WEBVTT 00:00:00.000 --> 00:00:03.419 The Internet, well, it's just flooded with claims 00:00:03.419 --> 00:00:06.019 these days, isn't it? You hear about AI agents, 00:00:06.219 --> 00:00:08.699 maybe even these magic money printing machines. 00:00:09.060 --> 00:00:10.900 Yeah, lots of noise. But what's the real story? 00:00:11.000 --> 00:00:13.419 I mean, are they actually a breakthrough or is 00:00:13.419 --> 00:00:15.720 it just, you know, chatbots with better marketing? 00:00:16.199 --> 00:00:19.079 Well, welcome to the Deep Dive. Today, we're 00:00:19.079 --> 00:00:21.039 definitely going to try and cut through that 00:00:21.039 --> 00:00:22.760 hype. We're doing a head -to -head comparison. 00:00:23.579 --> 00:00:25.699 We took two of the big ones everyone's talking 00:00:25.699 --> 00:00:29.579 about, ChatGPT's new agent mode and... The more 00:00:29.579 --> 00:00:32.920 established Genspark AI, we really put them to 00:00:32.920 --> 00:00:34.820 the test. OK, so we're going to define what an 00:00:34.820 --> 00:00:37.659 AI agent really is, not just the buzzword. Right. 00:00:37.820 --> 00:00:40.759 Then dive into how they actually did, you know, 00:00:40.780 --> 00:00:43.460 real world business stuff. And finally, give 00:00:43.460 --> 00:00:46.520 our verdict. Exactly. And hopefully you'll walk 00:00:46.520 --> 00:00:48.679 away with a kind of operator's manual, not just 00:00:48.679 --> 00:00:51.390 the what, but the how. how you can actually use 00:00:51.390 --> 00:00:53.549 these things effectively. All right. Let's start 00:00:53.549 --> 00:00:55.189 with that big distinction, because I think that's 00:00:55.189 --> 00:00:57.689 where people get tripped up. Chatbot versus AI 00:00:57.689 --> 00:01:00.250 agent. They sound similar, but they're not the 00:01:00.250 --> 00:01:02.750 same thing at all. Yeah. Think of a chatbot like 00:01:02.750 --> 00:01:05.519 a helpful assistant. Answers questions. Does 00:01:05.519 --> 00:01:07.879 a single task you tell it to? It's conversational, 00:01:07.920 --> 00:01:09.719 sure, but it's kind of waiting for your next 00:01:09.719 --> 00:01:11.900 command. It responds. That's the key. Exactly. 00:01:12.040 --> 00:01:15.560 An AI agent, though, that's more like a project 00:01:15.560 --> 00:01:18.439 manager or maybe even an intern like we'll get 00:01:18.439 --> 00:01:21.299 into. It can handle multiple complex tasks. It 00:01:21.299 --> 00:01:23.599 goes out and finds information itself, makes 00:01:23.599 --> 00:01:26.260 decisions, tries things to hit a goal you set. 00:01:26.480 --> 00:01:30.540 It's not just answering. It's doing. It's acting, 00:01:30.620 --> 00:01:33.040 taking initiative. Right. So first up. Contender 00:01:33.040 --> 00:01:36.780 number one, ChatGPT Agent Mode. This is OpenAI's 00:01:36.780 --> 00:01:39.219 big splash, right? They took the world's most 00:01:39.219 --> 00:01:43.459 famous AI and basically gave it the keys to the 00:01:43.459 --> 00:01:45.519 car. It's a big deal for them. And the idea is 00:01:45.519 --> 00:01:48.280 that ChatGPT can now actually do stuff, browse 00:01:48.280 --> 00:01:50.480 the web, analyze files, write code, run code, 00:01:50.560 --> 00:01:52.680 do multi -step things. Yeah. It's like that brilliant 00:01:52.680 --> 00:01:55.760 conversational brain we know, but now it's controlling 00:01:55.760 --> 00:01:58.340 the engines and steering the ship. It's pretty 00:01:58.340 --> 00:02:01.060 ambitious. Yeah, it is. Then there's contender 00:02:01.060 --> 00:02:05.140 number two. Genspark AI. Now, this one's a bit 00:02:05.140 --> 00:02:07.700 different, more specialized, not trying to be 00:02:07.700 --> 00:02:09.659 the do everything machine. It's built for specific 00:02:09.659 --> 00:02:11.840 kinds of work. What's really interesting with 00:02:11.840 --> 00:02:16.360 Genspark is strength seems to be as a strategic 00:02:16.360 --> 00:02:20.009 idea generator. It won't just write one marketing 00:02:20.009 --> 00:02:22.629 email. It's designed to maybe give you three 00:02:22.629 --> 00:02:25.110 completely different angles for that email, different 00:02:25.110 --> 00:02:27.469 subject lines, different approaches. It's meant 00:02:27.469 --> 00:02:29.610 to spark new ideas. That's a good way to put 00:02:29.610 --> 00:02:32.509 it. So if you think about analogies, chat GPT 00:02:32.509 --> 00:02:35.250 agent mode is maybe the huge Hollywood blockbuster. 00:02:35.569 --> 00:02:38.569 Big name, big potential, lots of buzz. Right. 00:02:38.689 --> 00:02:40.849 But maybe, you know, some rough edges. Feels 00:02:40.849 --> 00:02:43.370 a bit like a version 1 .0 sometimes. And GenStuck 00:02:43.370 --> 00:02:46.129 AI. That's more like the critically acclaimed 00:02:46.129 --> 00:02:49.289 indie film. Ah, yeah. Less famous, maybe, but 00:02:49.289 --> 00:02:51.289 respected for doing its specific thing really 00:02:51.289 --> 00:02:55.150 well. Polished, reliable in its niche. So let's 00:02:55.150 --> 00:02:57.430 boil it down. For someone listening, what's the 00:02:57.430 --> 00:03:00.030 core difference? Chatbot versus AI agent, plain 00:03:00.030 --> 00:03:03.090 English. Basically, a chatbot follows specific 00:03:03.090 --> 00:03:06.449 orders. An AI agent plans and manages complex, 00:03:06.569 --> 00:03:08.889 multi -step projects to reach a bigger goal. 00:03:09.419 --> 00:03:12.860 more autonomy. Okay. So to see who's really ready 00:03:12.860 --> 00:03:15.580 for actual work, we ran them through identical 00:03:15.580 --> 00:03:18.699 business tests, real world stuff. We looked at 00:03:18.699 --> 00:03:22.020 speed, reliability, and the quality of what they 00:03:22.020 --> 00:03:24.620 produced. First mission. Yeah. The AI stock market 00:03:24.620 --> 00:03:27.879 analyst. We asked them both to generate 100 reports 00:03:27.879 --> 00:03:31.060 on top cryptocurrencies, comparing their year 00:03:31.060 --> 00:03:33.159 -to -date returns to Bitcoin's average over the 00:03:33.159 --> 00:03:35.620 last decade. Pretty hefty task. Yeah, definitely. 00:03:35.819 --> 00:03:38.659 Chat GPT agent. It worked for about 45 minutes. 00:03:39.129 --> 00:03:40.870 Which was pretty long for an AI tool, right? 00:03:40.909 --> 00:03:43.430 Yeah. And the result, well, it gave us some basic 00:03:43.430 --> 00:03:45.830 slides, very minimal info. And it just completely 00:03:45.830 --> 00:03:47.990 ignored the request for 100 reports, didn't do 00:03:47.990 --> 00:03:50.310 the deep analysis either. Honestly, barely usable, 00:03:50.430 --> 00:03:52.780 just missed the whole point. Okay. And Genspark 00:03:52.780 --> 00:03:55.379 AI, we tested it on similar things like analyzing 00:03:55.379 --> 00:03:58.180 100 domains at once. It consistently handled 00:03:58.180 --> 00:04:00.099 that high volume. The reports were generally 00:04:00.099 --> 00:04:03.159 way more comprehensive, more detailed. And crucially, 00:04:03.280 --> 00:04:05.500 it actually gave us the quantity we asked for. 00:04:05.620 --> 00:04:08.020 It delivered on the scale. So test one winner, 00:04:08.139 --> 00:04:11.879 pretty clear. Genspark AI chat GPT just wasn't 00:04:11.879 --> 00:04:14.460 reliable. Failing to follow that core instruction 00:04:14.460 --> 00:04:16.500 about quantity was a big problem. All right, 00:04:16.519 --> 00:04:20.480 next up. The Code Monkey Challenge, or maybe 00:04:20.480 --> 00:04:22.699 Automated Code Review Challenge sounds better. 00:04:22.860 --> 00:04:25.079 Yeah, let's go with that. The mission. Look through 00:04:25.079 --> 00:04:28.959 35 PHP files, find any hard -coded API keys, 00:04:29.240 --> 00:04:33.019 and replace them with a secure URL proxy. Standard 00:04:33.019 --> 00:04:37.150 dev task, but tedious. Okay, so chat GPT. It 00:04:37.150 --> 00:04:39.329 immediately hit this really frustrating limit. 00:04:39.470 --> 00:04:41.949 It can only process 10 files at a time. Hard 00:04:41.949 --> 00:04:44.589 -coded limit. Only 10. So for 35 files. You got 00:04:44.589 --> 00:04:47.209 to do it in batches manually. Yeah. Which totally 00:04:47.209 --> 00:04:48.930 defeats the point of automating it. You might 00:04:48.930 --> 00:04:50.550 as well just do it by hand at that point. Wow. 00:04:50.629 --> 00:04:52.910 And did it even work within those batches? That's 00:04:52.910 --> 00:04:55.550 the kicker. Even in a small batch of 10, it struggled. 00:04:55.829 --> 00:04:59.810 Only got four out of the 10 files right. So slow, 00:04:59.990 --> 00:05:03.689 inefficient. Just a clear failure for that mission. 00:05:04.319 --> 00:05:06.079 I got to say, I still wrestle with prompt drift 00:05:06.079 --> 00:05:08.420 myself sometimes, remembering these quirks. You 00:05:08.420 --> 00:05:12.100 think you've explained it perfectly, but it's 00:05:12.100 --> 00:05:15.120 tough. Yeah, I get that. So what about Genspark 00:05:15.120 --> 00:05:18.439 AI on the code challenge? Well, Genspark hit 00:05:18.439 --> 00:05:20.959 a wall immediately, just flat out said. File 00:05:20.959 --> 00:05:24.139 type is not supported for PHP. Couldn't even 00:05:24.139 --> 00:05:27.620 start. Soft chuckle. So yeah, advanced tool, 00:05:27.720 --> 00:05:30.879 simple problem sometimes. So test two was, well, 00:05:30.980 --> 00:05:33.459 a draw. Or maybe a double failure is more accurate. 00:05:33.600 --> 00:05:36.160 Yeah, fascinating failure. ChatGPT failed on 00:05:36.160 --> 00:05:38.120 scale and competence. Couldn't handle the volume, 00:05:38.259 --> 00:05:40.360 messed up the task. Genspark failed on compatibility. 00:05:40.819 --> 00:05:42.699 Didn't have the right tool for the job. It's 00:05:42.699 --> 00:05:44.300 like one couldn't carry enough boxes and the 00:05:44.300 --> 00:05:46.019 other didn't have the right forklift. Exactly. 00:05:46.220 --> 00:05:48.740 Okay, test three. The content enhancement specialist. 00:05:49.000 --> 00:05:52.410 Goal. Take 20 articles, add Johnson boxes, and 00:05:52.410 --> 00:05:54.829 reformat data into tables. Johnson boxes, for 00:05:54.829 --> 00:05:56.029 anyone listening, that's like a call -out box 00:05:56.029 --> 00:05:58.089 in an article, right? Highlights key info. Yep, 00:05:58.149 --> 00:06:00.930 exactly. Common in marketing content. So, chat 00:06:00.930 --> 00:06:03.829 GPT. Same story. Hit the 10 -file limit again. 00:06:03.949 --> 00:06:06.209 Had to do two batches for the 20 articles. It 00:06:06.209 --> 00:06:08.790 was slow, but, you know, it did eventually finish 00:06:08.790 --> 00:06:10.870 the task. It got there. Shove Ganspark. Ganspark 00:06:10.870 --> 00:06:13.449 handled all 20 at once, no problem. But what 00:06:13.449 --> 00:06:15.949 was really impressive was its approach. It didn't 00:06:15.949 --> 00:06:19.509 just, like... blindly add boxes, it first figured 00:06:19.509 --> 00:06:22.370 out a template for the Johnson box. Oh, okay. 00:06:22.389 --> 00:06:25.290 And then applied that template consistently across 00:06:25.290 --> 00:06:28.670 all 20 articles. Much smarter, faster, more consistent 00:06:28.670 --> 00:06:30.949 output because of it. Okay. So winner of test 00:06:30.949 --> 00:06:33.689 three, content enhancement specialist. Definitely 00:06:33.689 --> 00:06:37.829 Ginsburg, AI, speed, scalability, and that intelligent 00:06:37.829 --> 00:06:40.389 sort of template -based approach really made 00:06:40.389 --> 00:06:42.829 it stand out. Final test. Yeah. The image manipulation 00:06:42.829 --> 00:06:45.509 artist. We gave them 10 Pinterest -style images 00:06:45.509 --> 00:06:47.449 and asked them to... create a presentation sort 00:06:47.449 --> 00:06:49.610 of vague wanted to see what they'd do right chat 00:06:49.610 --> 00:06:52.290 gpt complete failure just totally misunderstood 00:06:52.290 --> 00:06:54.629 ignored the images we gave it seriously yeah 00:06:54.629 --> 00:06:57.509 just created one single completely unrelated 00:06:57.509 --> 00:07:00.670 new image it was bizarre wow okay in gansburg 00:07:00.970 --> 00:07:03.230 Ganspark also really struggled with modifying 00:07:03.230 --> 00:07:05.170 existing images. It seems like that's a common 00:07:05.170 --> 00:07:07.410 thing right now with these models. They're great 00:07:07.410 --> 00:07:10.889 at generating new images from text, but actually 00:07:10.889 --> 00:07:13.449 manipulating existing ones like a graphic designer 00:07:13.449 --> 00:07:15.589 would in Photoshop. That seems to be a current 00:07:15.589 --> 00:07:19.230 limitation, a real blind spot. So test four winner, 00:07:19.410 --> 00:07:23.329 neither, showed a clear weakness for both in 00:07:23.329 --> 00:07:25.870 that kind of direct image work. So thinking back 00:07:25.870 --> 00:07:28.269 across all those tests, what felt like the biggest 00:07:28.269 --> 00:07:30.610 consistent roadblock, what kept tripping them 00:07:30.610 --> 00:07:33.870 up? You know, it really came back to those arbitrary 00:07:33.870 --> 00:07:37.170 file limits, like the 10 -file thing with ChatGPT, 00:07:37.269 --> 00:07:39.930 and then specific compatibility issues, like 00:07:39.930 --> 00:07:43.189 Nspark not handling PHP. Those technical hurdles 00:07:43.189 --> 00:07:45.889 often stopped progress more than anything else 00:07:45.889 --> 00:07:47.750 in the real world. So after all these tests, 00:07:47.870 --> 00:07:49.769 what's the takeaway? It really feels like that 00:07:49.769 --> 00:07:51.629 classic story, doesn't it? Yeah. The flashy show 00:07:51.629 --> 00:07:55.250 pony versus the reliable workhorse. That's a 00:07:55.250 --> 00:07:57.589 perfect analogy. Chet TPT agent mode feels exactly 00:07:57.589 --> 00:07:59.810 like a concept car right now. Big brand, slick 00:07:59.810 --> 00:08:01.930 look, amazing demos. But then you take it out 00:08:01.930 --> 00:08:05.009 for a real drive. Execution is slow. It's less 00:08:05.009 --> 00:08:07.910 reliable than you'd hope. And it often kind of 00:08:07.910 --> 00:08:10.129 misses the point on complex instructions. And 00:08:10.129 --> 00:08:12.740 that 10 file limit. We keep coming back to it, 00:08:12.800 --> 00:08:15.120 but it's honestly a deal breaker for serious 00:08:15.120 --> 00:08:18.579 work. Imagine trying to analyze a month's worth 00:08:18.579 --> 00:08:21.060 of customer feedback emails, hundreds, maybe 00:08:21.060 --> 00:08:24.240 thousands. That limit means hours of manual batching. 00:08:24.259 --> 00:08:26.600 It just kills the whole automation idea. It really 00:08:26.600 --> 00:08:29.300 feels like a public beta. Maybe rushed out, not 00:08:29.300 --> 00:08:31.620 quite ready for prime time at scale. Begin Spark 00:08:31.620 --> 00:08:36.049 AI. That feels like the Toyota Hilux. of AI agents, 00:08:36.190 --> 00:08:39.129 you know, not flashy, maybe, but built for heavy 00:08:39.129 --> 00:08:41.529 duty, real world work. It just gets the job done 00:08:41.529 --> 00:08:44.070 reliably. And it's way faster. Yeah. Often finishing 00:08:44.070 --> 00:08:47.169 tasks in minutes where chat GPT took like almost 00:08:47.169 --> 00:08:49.190 an hour. Right. And here's the really mind blowing 00:08:49.190 --> 00:08:52.129 part. Genspark has almost no arbitrary file limits. 00:08:52.269 --> 00:08:54.889 It can process hundreds, maybe thousands of documents 00:08:54.889 --> 00:08:58.450 in one go. Yeah. Whoa. I mean, just imagine scaling 00:08:58.450 --> 00:09:01.429 that, analyzing hundreds of contracts or thousands 00:09:01.429 --> 00:09:04.279 of research papers effortlessly. That's serious 00:09:04.279 --> 00:09:08.240 power, real leverage. And it was just way more 00:09:08.240 --> 00:09:10.799 reliable in the tests. Showed a smarter approach 00:09:10.799 --> 00:09:12.740 on things like the content enhancement. It feels 00:09:12.740 --> 00:09:16.139 mature, professional grade. So our verdict, it's 00:09:16.139 --> 00:09:17.559 pretty unanimous, actually, if you're looking 00:09:17.559 --> 00:09:20.759 for a serious AI agent platform now. And yeah, 00:09:20.799 --> 00:09:23.279 they can cause maybe $200 a month for real capability. 00:09:24.440 --> 00:09:28.860 The clear winner for actual work is Genspark 00:09:28.860 --> 00:09:32.789 AI, ChatGPT's agent. right now it's more like 00:09:32.789 --> 00:09:35.070 a high -priced toy for enthusiasts gen spark 00:09:35.070 --> 00:09:37.610 is a tool for people building things which brings 00:09:37.610 --> 00:09:40.470 us to okay what makes a good ai agent then based 00:09:40.470 --> 00:09:42.289 on these tests we kind of landed on five key 00:09:42.289 --> 00:09:45.289 things one reliability and focus it has to do 00:09:45.289 --> 00:09:48.750 what you ask consistently no weird detours two 00:09:48.750 --> 00:09:52.070 a congruent thinking process it needs to apply 00:09:52.070 --> 00:09:54.929 logic consistently across steps build on its 00:09:54.929 --> 00:09:57.029 work yeah not just start fresh every time three 00:09:57.399 --> 00:09:59.840 True scalability. No silly file limits. Handle 00:09:59.840 --> 00:10:02.679 hundreds of thousands of files. Four, real programming 00:10:02.679 --> 00:10:04.580 chops. If it's working with code, can it actually 00:10:04.580 --> 00:10:07.159 understand and modify it properly? Yeah, securely 00:10:07.159 --> 00:10:10.480 too. Right. And five, speed and efficiency times 00:10:10.480 --> 00:10:12.860 money, right? Minutes versus an hour. That's 00:10:12.860 --> 00:10:14.539 a massive difference in what you can get done. 00:10:14.740 --> 00:10:18.059 So if we define good for an AI agent based on 00:10:18.059 --> 00:10:20.360 what we saw in these tests. It really comes down 00:10:20.360 --> 00:10:23.759 to reliability. That consistent. Logic and genuine 00:10:23.759 --> 00:10:27.059 scalability for handling real world volumes of 00:10:27.059 --> 00:10:29.440 work. Yeah. Okay. But before everyone rushes 00:10:29.440 --> 00:10:32.000 out and delegates their entire workload, we need 00:10:32.000 --> 00:10:35.820 some real talk about managing these AI interns. 00:10:36.159 --> 00:10:37.759 Yeah. Interns is a good word for it. They're 00:10:37.759 --> 00:10:40.330 super fast, super eager. But they need really 00:10:40.330 --> 00:10:42.610 clear instructions and close supervision. You 00:10:42.610 --> 00:10:44.190 wouldn't just hand the keys to an intern without 00:10:44.190 --> 00:10:46.169 checking in. Exactly. And that hallucination 00:10:46.169 --> 00:10:49.210 problem, it gets amplified massively. Like one 00:10:49.210 --> 00:10:52.870 wrong fact from a chat bot is annoying. But an 00:10:52.870 --> 00:10:56.029 agent making that same mistake across 100 reports 00:10:56.029 --> 00:10:59.309 or 100 files, suddenly you have a huge systemic 00:10:59.309 --> 00:11:02.029 mess. So oversight is absolutely non -negotiable. 00:11:02.110 --> 00:11:04.549 You cannot set it and forget it, period. You 00:11:04.549 --> 00:11:06.789 have to check their work, validate it, especially 00:11:06.789 --> 00:11:10.090 for anything important. Trust? But verify. That's 00:11:10.090 --> 00:11:12.610 the mantra. Definitely. And also remember, agent 00:11:12.610 --> 00:11:14.970 work is often slower than chatbots. A complex 00:11:14.970 --> 00:11:17.470 task might take 30 minutes, maybe several hours. 00:11:17.529 --> 00:11:19.070 So you got to plan for that. It's not instant. 00:11:19.289 --> 00:11:21.750 And yeah, that idea of the $20 ,000 agent that 00:11:21.750 --> 00:11:24.549 just replaces a human entirely. Runs your business 00:11:24.549 --> 00:11:27.009 while you're on the beach. Chuckles. Still science 00:11:27.009 --> 00:11:30.149 fiction. Pretty much. These are powerful assistants, 00:11:30.529 --> 00:11:33.110 not autonomous replacements for your brain. Even 00:11:33.110 --> 00:11:35.190 with all that, they can seriously help you make 00:11:35.190 --> 00:11:39.799 money. Or save time, which is money. Like research 00:11:39.799 --> 00:11:42.559 and competitive analysis. An agent can scrape 00:11:42.559 --> 00:11:44.960 20 competitor sites, pull out their value props, 00:11:45.200 --> 00:11:48.879 pricing, compile a report way faster than a human. 00:11:49.000 --> 00:11:51.120 Or financial analysis. Give it an earnings report. 00:11:51.360 --> 00:11:53.879 Ask for summaries, trends, create charts. That's 00:11:53.879 --> 00:11:56.460 like junior investment banker level work done 00:11:56.460 --> 00:11:58.419 in minutes. As I'm an executive assistant too. 00:11:58.840 --> 00:12:01.879 Rewriting 50 articles into an e -book. Organizing 00:12:01.879 --> 00:12:04.220 schedules, summarizing tons of emails. Agents 00:12:04.220 --> 00:12:06.659 can do that. Sales and lead qualification. Yeah. 00:12:06.879 --> 00:12:09.200 An agent could research a new lead, check their 00:12:09.200 --> 00:12:11.240 website, see if they're a good fit based on their 00:12:11.240 --> 00:12:13.159 inquiry, maybe even handle the first couple of 00:12:13.159 --> 00:12:15.519 messages. Yeah, qualifying them before a human 00:12:15.519 --> 00:12:18.000 steps in and coding and development. This one's 00:12:18.000 --> 00:12:20.879 huge. Systematic changes across hundreds of files, 00:12:21.039 --> 00:12:23.820 fixing bugs, converting languages, even implementing 00:12:23.820 --> 00:12:27.100 basic features that could slash development time 00:12:27.100 --> 00:12:30.159 months down to days potentially. That's transformative. 00:12:30.539 --> 00:12:32.580 So with all these possibilities, but keeping 00:12:32.580 --> 00:12:35.080 in mind the need for oversight. Yeah. What's 00:12:35.080 --> 00:12:37.620 the single most crucial mindset for working well 00:12:37.620 --> 00:12:40.620 with these agents? You absolutely have to treat 00:12:40.620 --> 00:12:44.399 them like extremely powerful, but junior. interns, 00:12:44.399 --> 00:12:47.159 clear instructions, constant oversight. That's 00:12:47.159 --> 00:12:48.919 how you get the value. Mid -roll break, sponsor 00:12:48.919 --> 00:12:50.860 read would typically go here. Okay, so the big 00:12:50.860 --> 00:12:53.000 idea from this deep dive seems pretty clear. 00:12:53.360 --> 00:12:57.240 AI agents, incredibly powerful tools, truly. 00:12:57.600 --> 00:13:00.100 But they are tools. They're not magic money machines 00:13:00.100 --> 00:13:02.159 operating on their own. Yeah, our tests really 00:13:02.159 --> 00:13:04.879 showed Genspark AI is the workhorse right now. 00:13:05.000 --> 00:13:08.250 It excels at scale, reliability. It's ready for 00:13:08.250 --> 00:13:11.210 serious business use. Chat GPT agents. Fascinating 00:13:11.210 --> 00:13:13.509 potential, no doubt, but still feels like a public 00:13:13.509 --> 00:13:15.750 beta. That 10 -file limit is just a major hurdle 00:13:15.750 --> 00:13:18.830 for any real scale. And ultimately, success isn't 00:13:18.830 --> 00:13:20.929 just about picking the right tool. It's about 00:13:20.929 --> 00:13:23.809 your strategy, how you manage them. Like those 00:13:23.809 --> 00:13:27.129 super effective but still supervised interns, 00:13:27.509 --> 00:13:31.269 it's about your direction. So is the investment 00:13:31.269 --> 00:13:33.990 worth it? for businesses dealing with lots of 00:13:33.990 --> 00:13:37.429 content or code or research. Yeah, Genspark AI 00:13:37.429 --> 00:13:41.570 offers potentially huge ROI. if you use it strategically. 00:13:41.809 --> 00:13:44.929 But remember that key rule. No AI agent just 00:13:44.929 --> 00:13:47.690 magically makes you money out of thin air. They 00:13:47.690 --> 00:13:50.409 amplify an existing solid business strategy. 00:13:50.610 --> 00:13:52.970 They make what you're already doing more effective, 00:13:53.090 --> 00:13:54.990 faster. The people who are really going to win 00:13:54.990 --> 00:13:56.710 with these tools, they're the ones with a clear 00:13:56.710 --> 00:13:58.929 plan already. They know their bottlenecks. They 00:13:58.929 --> 00:14:00.950 give crystal clear instructions. They maintain 00:14:00.950 --> 00:14:03.070 that human oversight. Right. And then they use 00:14:03.070 --> 00:14:05.350 the time saved to focus on the high -level strategic 00:14:05.350 --> 00:14:08.220 stuff that, frankly... only a human can do. So 00:14:08.220 --> 00:14:09.759 maybe take a minute and think about your own 00:14:09.759 --> 00:14:12.519 business. Where are those bottlenecks? What repetitive, 00:14:12.620 --> 00:14:14.759 scalable tasks are just eating up your time? 00:14:14.940 --> 00:14:17.679 Could a powerful AI agent under your clear direction 00:14:17.679 --> 00:14:20.379 be the digital leverage you need? Out to your 00:14:20.379 --> 00:14:20.799 own music.