those people who are just listening, not watching your background is super nice. 00:18:30.320 --> 00:18:35.280 Your bona fides are solid here, but you've got a bunch of different ones. And I personally also, 00:18:35.700 --> 00:18:38.400 I don't know, you might even just kick me out of the club if I should do that. 00:18:38.480 --> 00:18:39.880 That's the Microsoft Sculpt, right? 00:18:40.600 --> 00:18:44.800 Microsoft Sculpt ergonomic. And I like it so much because I can take this little bottom thing off 00:18:44.800 --> 00:18:49.140 and it's like razor thin if I could rotate and reverse and jam it in my backpack and take it 00:18:49.240 --> 00:18:55.380 with me. But I've also had RSI issues for 25 years or something. And it was really bad. And I switched 00:18:55.400 --> 00:18:56.760 I used to type them on like laptops and stuff. 00:18:56.840 --> 00:19:01.080 And I switched to just something like this and I could type 10 hours a day and 00:19:01.120 --> 00:19:02.360 there's no problem. Whereas before, if I, 00:19:02.400 --> 00:19:05.220 if I were to force to type full on, on a laptop, 00:19:05.460 --> 00:19:08.980 I would probably be like unable to work in a week. If not a week. 00:19:09.420 --> 00:19:12.980 So we had an offsite in San Francisco. So I was there like two weeks ago, 00:19:13.460 --> 00:19:16.080 a lot of fun, but like, I'm not going to bring like, 00:19:16.860 --> 00:19:18.680 airport security is going to look at this and wonder what, 00:19:19.560 --> 00:19:22.640 like what kind of weird alien device this is. Right. So I figured, okay, 00:19:22.780 --> 00:19:25.180 I'll leave those at home and just bring my normal laptop. And after a week, 00:19:25.220 --> 00:19:26.660 I'm feeling it in my wrist again. 00:19:27.020 --> 00:19:27.520 It's not good. 00:19:27.940 --> 00:19:29.240 Yeah, it's something that takes serious. 00:19:29.360 --> 00:19:31.400 Although I will also say like 00:19:32.600 --> 00:19:34.400 because the kid was sick and the wife was sick 00:19:34.460 --> 00:19:36.200 so I wasn't able to do a whole lot of exercise at home. 00:19:37.040 --> 00:19:37.620 Also do exercise. 00:19:37.880 --> 00:19:39.220 That also totally helps. 00:19:39.300 --> 00:19:39.900 If I had to like, 00:19:40.920 --> 00:19:42.660 sure, buy an ergonomic keyboard if you like. 00:19:42.740 --> 00:19:43.760 Programmatic keyboards, they're great. 00:19:44.120 --> 00:19:45.240 But if you're going to do that as an excuse 00:19:45.380 --> 00:19:46.800 not to do exercise, you're doing it wrong. 00:19:47.120 --> 00:19:48.860 That's the one thing I do want to add to that. 00:19:48.960 --> 00:19:50.220 There's lots of stretches you can do. 00:19:50.460 --> 00:19:51.160 Taking breaks matters. 00:19:51.660 --> 00:19:52.300 Exercise matters. 00:19:53.020 --> 00:19:56.040 But I think those keyboards are an essential feature. 00:19:56.520 --> 00:19:58.560 They do totally help. 00:19:58.600 --> 00:20:01.140 And also, sometimes it's not so much a healing measure. 00:20:01.340 --> 00:20:02.400 It's more of a preventative measure. 00:20:02.760 --> 00:20:03.740 Yes, 100%. 00:20:04.040 --> 00:20:09.520 And I would like to put this message out just to everyone listening who is young, absolutely indestructible. 00:20:11.360 --> 00:20:11.840 Please. 00:20:12.420 --> 00:20:15.520 I know they're a bit of a pain in the butt with the weird curviness. 00:20:15.900 --> 00:20:20.540 It is so worth it to just say, I've never had any RSI issues. 00:20:21.060 --> 00:20:22.980 I just use this weird keyboard and people make fun of me, 00:20:23.010 --> 00:20:23.560 but I don't care. 00:20:23.740 --> 00:20:26.840 You know, that is a better thing than like, I'm working on it. 00:20:27.220 --> 00:20:27.420 Yeah. 00:20:27.660 --> 00:20:28.140 Oh, my. 00:20:28.140 --> 00:20:28.420 It hurts. 00:20:28.610 --> 00:20:28.880 You know? 00:20:29.400 --> 00:20:31.600 Well, another thing is also, especially now 00:20:31.640 --> 00:20:32.840 we've got stuff like Claude, right? 00:20:32.840 --> 00:20:35.240 I just want-- if I can point out like one thing on that front. 00:20:36.180 --> 00:20:37.880 So these ergonomic keyboards, you can often 00:20:38.190 --> 00:20:39.460 program them as you see fit. 00:20:39.620 --> 00:20:41.880 So you can say, like, if I hit this key, it's K. 00:20:42.010 --> 00:20:43.740 But if I hold it down, it becomes command, 00:20:43.960 --> 00:20:44.920 or whatever you like. 00:20:45.180 --> 00:20:47.000 But it also means that you can map macros or shortcuts. 00:20:47.280 --> 00:20:51.020 So whenever I hit this button, an app called MacWhisperer boots 00:20:51.040 --> 00:20:51.720 That's going to record my voice. 00:20:51.720 --> 00:20:52.680 I love Mac Whisper. 00:20:53.140 --> 00:20:53.240 Yeah. 00:20:53.620 --> 00:20:55.360 And then there's alternative variants for it. 00:20:55.380 --> 00:20:56.800 I'm sure you've got stuff for Linux as well. 00:20:56.880 --> 00:20:59.280 But the main thing it does is just really good speech to text. 00:20:59.740 --> 00:21:01.680 And then whenever I'm done talking, 00:21:01.840 --> 00:21:03.800 it's just immediately going to paste whatever I'm in. 00:21:04.260 --> 00:21:06.240 So, oh, that's actually very nice, 00:21:06.420 --> 00:21:08.700 because now the keyboard shortcut is just me holding my thumb down 00:21:08.840 --> 00:21:14.420 instead of some sort of weird claw I got to eject to my keyboard. 00:21:15.000 --> 00:21:17.780 And suddenly, it doesn't necessarily become a convenience thing. 00:21:17.880 --> 00:21:20.100