WEBVTT 00:00:00.000 --> 00:00:03.779 The digital world, it moves so fast. AI isn't 00:00:03.779 --> 00:00:05.839 some far -off idea anymore, is it? It's here. 00:00:05.900 --> 00:00:08.519 It's a daily tool. And this keeps evolving at 00:00:08.519 --> 00:00:11.119 this, well, incredible pace. I honestly feel 00:00:11.119 --> 00:00:14.080 like digital vertigo sometimes, just caught in 00:00:14.080 --> 00:00:17.339 this constant whirlwind of new tools, new systems. 00:00:17.980 --> 00:00:20.359 But you don't need to be a tech wizard to actually 00:00:20.359 --> 00:00:23.480 grasp this power. You just need maybe a guide, 00:00:24.000 --> 00:00:26.559 something to cut through all that noise. Welcome 00:00:26.559 --> 00:00:29.399 to the deep dive. Today, our mission is all about 00:00:29.399 --> 00:00:31.800 navigating this AI revolution. We've looked at 00:00:31.800 --> 00:00:34.159 sources that give us a pretty clear roadmap to, 00:00:34.159 --> 00:00:36.740 well, mastery, hopefully demystifying this whole 00:00:36.740 --> 00:00:40.719 landscape. mental roadblocks, then we'll help 00:00:40.719 --> 00:00:43.119 you figure out your unique AI persona. We'll 00:00:43.119 --> 00:00:45.060 define some key concepts, the anchors really, 00:00:45.460 --> 00:00:47.640 explore essential tools, master those evergreen 00:00:47.640 --> 00:00:49.740 skills, and yeah, even to touch on the future 00:00:49.740 --> 00:00:52.119 with AI agents. Yeah, it's totally about moving 00:00:52.119 --> 00:00:54.159 from feeling kind of lost to feeling genuinely 00:00:54.159 --> 00:00:56.500 empowered, right? Like finding the best hiking 00:00:56.500 --> 00:00:58.320 trail for your skill level instead of just, you 00:00:58.320 --> 00:01:00.039 know, wandering off into the wilderness without 00:01:00.039 --> 00:01:03.200 a map. OK, let's unpack this then. It sounds 00:01:03.200 --> 00:01:05.980 like a lot of us are feeling, well, maybe intimidated 00:01:05.980 --> 00:01:09.659 by AI. Where did these psychological walls even 00:01:09.659 --> 00:01:11.620 come from? And how do we start taking them down? 00:01:11.939 --> 00:01:14.219 Well, our sources point to about five really 00:01:14.219 --> 00:01:16.719 common barriers. The first one is just that thought, 00:01:16.719 --> 00:01:19.400 I'm not a technical person. But the thing with 00:01:19.400 --> 00:01:21.840 generative AI, it's actually built to be accessible. 00:01:22.060 --> 00:01:24.659 Your own language, the way you talk or write, 00:01:24.739 --> 00:01:27.260 that's the interface. If you can ask a question, 00:01:27.739 --> 00:01:29.500 give an instruction, you've got the core skill. 00:01:29.980 --> 00:01:33.640 No coding needed. Curiosity, honestly, that's 00:01:33.640 --> 00:01:35.900 the real key. OK, so it's less about technical 00:01:35.900 --> 00:01:37.560 background and more about just being willing 00:01:37.560 --> 00:01:40.299 to ask. Exactly. Then the second barrier. You 00:01:40.299 --> 00:01:42.239 hear this a lot. It's all changing too fast. 00:01:42.719 --> 00:01:44.599 And yeah, OK, the surface level is buzzing. New 00:01:44.599 --> 00:01:46.700 models, constant updates. That's like the model 00:01:46.700 --> 00:01:49.620 arms race. But for most people, it's mostly noise. 00:01:49.799 --> 00:01:51.359 Think about it like driving a car. New models 00:01:51.359 --> 00:01:53.879 come out every year, right? Fancy features. But 00:01:53.879 --> 00:01:56.959 the core skills, steering, accelerating, braking. 00:01:57.500 --> 00:02:00.719 they stay the same. Learning one LLM well, it 00:02:00.719 --> 00:02:02.579 really helps you understand others. You gotta 00:02:02.579 --> 00:02:04.879 focus on those underlying principles, not the 00:02:04.879 --> 00:02:08.360 shiny new object. Ah, the car analogy. That actually 00:02:08.360 --> 00:02:10.900 helps a lot. So focus on the driving, not just 00:02:10.900 --> 00:02:13.280 the latest dashboard. Precisely. Then there's, 00:02:13.360 --> 00:02:15.759 oh my gosh, there are thousands of tools. And 00:02:15.759 --> 00:02:17.539 yeah, it looks that way. But this is where the 00:02:17.539 --> 00:02:20.060 80 -20 rule is your best friend. You probably 00:02:20.060 --> 00:02:23.520 only need to focus on maybe five to seven foundational 00:02:23.520 --> 00:02:26.219 tools. So many of the others are just wrappers. 00:02:26.479 --> 00:02:28.520 They're like specialized interfaces built on 00:02:28.520 --> 00:02:30.960 top of the big models for very specific tasks. 00:02:31.539 --> 00:02:33.819 Understanding that, it cuts through so much clutter. 00:02:34.080 --> 00:02:36.560 OK, that's reassuring. Five to seven sounds manageable. 00:02:37.039 --> 00:02:40.000 Right. Then, next up. I can't possibly keep up 00:02:40.000 --> 00:02:42.780 with all the AI news and developments. And, honestly, 00:02:43.379 --> 00:02:45.280 you shouldn't even try. Trying to drink from 00:02:45.280 --> 00:02:47.460 that fire hose is just a recipe for burnout. 00:02:48.159 --> 00:02:50.159 Your goal isn't to become an encyclopedia of 00:02:50.159 --> 00:02:52.280 AI. It's to be a practitioner, someone who uses 00:02:52.280 --> 00:02:55.039 it, curated newsletters. They're gold. Let someone 00:02:55.039 --> 00:02:56.759 else sift through the noise so you can focus 00:02:56.759 --> 00:02:59.020 on how to actually apply this stuff. Oh, filtered 00:02:59.020 --> 00:03:02.039 information, not the fire hose. Got it. And the 00:03:02.039 --> 00:03:04.979 last one. I'm worried about the ethical implications. 00:03:05.300 --> 00:03:07.439 This one's important, but it shouldn't be a barrier 00:03:07.439 --> 00:03:09.800 to starting. Think of it more as a principle 00:03:09.800 --> 00:03:12.800 to weave into your learning from day one. Being 00:03:12.800 --> 00:03:15.500 informed means understanding the limits, things 00:03:15.500 --> 00:03:17.699 like hallucinations when the AI just kind of 00:03:17.699 --> 00:03:19.919 makes stuff up. It means critically checking 00:03:19.919 --> 00:03:22.879 the outputs. Using AI responsibly actually makes 00:03:22.879 --> 00:03:25.699 you part of the solution, not part of the problem. 00:03:25.939 --> 00:03:27.840 So looking at all those barriers, what's the 00:03:27.840 --> 00:03:30.379 single most important mindset shift we really 00:03:30.379 --> 00:03:33.400 need to make here? AI mastery starts with curiosity, 00:03:33.740 --> 00:03:36.939 not coding. Principles, not fleeting news. OK, 00:03:36.979 --> 00:03:38.979 we've cleared some of those mental hurdles. So 00:03:38.979 --> 00:03:41.620 the next logical step is, where do we actually 00:03:41.620 --> 00:03:44.180 start? It sounds like why we want to learn AI 00:03:44.180 --> 00:03:47.300 shapes the path we take. It absolutely does. 00:03:47.800 --> 00:03:50.460 Our sources talk about three main learning personas. 00:03:50.919 --> 00:03:52.840 And you'll probably find yourself moving between 00:03:52.840 --> 00:03:55.379 them over time, which is totally normal. First 00:03:55.379 --> 00:03:57.960 up is the everyday explorer. Your motivation 00:03:57.960 --> 00:04:01.080 here. It's pretty simple. Save time, make life 00:04:01.080 --> 00:04:03.340 a little easier, maybe boost your personal productivity 00:04:03.340 --> 00:04:06.180 or creativity. Your mindset is basically, how 00:04:06.180 --> 00:04:09.000 can AI help me out with my daily stuff? So maybe 00:04:09.000 --> 00:04:11.400 it's summarizing that super long email or brainstorming 00:04:11.400 --> 00:04:14.020 ideas for a project, or even figuring out what 00:04:14.020 --> 00:04:15.840 to cook based on what's actually in your fridge. 00:04:16.399 --> 00:04:19.060 Your main tool here is likely one of the big 00:04:19.060 --> 00:04:22.279 LLMs, chat, GPT, Gemini, Claude, something like 00:04:22.279 --> 00:04:24.939 that. OK. That feels like a very accessible starting 00:04:24.939 --> 00:04:27.620 point, just making everyday tasks smoother. Yeah, 00:04:27.620 --> 00:04:30.600 exactly. Then you might evolve into the power 00:04:30.600 --> 00:04:33.120 user. Their motivation is different. It's about 00:04:33.120 --> 00:04:35.279 seriously amplifying their professional work, 00:04:35.740 --> 00:04:38.899 creating higher quality stuff faster. and, importantly, 00:04:39.220 --> 00:04:42.000 integrating multiple AI tools together. Their 00:04:42.000 --> 00:04:44.319 mindset is more like, how can I combine these 00:04:44.319 --> 00:04:46.300 different AI tools to get results I couldn't 00:04:46.300 --> 00:04:49.519 possibly achieve alone? Think of, say, a freelance 00:04:49.519 --> 00:04:51.759 content creator. They might use Perplexity for 00:04:51.759 --> 00:04:54.300 deep research, then draft with Claude, generate 00:04:54.300 --> 00:04:56.399 stunning images with Mid -Journey, maybe even 00:04:56.399 --> 00:04:58.079 create voiceovers with 11 Labs. They're like 00:04:58.079 --> 00:05:00.379 a conductor, you know, orchestrating all these 00:05:00.379 --> 00:05:02.860 specialized tools. That's a definite step up. 00:05:03.100 --> 00:05:04.959 It sounds like it requires more strategic thinking 00:05:04.959 --> 00:05:07.519 about which tool does what best. It does, yeah. 00:05:07.660 --> 00:05:10.420 It's about building a workflow. And that leads 00:05:10.420 --> 00:05:12.740 naturally to the third persona, the builder. 00:05:13.360 --> 00:05:15.379 Their drive is bigger picture. They want to solve 00:05:15.379 --> 00:05:17.860 systemic problems, create totally new capabilities, 00:05:18.399 --> 00:05:21.300 maybe automate really complex processes using 00:05:21.300 --> 00:05:24.720 custom tools or even AI agents. Their mindset 00:05:24.720 --> 00:05:27.259 is, how can I build something where AI works 00:05:27.259 --> 00:05:29.379 for me, even when I'm not actively directing 00:05:29.379 --> 00:05:31.829 it? This could be a small business owner maybe 00:05:31.829 --> 00:05:34.050 building a custom chat bot for customer service 00:05:34.050 --> 00:05:36.910 using something like N8n, or a developer using 00:05:36.910 --> 00:05:39.610 an AI coding assistant like Cursor to build apps 00:05:39.610 --> 00:05:42.610 faster. They're creating systems that can run 00:05:42.610 --> 00:05:44.949 more autonomously. So for someone just dipping 00:05:44.949 --> 00:05:47.230 their toes in, which persona makes the most sense 00:05:47.230 --> 00:05:50.089 to aim for first? Definitely start as an explorer. 00:05:50.410 --> 00:05:53.129 Focus on daily tasks to build that foundational 00:05:53.129 --> 00:05:56.350 AI comfort. Right. Amidst all this chatter about 00:05:56.350 --> 00:05:58.790 new tools constantly popping up, what are the 00:05:58.790 --> 00:06:01.009 things that actually stay the same? What are 00:06:01.009 --> 00:06:03.069 the bedrock principles we really need to get 00:06:03.069 --> 00:06:05.410 our heads around? Great question. We need a shared 00:06:05.410 --> 00:06:07.689 language, but it's not just about memorizing 00:06:07.689 --> 00:06:09.730 definitions. It's about understanding what these 00:06:09.730 --> 00:06:13.529 concepts do in practice. So artificial intelligence, 00:06:13.850 --> 00:06:16.850 AI, Broadly, it's software that simulates human 00:06:16.850 --> 00:06:18.949 intelligence. Think of it as a whole big field. 00:06:19.189 --> 00:06:22.290 Machine learning, ML. This is a part of AI where 00:06:22.290 --> 00:06:24.810 the software learns patterns from data to make 00:06:24.810 --> 00:06:27.310 predictions or decisions. It gets smarter over 00:06:27.310 --> 00:06:29.550 time without explicit programming for every single 00:06:29.550 --> 00:06:32.089 thing. Okay, so AI is the goal, ML is one way 00:06:32.089 --> 00:06:33.949 it learns. Pretty much. Then you have deep learning 00:06:33.949 --> 00:06:36.350 and neural networks. This is a type of ML kind 00:06:36.350 --> 00:06:38.250 of inspired by how the human brain is structured. 00:06:38.610 --> 00:06:41.269 It uses layers to find really complex patterns. 00:06:41.750 --> 00:06:43.509 This is what's behind a lot of the breakthroughs 00:06:43.509 --> 00:06:46.410 like recognizing images or understanding speech, 00:06:47.029 --> 00:06:49.290 generative AI. This is the type of AI that actually 00:06:49.290 --> 00:06:51.790 creates new stuff. Text, images, music, code, 00:06:51.990 --> 00:06:54.009 stuff that feels original. That's the buzz right 00:06:54.009 --> 00:06:56.970 now. LLMs, large language models. These are the 00:06:56.970 --> 00:06:59.209 engines behind a lot of generative AI you interact 00:06:59.209 --> 00:07:01.709 with. They work by predicting the next most likely 00:07:01.709 --> 00:07:03.670 word, which lets them generate text that sounds 00:07:03.670 --> 00:07:07.589 remarkably human. Think chat GPT, Claude, Gemini. 00:07:07.829 --> 00:07:10.050 Got it. And the instructions we give them. That's 00:07:10.050 --> 00:07:12.689 your prompt. Simply put, it's the specific instruction 00:07:12.689 --> 00:07:15.889 or question you give to the AI. Mastering prompts 00:07:15.889 --> 00:07:19.629 is key. Then there's hallucination. This is crucial. 00:07:19.910 --> 00:07:22.610 It's when the AI generates information that sounds 00:07:22.610 --> 00:07:25.649 plausible, maybe even confident, but it's actually 00:07:25.649 --> 00:07:28.569 false or nonsensical. It just makes things up 00:07:28.569 --> 00:07:30.569 sometimes. Ah, so it's not always telling the 00:07:30.569 --> 00:07:32.529 truth, even if it sounds like it is. Exactly. 00:07:33.069 --> 00:07:36.259 Which brings us to... ARJ, Retrieval Augmented 00:07:36.259 --> 00:07:39.740 Generation. This is a technique to make AI more 00:07:39.740 --> 00:07:42.759 factual. It basically lets the AI check its answers 00:07:42.759 --> 00:07:45.240 against a set of trusted external documents or 00:07:45.240 --> 00:07:48.379 data before it responds. Helps reduce those hallucinations 00:07:48.379 --> 00:07:51.060 quite a bit. OK, so why is understanding hallucinations 00:07:51.060 --> 00:07:53.920 so fundamentally important for literally anyone 00:07:53.920 --> 00:07:56.560 using these tools? It reminds us to always verify 00:07:56.560 --> 00:07:59.360 AI output, especially for factual accuracy. Don't 00:07:59.360 --> 00:08:01.980 just trust blindly. OK, concepts down. Let's 00:08:01.980 --> 00:08:05.139 get practical now. The tools. With so many out 00:08:05.139 --> 00:08:06.839 there, which categories really matter? Which 00:08:06.839 --> 00:08:09.040 one should we focus on? Our sources give a great 00:08:09.040 --> 00:08:11.459 breakdown into five essential categories. First, 00:08:11.600 --> 00:08:14.220 obviously, the large -language models, LLMs. 00:08:14.480 --> 00:08:17.579 We mentioned ChatGPT, Gemini, Claude. Think of 00:08:17.579 --> 00:08:21.019 these as the Swiss army knives of AI. Super versatile, 00:08:21.199 --> 00:08:23.199 a great starting point. And they're getting better 00:08:23.199 --> 00:08:25.660 all the time, becoming multimodal, meaning they 00:08:25.660 --> 00:08:28.360 can understand not just text, but images, documents, 00:08:28.519 --> 00:08:30.959 sometimes even audio you upload. So your go -to 00:08:30.959 --> 00:08:33.460 generalist tool, what's next? Second category, 00:08:34.120 --> 00:08:36.519 AI -powered research and knowledge synthesis. 00:08:37.159 --> 00:08:40.100 are like giving your LLM a connection to the 00:08:40.100 --> 00:08:41.980 live internet or letting it become an expert 00:08:41.980 --> 00:08:44.840 in your specific documents. Your second brain, 00:08:45.179 --> 00:08:47.480 maybe. Perplexity is a fantastic example. It's 00:08:47.480 --> 00:08:49.559 like an answer engine. It searches the web in 00:08:49.559 --> 00:08:51.879 real time and gives you citations, which is amazing 00:08:51.879 --> 00:08:54.059 for fact -checking what an LLM tells you. And 00:08:54.059 --> 00:08:55.519 then there's Notebook LLM. This one's different. 00:08:55.559 --> 00:08:58.000 It becomes an expert on your private files. You 00:08:58.000 --> 00:09:00.120 upload your documents, notes, whatever, and it 00:09:00.120 --> 00:09:02.000 can summarize them, find connections, answer 00:09:02.000 --> 00:09:03.840 questions based only on your stuff. It's like 00:09:03.840 --> 00:09:07.230 a personal research assistant. Wow. OK. Proplexity 00:09:07.230 --> 00:09:09.990 for the web, notebook LM for my own stuff, that's 00:09:09.990 --> 00:09:13.710 useful. What about visuals? Third category, image 00:09:13.710 --> 00:09:16.610 generation. This has exploded, right? Moved way 00:09:16.610 --> 00:09:18.629 beyond just a novelty into a serious creative 00:09:18.629 --> 00:09:21.210 tool for professionals. Mid -Journey is still 00:09:21.210 --> 00:09:24.429 often seen as the leader for really artistic 00:09:24.429 --> 00:09:28.139 or photorealistic images. Ideogram is interesting 00:09:28.139 --> 00:09:29.899 because it's particularly good at generating 00:09:29.899 --> 00:09:32.320 images with text in them, like logos or posters. 00:09:32.700 --> 00:09:34.700 And DLE3, especially the version inside Chat 00:09:34.700 --> 00:09:37.320 GPT, is great because you can talk to it, refine 00:09:37.320 --> 00:09:39.399 the image conversationally, make the dog beer, 00:09:39.559 --> 00:09:41.259 change the background to a beach, that kind of 00:09:41.259 --> 00:09:43.340 thing. Right, the conversational aspect is powerful. 00:09:43.600 --> 00:09:46.259 And beyond static images. Yeah, fourth category, 00:09:46.340 --> 00:09:48.860 video and audio generation. This area is moving 00:09:48.860 --> 00:09:51.840 incredibly fast, probably the fastest. For video, 00:09:51.840 --> 00:09:54.779 you've got tools like Google's Veo Runway. They 00:09:54.779 --> 00:09:57.419 can generate short, pretty high -quality video 00:09:57.419 --> 00:09:59.919 clips just from a text description. It's still 00:09:59.919 --> 00:10:02.139 early days relatively, but improving rapidly. 00:10:02.580 --> 00:10:05.519 For audio, 11Labs is amazing for text -to -speech. 00:10:05.860 --> 00:10:08.139 Hyper -realistic voices, you can even clone your 00:10:08.139 --> 00:10:11.419 own voice ethically. And for music, tools like 00:10:11.419 --> 00:10:13.740 Suno and Udio, you type in a description, maybe 00:10:13.740 --> 00:10:16.399 some lyrics. and they generate a full song. Vocals, 00:10:16.600 --> 00:10:19.120 instruments, broadcast quality sometimes. It's 00:10:19.120 --> 00:10:22.159 two -second silence. Whoa. I mean, just imagine 00:10:22.159 --> 00:10:24.639 scaling that. One simple text prompt, and boom, 00:10:24.659 --> 00:10:26.340 you've got an entire original song. It's kind 00:10:26.340 --> 00:10:27.960 of mind -blowing what's becoming possible there. 00:10:28.080 --> 00:10:29.799 It really is. It opens up creative possibilities 00:10:29.799 --> 00:10:31.759 for so many people who maybe didn't have the 00:10:31.759 --> 00:10:34.320 traditional skills or resources before. Absolutely. 00:10:34.840 --> 00:10:37.360 And the fifth final category ties a lot of this 00:10:37.360 --> 00:10:40.580 together. Automation platforms. Think of these 00:10:40.580 --> 00:10:43.190 as the digital glue. They connect different AI 00:10:43.190 --> 00:10:45.330 tools to each other and also to all your other 00:10:45.330 --> 00:10:47.570 apps like email, spreadsheets, social media. 00:10:47.850 --> 00:10:49.750 They're really the bridge from being a power 00:10:49.750 --> 00:10:52.409 user, manually combining tools to becoming a 00:10:52.409 --> 00:10:55.830 builder, creating automated workflows. Zapier 00:10:55.830 --> 00:10:58.169 and Make are really user -friendly for connecting 00:10:58.169 --> 00:11:00.610 cloud apps, lots of pre -built connections. Then 00:11:00.610 --> 00:11:02.590 there's NAN, which is generally seen as more 00:11:02.590 --> 00:11:05.070 powerful, more flexible. It's great for building 00:11:05.070 --> 00:11:07.669 more complex workflows, and it's becoming a key 00:11:07.669 --> 00:11:09.710 platform for building those AI agents we mentioned 00:11:09.710 --> 00:11:12.990 earlier. Offers more customization. OK, five 00:11:12.990 --> 00:11:15.250 categories. If I were to pick just one single 00:11:15.250 --> 00:11:17.850 tool today, right now, where should I start to 00:11:17.850 --> 00:11:19.750 see the most immediate impact or get the most 00:11:19.750 --> 00:11:23.009 versatility? Begin with a primary LLM like ChatGPT, 00:11:23.110 --> 00:11:25.250 Gemini, or Claude for its broad versatility. 00:11:25.350 --> 00:11:28.090 Makes sense. Now, tools will inevitably change. 00:11:28.309 --> 00:11:30.710 New ones will pop up. Old ones will fade. But 00:11:30.710 --> 00:11:33.889 skills. Skills last. What are those essential, 00:11:34.129 --> 00:11:36.169 truly evergreen abilities we need to cultivate 00:11:36.169 --> 00:11:39.559 for AI mastery? Yeah, this is critical. Our sources 00:11:39.559 --> 00:11:42.720 highlight four core skills. The first, and arguably 00:11:42.720 --> 00:11:45.220 the most important, is advanced prompting, sometimes 00:11:45.220 --> 00:11:47.779 called the art of the ask. This skill is honestly 00:11:47.779 --> 00:11:50.159 the difference between getting a useless, generic 00:11:50.159 --> 00:11:52.740 response and getting something truly game -changing 00:11:52.740 --> 00:11:55.879 from an AI. It's about moving beyond simple questions 00:11:55.879 --> 00:11:58.820 to giving clear, structured instructions. A great 00:11:58.820 --> 00:12:01.679 way to do this is using a framework, like CoStar. 00:12:01.879 --> 00:12:03.580 Co -star. What does that stand for? It helps 00:12:03.580 --> 00:12:06.500 structure your prompt. C is for context. Tell 00:12:06.500 --> 00:12:09.019 the AI who it should be, who you are, and maybe 00:12:09.019 --> 00:12:11.779 who the audience for the responses. O is for 00:12:11.779 --> 00:12:14.500 objective. What exactly do you want the AI to 00:12:14.500 --> 00:12:17.259 do? Be specific. S is for style. What writing 00:12:17.259 --> 00:12:20.340 style should it use? Formal, witty, simple. T 00:12:20.340 --> 00:12:23.000 is for tone. What's the emotional feel? Empathetic. 00:12:23.120 --> 00:12:26.360 urgent, neutral. A is for audience. Who is this 00:12:26.360 --> 00:12:28.639 response intended for? A beginner, an expert, 00:12:28.879 --> 00:12:31.320 a child. R is for response format. How should 00:12:31.320 --> 00:12:33.639 the AI structure its output? Paragraphs, bullet 00:12:33.639 --> 00:12:36.559 points, a table, JSON code. OK. That's quite 00:12:36.559 --> 00:12:38.000 structured. Can you give us a quick concrete 00:12:38.000 --> 00:12:40.100 example of how that works? Sure. Let's use that 00:12:40.100 --> 00:12:42.419 retirement saving example. Instead of just asking, 00:12:42.779 --> 00:12:45.879 explain IRA versus Roth IRA, a costar prompt 00:12:45.879 --> 00:12:50.100 would be more like, C, you are an expert -friendly 00:12:50.100 --> 00:12:52.909 financial advisor. I am a 28 -year -old freelance 00:12:52.909 --> 00:12:55.269 graphic designer, totally new to retirement savings 00:12:55.269 --> 00:12:58.769 and feeling a bit overwhelmed. O. Your objective 00:12:58.769 --> 00:13:01.070 is to clearly explain the main difference between 00:13:01.070 --> 00:13:04.490 a traditional IRA and a Roth IRA for me. S. Use 00:13:04.490 --> 00:13:06.809 a simple, clear style, maybe include an analogy 00:13:06.809 --> 00:13:10.470 to make the core concept stick. T. Your tone 00:13:10.470 --> 00:13:13.009 should be encouraging and non -judgmental. A, 00:13:13.029 --> 00:13:15.350 I'm a complete beginner, so avoid complex jargon. 00:13:16.110 --> 00:13:18.009 R, please write about three short paragraphs, 00:13:18.110 --> 00:13:20.309 put the analogy in the second one, and end with 00:13:20.309 --> 00:13:22.269 bullet points summarizing the key takeaways for 00:13:22.269 --> 00:13:24.669 each account type. See the difference? That level 00:13:24.669 --> 00:13:26.870 of detail guides the AI much more effectively. 00:13:27.049 --> 00:13:29.230 Wow, yeah. That's much more specific. Way more 00:13:29.230 --> 00:13:31.330 likely to get a useful answer. Definitely. And 00:13:31.330 --> 00:13:33.960 honestly. I still wrestle with Chrome Drift myself 00:13:33.960 --> 00:13:36.179 sometimes, you know, where you start off clear 00:13:36.179 --> 00:13:38.919 and the AI conversation just wanders off track. 00:13:39.279 --> 00:13:41.539 That's exactly why frameworks like CoStar are 00:13:41.539 --> 00:13:44.639 so valuable. They help keep things focused. Okay, 00:13:44.940 --> 00:13:48.240 second skill, tool literacy and selection. This 00:13:48.240 --> 00:13:50.360 isn't about becoming an expert at every single 00:13:50.360 --> 00:13:52.580 tool out there. That's impossible. It's about 00:13:52.580 --> 00:13:55.559 knowing broadly what's possible with different 00:13:55.559 --> 00:13:58.179 types of AI tools and developing the intuition 00:13:58.179 --> 00:14:01.159 for which tool is right for this job. So if you 00:14:01.159 --> 00:14:03.419 need verifiable facts with sources, you think, 00:14:03.419 --> 00:14:05.960 ah, perplexity might be good here. If you need 00:14:05.960 --> 00:14:08.559 to build a complex automated process with conditional 00:14:08.559 --> 00:14:11.100 steps, you think, OK, maybe N8n is a better fit 00:14:11.100 --> 00:14:14.039 than just using a basic LLM chat. It's understanding 00:14:14.039 --> 00:14:15.820 those categories we talked about. Knowing the 00:14:15.820 --> 00:14:19.000 landscape, not every single path. Exactly. Third 00:14:19.000 --> 00:14:22.460 skill, workflow thinking. This is about deconstruction 00:14:22.460 --> 00:14:25.700 and reconstruction. Taking a big, complex goal, 00:14:25.740 --> 00:14:28.059 something too big for one AI prompt, and breaking 00:14:28.059 --> 00:14:30.960 it down into smaller, logical, sequential steps. 00:14:31.399 --> 00:14:33.559 Then figuring out which AI tool, or maybe even 00:14:33.559 --> 00:14:36.620 a non -AI tool, is best for each step. Like asking 00:14:36.620 --> 00:14:39.039 an AI to write my marketing campaign that's probably 00:14:39.039 --> 00:14:40.860 gonna fail or give you something super generic, 00:14:40.899 --> 00:14:44.139 but breaking it down. Step one, use chat GPT 00:14:44.139 --> 00:14:46.840 to brainstorm potential target audiences. Step 00:14:46.840 --> 00:14:49.299 two, use perplexity to research their biggest 00:14:49.299 --> 00:14:52.100 pain points. Step three, use Claude to draft 00:14:52.100 --> 00:14:54.340 several compelling ad copy hooks based on those 00:14:54.340 --> 00:14:57.340 pain points. Step four, use Mid Journey to generate 00:14:57.340 --> 00:15:00.179 a relevant image. Step five, maybe use Zapier 00:15:00.179 --> 00:15:02.220 to automatically schedule posting the final ad. 00:15:02.220 --> 00:15:05.639 You got it. And the fourth skill, critical evaluation 00:15:05.639 --> 00:15:09.200 and creative remixing. This is huge. AI is a 00:15:09.200 --> 00:15:11.720 powerful collaborator. But it's not an oracle. 00:15:11.879 --> 00:15:14.340 It makes mistakes. It hallucinates. You must 00:15:14.340 --> 00:15:16.600 always critically evaluate its output, especially 00:15:16.600 --> 00:15:20.220 for factual accuracy, bias, or just plain weirdness. 00:15:20.700 --> 00:15:23.120 But there's another side to this too. Sometimes 00:15:23.120 --> 00:15:25.379 the AI gives you something unexpected, something 00:15:25.379 --> 00:15:27.480 you didn't ask for, but it's actually better. 00:15:27.899 --> 00:15:30.759 Or it sparks a totally new idea. So part of this 00:15:30.759 --> 00:15:33.639 skill is being flexible, recognizing those happy 00:15:33.639 --> 00:15:36.320 accidents, and being willing to remix your original 00:15:36.320 --> 00:15:39.059 plan. lean into the AI's surprising strengths 00:15:39.059 --> 00:15:42.440 sometimes. So verify, but also be open to useful 00:15:42.440 --> 00:15:44.899 surprises. Out of those four skills, which one 00:15:44.899 --> 00:15:47.500 offers the quickest path to immediate improvement 00:15:47.500 --> 00:15:50.259 in how we use AI? Mastering advanced prompting 00:15:50.259 --> 00:15:53.000 significantly elevates your AI interactions almost 00:15:53.000 --> 00:15:54.759 instantly. Okay, so we're getting better with 00:15:54.759 --> 00:15:56.820 prompts, tools, workflows. What's the next step? 00:15:56.919 --> 00:15:58.799 If we're getting good at using AI, what's the 00:15:58.799 --> 00:16:00.600 next frontier? Especially thinking about the 00:16:00.600 --> 00:16:03.000 future of work. That next level really points 00:16:03.000 --> 00:16:05.480 towards building and managing AI agents. Now, 00:16:05.519 --> 00:16:07.000 it's important to understand the difference here. 00:16:07.440 --> 00:16:10.059 Regular automation, like with Zapier maybe, tends 00:16:10.059 --> 00:16:13.120 to follow fixed rules. If this happens, then 00:16:13.120 --> 00:16:16.159 do that specific thing. Pretty rigid. An AI agent 00:16:16.159 --> 00:16:18.799 is different. It can reason, it can plan, and 00:16:18.799 --> 00:16:20.899 it can make decisions on its own to achieve a 00:16:20.899 --> 00:16:23.220 broader goal you give it. You don't tell it every 00:16:23.220 --> 00:16:25.279 single step, you give it an objective, and it 00:16:25.279 --> 00:16:27.600 figures out how to get there, which tools to 00:16:27.600 --> 00:16:29.940 use from its toolkit, and in what order. So less 00:16:29.940 --> 00:16:32.940 instruction following, more autonomous problem 00:16:32.940 --> 00:16:35.460 solving. Exactly. Think of the components. An 00:16:35.460 --> 00:16:37.519 agent usually has a brain, which is a powerful 00:16:37.519 --> 00:16:40.679 LLM like GPT -4 or Gemini for the reasoning part. 00:16:41.360 --> 00:16:43.440 It needs memory to remember past interactions, 00:16:43.820 --> 00:16:46.120 context, what it learned. And it needs access 00:16:46.120 --> 00:16:48.360 to tools. These are the actions it can take, 00:16:48.639 --> 00:16:50.720 like searching the web, sending an email, accessing 00:16:50.720 --> 00:16:52.860 your files, running code, interacting with other 00:16:52.860 --> 00:16:55.240 apps. What's exciting is that platforms like 00:16:55.240 --> 00:16:57.340 NNN are starting to make building these agents 00:16:57.340 --> 00:16:59.899 much more accessible, even with drag -and -drop 00:16:59.899 --> 00:17:02.559 interfaces. It's democratizing the ability to 00:17:02.559 --> 00:17:04.660 create these more eponymous systems. Can you 00:17:04.660 --> 00:17:06.619 give a simple example of what an agent might 00:17:06.619 --> 00:17:09.319 do? Sure. A relatively simple one could be an 00:17:09.319 --> 00:17:12.680 agent that, say, monitors a specific RSS feed 00:17:12.680 --> 00:17:15.450 for news articles every morning. When a new article 00:17:15.450 --> 00:17:18.130 appears, it uses an LLM tool to summarize it, 00:17:18.529 --> 00:17:21.210 then uses a Slack or Discord tool to post that 00:17:21.210 --> 00:17:23.230 summary to a specific channel for your team. 00:17:24.190 --> 00:17:26.730 All, automatically based on the goal, keep the 00:17:26.730 --> 00:17:30.049 team updated on relevant news. A more complex 00:17:30.049 --> 00:17:33.390 one might monitor industry trends, identify potential 00:17:33.390 --> 00:17:35.769 competitive threats based on certain criteria, 00:17:36.309 --> 00:17:39.430 synthesize that information and draft a preliminary 00:17:39.430 --> 00:17:41.890 strategic brief for human review. Right, I can 00:17:41.890 --> 00:17:44.069 see how that scales. How does this change the 00:17:44.069 --> 00:17:46.809 picture for daily work? The potential shift is 00:17:46.809 --> 00:17:49.130 that humans move further towards overseeing, 00:17:49.369 --> 00:17:52.450 strategizing, and focusing on the uniquely human 00:17:52.450 --> 00:17:55.150 skills, creativity, complex problem -solving, 00:17:55.410 --> 00:17:58.009 relationship building, ethical judgment. We'd 00:17:58.009 --> 00:18:00.250 be managing a team of specialized AI agents that 00:18:00.250 --> 00:18:02.730 handle a lot of the repetitive data processing 00:18:02.730 --> 00:18:05.529 or routine communication tasks. So looking ahead, 00:18:05.630 --> 00:18:07.549 what's potentially the biggest shift for our 00:18:07.549 --> 00:18:10.009 day -to -day work when agents become more widespread? 00:18:10.220 --> 00:18:13.079 Humans will likely focus much more on high -level 00:18:13.079 --> 00:18:16.319 thinking and direction, delegating routine execution 00:18:16.319 --> 00:18:20.559 to AI agents. Sponsor. So let's pull this all 00:18:20.559 --> 00:18:22.779 together. After this deep dive, what's the big 00:18:22.779 --> 00:18:25.099 takeaway? It feels like the AI revolution isn't 00:18:25.099 --> 00:18:27.759 really about replacing us, is it? No, I really 00:18:27.759 --> 00:18:30.440 don't think so. It's fundamentally about empowerment. 00:18:30.920 --> 00:18:34.380 AI offers these incredibly powerful, super -intelligent 00:18:34.380 --> 00:18:37.519 tools for humanity. All the noise, the hype cycles 00:18:37.519 --> 00:18:39.680 about new models, it's mostly surface level. 00:18:40.119 --> 00:18:42.000 The core principles, we talked about learning 00:18:42.000 --> 00:18:44.240 how to ask good questions, prompting, knowing 00:18:44.240 --> 00:18:46.559 which tool to use for what job, thinking and 00:18:46.559 --> 00:18:48.720 workflows, and always critically evaluating the 00:18:48.720 --> 00:18:51.240 output. Those skills are evergreen. They'll serve 00:18:51.240 --> 00:18:53.339 you no matter what new tool comes out next week. 00:18:53.599 --> 00:18:56.329 And the feeling of being behind. Maybe that's 00:18:56.329 --> 00:18:58.289 misplaced. Just understanding these concepts 00:18:58.289 --> 00:19:00.710 seems like a big step forward. Absolutely. If 00:19:00.710 --> 00:19:03.130 you grasp these ideas, you're likely already 00:19:03.130 --> 00:19:05.309 ahead of most people. You're not behind. You're 00:19:05.309 --> 00:19:07.970 building the foundation. And remember, the future 00:19:07.970 --> 00:19:10.250 isn't this passive thing that just washes over 00:19:10.250 --> 00:19:12.490 us. It's something we actively shape, you know? 00:19:12.950 --> 00:19:16.230 Prompt by prompt, workflow by workflow. So here's 00:19:16.230 --> 00:19:19.160 something to think about. What's one small, maybe 00:19:19.160 --> 00:19:21.900 slightly annoying, repetitive task in your work 00:19:21.900 --> 00:19:24.200 or your life right now? Just one thing. Could 00:19:24.200 --> 00:19:26.700 you maybe transform that even just a little bit 00:19:26.700 --> 00:19:30.089 with a simple AI tool? Starting today. beat. 00:19:30.390 --> 00:19:33.529 Don't aim for perfection. Just begin. Experiment. 00:19:33.869 --> 00:19:36.250 Yeah, exactly. And just remember, every little 00:19:36.250 --> 00:19:39.049 step you take, every small aha moment you have 00:19:39.049 --> 00:19:41.950 playing with these tools, it moves you closer. 00:19:42.349 --> 00:19:44.710 Closer to really understanding and harnessing 00:19:44.710 --> 00:19:47.009 this incredible technology for yourself. That 00:19:47.009 --> 00:19:48.730 seems like a good place to leave it for today. 00:19:49.390 --> 00:19:51.390 That's all for this deep dive. We really hope 00:19:51.390 --> 00:19:53.430 it sparked your curiosity and maybe gave you 00:19:53.430 --> 00:19:56.549 a clearer path forward in navigating AI. Out 00:19:56.549 --> 00:19:57.069 to your music.