WEBVTT 00:00:00.000 --> 00:00:02.220 When you sit down with an artificial intelligence 00:00:02.220 --> 00:00:05.019 tool to research your investments, are you simply 00:00:05.019 --> 00:00:07.980 using a lightning -fast search engine, BEAT, 00:00:08.460 --> 00:00:12.320 or is that AI actually functioning as your personal, 00:00:12.320 --> 00:00:14.919 you know, dedicated financial analyst? That is 00:00:14.919 --> 00:00:16.660 the crucial distinction, yeah. And welcome to 00:00:16.660 --> 00:00:18.660 the Deep Dive. The difference, as our sources 00:00:18.660 --> 00:00:20.660 are showing, really comes down to the quality 00:00:20.660 --> 00:00:23.679 of your command, of your prompt. Most investors, 00:00:23.679 --> 00:00:26.019 they still rely on simple, kind of one -line 00:00:26.019 --> 00:00:28.539 questions. But stay, we're giving you a shortcut, 00:00:28.579 --> 00:00:31.219 really, to maximizing rigor. Right. We're looking 00:00:31.219 --> 00:00:33.520 at sources that treat the prompt, the instruction 00:00:33.520 --> 00:00:36.600 you give the AI like a complete blueprint, almost 00:00:36.600 --> 00:00:39.240 like a multi -part structure designed to generate 00:00:39.240 --> 00:00:42.439 an organized, deep research report, not just, 00:00:42.439 --> 00:00:44.600 you know, a list of facts. Exactly. Our mission 00:00:44.600 --> 00:00:47.619 today is to give you that blueprint. seven detailed 00:00:47.619 --> 00:00:49.799 examples. We're showing you how to move from 00:00:49.799 --> 00:00:52.579 basic data check stuff like that to complex stock 00:00:52.579 --> 00:00:55.259 screening and even qualitative analysis. You're 00:00:55.259 --> 00:00:57.619 going to learn how to transform an AI, something 00:00:57.619 --> 00:01:00.359 like perplexity, into a disciplined systematic 00:01:00.359 --> 00:01:03.320 research partner. Let's dive right into the core 00:01:03.320 --> 00:01:05.790 analysis. OK, let's unpack this first scenario, 00:01:05.989 --> 00:01:08.829 then. We really need to move far past just asking 00:01:08.829 --> 00:01:11.650 if a stock went up or down. To gain a true edge, 00:01:11.790 --> 00:01:13.390 you've got to understand the why behind that 00:01:13.390 --> 00:01:15.750 move and, crucially, what the wider market thinks 00:01:15.750 --> 00:01:19.409 now. Right. So our case study focuses on NVIDIA 00:01:19.409 --> 00:01:23.549 after a massive price jump. A structured analysis 00:01:23.549 --> 00:01:25.829 here kicks off with a four -part prompt. And 00:01:25.829 --> 00:01:28.030 the first output it gives you is a performance 00:01:28.030 --> 00:01:30.390 comparison. And that performance gap is, well, 00:01:30.629 --> 00:01:32.849 it's staggering, isn't it? Our sources note that 00:01:32.849 --> 00:01:36.170 in one recent week, NVDA stock delivered an astonishing 00:01:36.170 --> 00:01:41.769 game, 21 .5%. 21 .5%. Now, hold that number against 00:01:41.769 --> 00:01:44.150 the sector benchmark. The VanEck semiconductor 00:01:44.150 --> 00:01:47.599 ETF, that's SMH, tracks the whole industry. it 00:01:47.599 --> 00:01:50.640 only managed an 8 .2 % climb in the same period. 00:01:51.120 --> 00:01:53.420 So the massive outperformance, it confirms the 00:01:53.420 --> 00:01:55.299 catalyst was company specific. It wasn't just 00:01:55.299 --> 00:01:57.260 a rising tide lifting all boats, you know. Right, 00:01:57.319 --> 00:01:59.739 it singles out Nvidia. Which brings us directly 00:01:59.739 --> 00:02:02.200 to the primary catalyst. What was the specific 00:02:02.200 --> 00:02:05.159 needle moving news here? It was the GTC 2025 00:02:05.159 --> 00:02:08.180 conference and specifically the introduction 00:02:08.180 --> 00:02:10.800 of the new Blackwell Ultra GPU for data centers. 00:02:11.120 --> 00:02:14.319 And get this, this wasn't just some small incremental 00:02:14.319 --> 00:02:17.210 update. Public tests highlight that Blackwell 00:02:17.210 --> 00:02:20.930 Ultra was 30 % faster for key AI training tasks 00:02:20.930 --> 00:02:24.169 than the older model. 30%. That's a huge leap. 00:02:24.349 --> 00:02:26.610 Yeah. That kind of performance jump immediately 00:02:26.610 --> 00:02:28.710 shifts the calculus for analysts. You can see 00:02:28.710 --> 00:02:31.009 it happen. And the analyst reaction was swift 00:02:31.009 --> 00:02:34.849 and quantifiable, too. HSBC upgraded NVDA from 00:02:34.849 --> 00:02:38.629 hold. to buy. Goldman Sachs significantly raised 00:02:38.629 --> 00:02:41.669 its price target, moving it from $150 up to $180. 00:02:41.909 --> 00:02:43.789 I mean, the market perception just changed overnight. 00:02:44.370 --> 00:02:45.909 And the change in valuation is maybe the most 00:02:45.909 --> 00:02:48.430 important output here. Before this rally, the 00:02:48.430 --> 00:02:50.990 stock's forward PE ratio was sitting around 35 00:02:50.990 --> 00:02:54.389 times earnings. OK, 35x. And after that 21 .5 00:02:54.389 --> 00:02:57.949 % jump, that forward PE shot up to 42 .5 times. 00:02:58.009 --> 00:03:00.310 That is a substantial increase. It really is. 00:03:00.569 --> 00:03:02.710 The market isn't just saying NVDA is worth X 00:03:02.710 --> 00:03:05.240 amount today. By accepting that much higher ratio, 00:03:05.340 --> 00:03:08.879 42 .5, they are explicitly pricing in huge, almost 00:03:08.879 --> 00:03:10.900 guaranteed future growth, which means they're 00:03:10.900 --> 00:03:13.520 willing to pay a massive risk premium for those 00:03:13.520 --> 00:03:15.860 projected earnings down the line. OK, let's just 00:03:15.860 --> 00:03:18.319 unpack that premium for a second. How does that 00:03:18.319 --> 00:03:22.659 PE jump going from 35x to 42 .5x, how does that 00:03:22.659 --> 00:03:26.139 actually quantify investor belief in NVDA's future 00:03:26.139 --> 00:03:28.599 growth? Well, the increase confirms investors 00:03:28.599 --> 00:03:30.960 expect significantly higher future earnings. 00:03:31.520 --> 00:03:34.500 It moves beyond just optimism into actual financial 00:03:34.500 --> 00:03:36.780 commitment. Right. That shift from just analysis 00:03:36.780 --> 00:03:39.240 to actual commitment. That's key. Absolutely. 00:03:39.479 --> 00:03:41.349 Now, moving on. This is where you stop being 00:03:41.349 --> 00:03:44.349 like a manual data clerk and really start acting 00:03:44.349 --> 00:03:46.909 as a portfolio manager. The next two prompts 00:03:46.909 --> 00:03:49.389 focus entirely on automation and scaling your 00:03:49.389 --> 00:03:52.110 analysis using structured reports. OK, so prompt 00:03:52.110 --> 00:03:54.349 two is designed for a daily portfolio briefing. 00:03:54.789 --> 00:03:56.810 You basically stop manually checking individual 00:03:56.810 --> 00:03:59.169 events every single morning and you let the AI 00:03:59.169 --> 00:04:01.629 compile the heavy lifting for you. Exactly. This 00:04:01.629 --> 00:04:03.750 structured report delivers four key components. 00:04:03.849 --> 00:04:06.259 First up. technical analysis. So it's tracking 00:04:06.259 --> 00:04:08.879 price change, volume compared to the 20 -day 00:04:08.879 --> 00:04:11.319 average, and those essential support or resistance 00:04:11.319 --> 00:04:14.500 levels. Then you get fundamental news. And this 00:04:14.500 --> 00:04:17.379 includes any urgent SEC filings, like a Form 00:04:17.379 --> 00:04:19.680 8K. For those who may be unfamiliar, that signals 00:04:19.680 --> 00:04:22.259 a major corporate change or some crucial event 00:04:22.259 --> 00:04:24.980 that needs immediate attention. It's important 00:04:24.980 --> 00:04:27.579 stuff. Definitely. The report also captures analyst 00:04:27.579 --> 00:04:30.720 updates and critical macroeconomic context. Our 00:04:30.720 --> 00:04:32.899 sources showed an example where the August CPI 00:04:32.899 --> 00:04:35.800 data, the inflation number, came in at 0 .4%. 00:04:35.800 --> 00:04:38.540 That was higher than expected. Now, that kind 00:04:38.540 --> 00:04:41.399 of macro news needs to be filtered down to specific 00:04:41.399 --> 00:04:43.360 stock impact. You need to see how it connects. 00:04:43.600 --> 00:04:46.019 And the report does that. It delivers those targeted 00:04:46.019 --> 00:04:49.100 results. For instance, TSLA faced selling pressure 00:04:49.100 --> 00:04:53.279 dropping 2 .1%, breaking below its key $250 support 00:04:53.279 --> 00:04:55.459 level, potentially due to production warmers, 00:04:55.579 --> 00:04:57.639 maybe linked to the economic outlook. Meanwhile, 00:04:57.639 --> 00:05:01.240 Microsoft, MSFT, it rose 1 .5 % on trading volume 00:05:01.240 --> 00:05:04.019 that was 30 % higher than its average. The AI 00:05:04.019 --> 00:05:06.139 connects the dots between the CPI number and 00:05:06.139 --> 00:05:07.920 the specific stock reactions almost instantly. 00:05:08.000 --> 00:05:10.220 And that speed and organization leads directly 00:05:10.220 --> 00:05:12.379 into prompt three, the complex technical screening. 00:05:12.540 --> 00:05:14.920 This is where you transform an entire multi -layered 00:05:14.920 --> 00:05:17.240 trading strategy into just one single command 00:05:17.240 --> 00:05:20.199 for the AI. OK, so you define the specific bullish 00:05:20.199 --> 00:05:22.439 criteria for the AI. You're basically asking 00:05:22.439 --> 00:05:26.240 it to search the entire S &P 500 and find only 00:05:26.240 --> 00:05:28.670 the that meet all three specific conditions at 00:05:28.670 --> 00:05:33.060 the same time. Pretty rigorous. First, it's got 00:05:33.060 --> 00:05:35.500 to be exiting oversold territory. That means 00:05:35.500 --> 00:05:38.639 the 14 May Relative Strength Index, or RSI that 00:05:38.639 --> 00:05:40.939 measures price momentum, has recently moved above 00:05:40.939 --> 00:05:43.519 the 30 level. Second, you need a bullish MEC 00:05:43.519 --> 00:05:46.079 -ED crossover. That indicates a potential shift 00:05:46.079 --> 00:05:48.800 in longer -term momentum is underway. OK. And 00:05:48.800 --> 00:05:51.459 the third hurdle is volume confirmation. You 00:05:51.459 --> 00:05:53.540 need that daily trading volume to be at least 00:05:53.540 --> 00:05:57.040 50 % higher than the 20 -day average. That proves 00:05:57.040 --> 00:05:59.360 the move has real conviction behind it. Yeah, 00:05:59.360 --> 00:06:02.279 just listing those three complex criteria simultaneously 00:06:02.279 --> 00:06:04.819 makes my head spin thinking about checking even 00:06:04.819 --> 00:06:07.639 20 stocks manually for all that. Honestly, yeah. 00:06:07.819 --> 00:06:10.300 Trying to check the RSI and the MechEd crossover 00:06:10.300 --> 00:06:12.420 and the volume confirmation across a full watch 00:06:12.420 --> 00:06:14.019 list, that's usually where I just kind of give 00:06:14.019 --> 00:06:17.279 up and maybe resort to a hunch. This prompt solves 00:06:17.279 --> 00:06:19.699 that exact pain point. It's a vulnerability I 00:06:19.699 --> 00:06:21.279 definitely admit to having myself sometimes. 00:06:21.560 --> 00:06:23.379 Right. We've all been there. And the resulting 00:06:23.379 --> 00:06:25.860 report from the AI, it found three opportunities 00:06:25.860 --> 00:06:29.079 that met all those criteria. Adobe, Qualcomm, 00:06:29.379 --> 00:06:31.660 and Caterpillar. And the data confirmation was 00:06:31.660 --> 00:06:34.879 right there. QCOM, for example, it showed a plus 00:06:34.879 --> 00:06:38.639 72 % volume change validating that signal. OK, 00:06:38.899 --> 00:06:41.819 so drilling down on that, what is the main benefit 00:06:41.819 --> 00:06:45.779 of screening using three complex criteria simultaneously 00:06:45.779 --> 00:06:48.259 like this? It efficiently finds opportunities 00:06:48.259 --> 00:06:52.139 that exactly match a specific multi -layer trading 00:06:52.139 --> 00:06:55.180 strategy. And importantly, it eliminates human 00:06:55.180 --> 00:06:57.980 error or oversight. Efficiency and accuracy. 00:06:58.000 --> 00:07:00.379 Makes sense. a mid -roll sponsor read placeholder. 00:07:01.019 --> 00:07:02.839 Welcome back. So far, we've covered hard data, 00:07:02.980 --> 00:07:05.120 automated reports. But where the real alpha, 00:07:05.160 --> 00:07:07.579 the edge, is often found, it's not just in the 00:07:07.579 --> 00:07:09.720 numbers. It's often in the qualitative analysis 00:07:09.720 --> 00:07:12.040 reading between the lines of management communication. 00:07:12.379 --> 00:07:15.550 Exactly. Prompt4 focuses on going inside an earnings 00:07:15.550 --> 00:07:17.810 call. This process extracts management sentiment, 00:07:18.089 --> 00:07:20.069 identifies recurring themes in the Q &A session, 00:07:20.310 --> 00:07:22.709 which often reveal way more about future strategy 00:07:22.709 --> 00:07:24.850 than just the basic financials do. Let's use 00:07:24.850 --> 00:07:27.769 the Microsoft MSFT earnings call pace study here. 00:07:28.250 --> 00:07:30.470 Part one analyzes the key performance indicators, 00:07:30.629 --> 00:07:34.029 the KPIs. The AI extracted that Azure cloud revenue 00:07:34.029 --> 00:07:37.449 grew by 42%. Pretty strong number. Yeah, but 00:07:37.449 --> 00:07:40.139 the fascinating part is the acceleration. Azure 00:07:40.139 --> 00:07:42.279 growth was actually slightly higher than the 00:07:42.279 --> 00:07:45.139 40 % reported in the previous quarter. Now why 00:07:45.139 --> 00:07:47.800 is that tiny 2 % difference such a strong signal? 00:07:48.480 --> 00:07:50.560 It suggests operational momentum is actually 00:07:50.560 --> 00:07:53.069 building, not slowing down. Interesting nuance. 00:07:53.329 --> 00:07:55.329 OK, then the Q &A theme section. This is where 00:07:55.329 --> 00:07:57.189 the structure prompt really shines, I think. 00:07:57.629 --> 00:08:00.129 The AI identified the top three concerns that 00:08:00.129 --> 00:08:02.089 analysts kept hammering away at during the call. 00:08:02.269 --> 00:08:05.550 Number one, how Microsoft plans on actually monetizing 00:08:05.550 --> 00:08:08.470 its co -pilot AI services. Number two, maintaining 00:08:08.470 --> 00:08:10.889 its cloud advantage over rivals like AWS and 00:08:10.889 --> 00:08:13.600 Google. And number three, the looming threat 00:08:13.600 --> 00:08:15.800 of increasing global regulation. Those were the 00:08:15.800 --> 00:08:18.319 hot topics. And then there's the sentiment analysis. 00:08:18.439 --> 00:08:20.279 This is something that's incredibly hard for 00:08:20.279 --> 00:08:23.000 a human to track consistently across hours of 00:08:23.000 --> 00:08:26.100 audio. The AI detected a consistently confident 00:08:26.100 --> 00:08:28.699 and assertive tone from the management team throughout 00:08:28.699 --> 00:08:30.720 the entire call. OK, and here's where it gets 00:08:30.720 --> 00:08:32.850 really interesting, I thought. When addressing 00:08:32.850 --> 00:08:35.649 the competitive landscape, the CEO made a highly 00:08:35.649 --> 00:08:38.809 specific strategic point. He emphasized offering 00:08:38.809 --> 00:08:41.889 a complete system from the computer chips all 00:08:41.889 --> 00:08:43.990 the way to the final apps. That's a direct quote 00:08:43.990 --> 00:08:46.649 pulled by the AI. And this was framed as their 00:08:46.649 --> 00:08:48.990 unique advantage over companies that only offer 00:08:48.990 --> 00:08:52.970 single sort of. point solutions. Yeah, that quote, 00:08:53.269 --> 00:08:55.529 that single quote, is the kind of detail that 00:08:55.529 --> 00:08:57.649 informs your investment thesis way better than 00:08:57.649 --> 00:08:59.830 just looking at a balance sheet sometimes. It's 00:08:59.830 --> 00:09:02.049 really a statement about market domination strategy, 00:09:02.129 --> 00:09:04.389 not just market share numbers. So digging into 00:09:04.389 --> 00:09:06.750 that sentiment piece again, what did the sentiment 00:09:06.750 --> 00:09:09.570 analysis reveal about Microsoft's competition 00:09:09.570 --> 00:09:12.190 strategy specifically? Management confidently 00:09:12.190 --> 00:09:14.190 focused on promoting their whole end -to -end 00:09:14.190 --> 00:09:16.649 system, their ecosystem, rather than just competing 00:09:16.649 --> 00:09:19.850 on specs for single products. Okay, moving into 00:09:19.850 --> 00:09:22.289 our final segment now. We're looking at using 00:09:22.289 --> 00:09:25.370 AI as more of a strategic radar system. This 00:09:25.370 --> 00:09:27.669 involves tracking the entire competitive landscape 00:09:27.669 --> 00:09:31.269 and then filtering the market based on advanced, 00:09:31.629 --> 00:09:34.110 sometimes complex investment philosophies. Right, 00:09:34.350 --> 00:09:36.490 so Prompt 5 is your weekly industry intelligence 00:09:36.490 --> 00:09:39.950 report. You're effectively using AI as a sophisticated 00:09:39.950 --> 00:09:43.309 radar system. It tracks the entire sector, not 00:09:43.309 --> 00:09:45.389 just the stocks you happen to own or follow closely. 00:09:45.649 --> 00:09:48.190 Exactly. The first part tracks the competitive 00:09:48.190 --> 00:09:51.240 landscape. For example, the sources noted a key 00:09:51.240 --> 00:09:53.899 strategic partnership between AMD and Oracle 00:09:53.899 --> 00:09:58.639 Cloud to deploy AMD's new MI -400X accelerators. 00:09:59.120 --> 00:10:01.620 Now, that is a direct, measurable challenge to 00:10:01.620 --> 00:10:03.379 Nvidia's dominance in the data center space. 00:10:03.480 --> 00:10:06.779 You need to know that. Part two handles emerging 00:10:06.779 --> 00:10:09.779 trends. This is where the AI spotted the sovereign 00:10:09.779 --> 00:10:12.679 AI trend. That's countries like France and India 00:10:12.679 --> 00:10:14.840 starting to build their own national large language 00:10:14.840 --> 00:10:17.720 models. This creates an entirely new global market 00:10:17.720 --> 00:10:19.600 for infrastructure. and ship companies. That's 00:10:19.600 --> 00:10:21.799 a big one. And part three tracks venture capital 00:10:21.799 --> 00:10:24.240 flow. Where's the smart money going? We see an 00:10:24.240 --> 00:10:26.559 example like a startup called Cerebral Dynamics 00:10:26.559 --> 00:10:29.799 focusing on AI drug discovery, raising a staggering 00:10:29.799 --> 00:10:33.700 $120 million. This immediately flags where sophisticated 00:10:33.700 --> 00:10:36.059 investors are deploying capital right now. That 00:10:36.059 --> 00:10:39.009 sovereign AI trend. Wow. I mean, I would have 00:10:39.009 --> 00:10:40.850 completely missed that just scrolling through 00:10:40.850 --> 00:10:43.830 normal headlines. Whoa. Imagine automatically 00:10:43.830 --> 00:10:46.490 tracking every single global trend like that 00:10:46.490 --> 00:10:48.669 without reading hundreds of news sources every 00:10:48.669 --> 00:10:50.950 single week. That's like having a bespoke spy 00:10:50.950 --> 00:10:53.610 satellite just for market movers. Incredible. 00:10:54.110 --> 00:10:56.990 Right. That kind of comprehensive radar shifts 00:10:56.990 --> 00:10:59.909 the conversation from just reacting to data passively 00:10:59.909 --> 00:11:02.370 to actively forming strategy. So we've covered 00:11:02.370 --> 00:11:04.549 five types of reports now. Let's jump to our 00:11:04.549 --> 00:11:07.250 final technique. This is prompt seven, which 00:11:07.250 --> 00:11:09.730 transforms an entire investment philosophy into 00:11:09.730 --> 00:11:13.590 basically machine code. OK, prompt seven is the 00:11:13.590 --> 00:11:16.110 JARP screening, growth at a reasonable price. 00:11:16.330 --> 00:11:18.269 Now, this is a highly nuanced philosophy, right? 00:11:18.490 --> 00:11:20.769 It blends two separate concepts, quality and 00:11:20.769 --> 00:11:24.070 value, into one precise interlocking set of machine 00:11:24.070 --> 00:11:26.070 searchable criteria. Man, the criteria are demanding. 00:11:26.230 --> 00:11:28.450 They're layered. Yeah. You require scale, first 00:11:28.450 --> 00:11:31.230 off market cap over $100 billion, then consistent 00:11:31.230 --> 00:11:33.909 growth over 15 % revenue growth for three consecutive 00:11:33.909 --> 00:11:37.070 years, plus high quality needing over 60 % gross 00:11:37.070 --> 00:11:39.789 margin and over 20 % return on equity. Pretty 00:11:39.789 --> 00:11:42.500 tough gates. And critically, the requirement 00:11:42.500 --> 00:11:45.720 for a reasonable price. Specifically, the forward 00:11:45.720 --> 00:11:48.840 PE ratio must be below its own five -year historical 00:11:48.840 --> 00:11:51.860 average. That's complex screening. It forces 00:11:51.860 --> 00:11:54.840 the AI to consider relative historical valuation, 00:11:55.159 --> 00:11:57.320 not just the current price level. OK, but wait 00:11:57.320 --> 00:12:00.679 a sec. Isn't defining reasonable price simply 00:12:00.679 --> 00:12:03.879 by its historical average maybe a bit too simplistic 00:12:03.879 --> 00:12:06.960 for a machine? Doesn't the broader economic context 00:12:06.960 --> 00:12:09.360 like interest rates matter there? That's a fair 00:12:09.360 --> 00:12:11.539 point. It does matter in the real world. Absolutely. 00:12:11.740 --> 00:12:14.580 But the beauty of these structured rules is that 00:12:14.580 --> 00:12:16.940 the prompt isn't trying to capture all possible 00:12:16.940 --> 00:12:19.419 context. That would be impossible. It's trying 00:12:19.419 --> 00:12:22.379 to capture one specific actionable trading inefficiency. 00:12:22.740 --> 00:12:24.500 Finding stocks that are high quality and still 00:12:24.500 --> 00:12:27.080 growing but seem to be temporarily mispriced 00:12:27.080 --> 00:12:29.159 compared to their own established historical 00:12:29.159 --> 00:12:32.100 norm. It's a very focused task. I see. So it's 00:12:32.100 --> 00:12:34.820 finding a specific anomaly based on its own history. 00:12:34.879 --> 00:12:36.919 And the results from the source material showed 00:12:36.919 --> 00:12:41.500 that Microsoft, MSFT, and Adobe ADBE met all 00:12:41.500 --> 00:12:44.100 these strict requirements at that time. Notably, 00:12:44.279 --> 00:12:47.320 Microsoft's PE was 5 % below its five -year average, 00:12:47.639 --> 00:12:50.980 and Adobe's was actually 10 % below. So it efficiently 00:12:50.980 --> 00:12:53.299 finds these high -quality opportunities only 00:12:53.299 --> 00:12:56.320 when they're temporarily potentially undervalued 00:12:56.320 --> 00:12:58.379 relative to themselves. So thinking about that 00:12:58.379 --> 00:13:01.299 JARP prompt, what would you say is its main accomplishment? 00:13:01.379 --> 00:13:03.730 What does it really achieve? It efficiently finds 00:13:03.730 --> 00:13:06.350 high -quality stocks only when they appear temporarily 00:13:06.350 --> 00:13:09.269 mispriced relative to their own established historical 00:13:09.269 --> 00:13:11.879 valuation range. That really is the core lesson 00:13:11.879 --> 00:13:13.960 we wanted to share today, isn't it? The quality 00:13:13.960 --> 00:13:16.799 of the AI output you get is directly proportional 00:13:16.799 --> 00:13:18.940 to the quality, the structure, the detail of 00:13:18.940 --> 00:13:21.679 your input. These detailed multi -part prompts, 00:13:21.720 --> 00:13:24.379 they really act as a necessary blueprint. Yeah, 00:13:24.379 --> 00:13:26.840 they save you countless hours of routine research. 00:13:27.120 --> 00:13:29.740 Absolutely, yes. But far more importantly, I 00:13:29.740 --> 00:13:33.159 think, they significantly improve the rigor and 00:13:33.159 --> 00:13:36.399 the quality of your analysis by forcing the AI 00:13:36.399 --> 00:13:39.860 to synthesize multiple complex data points simultaneously. 00:13:39.690 --> 00:13:41.549 simultaneously, something that's really hard 00:13:41.549 --> 00:13:44.009 for us humans to do consistently. Now, just a 00:13:44.009 --> 00:13:46.529 quick but very necessary word of caution here. 00:13:46.950 --> 00:13:48.909 The information we discussed today, including 00:13:48.909 --> 00:13:51.309 the specific stocks and metrics like NVDA or 00:13:51.309 --> 00:13:54.409 MSFT, it's purely for educational purposes only. 00:13:54.590 --> 00:13:57.289 This is not investment advice. Please always 00:13:57.289 --> 00:13:59.970 perform your own due diligence and speak to a 00:13:59.970 --> 00:14:02.009 qualified professional before making any financial 00:14:02.009 --> 00:14:04.429 decisions. Indeed. Very important disclaimer. 00:14:04.570 --> 00:14:07.389 We focus heavily today on using these structured 00:14:07.389 --> 00:14:09.669 prompts for analysis, you know, reacting to and 00:14:09.669 --> 00:14:11.830 dissecting the data as it arrives. But what if 00:14:11.830 --> 00:14:14.570 we sort of reverse the process? How can these 00:14:14.570 --> 00:14:17.190 automated systems become fully proactive? Could 00:14:17.190 --> 00:14:19.409 they be constantly generating new customized 00:14:19.409 --> 00:14:21.970 investment philosophies, maybe new complex criteria 00:14:21.970 --> 00:14:25.370 for us to simply test and explore, beat? That 00:14:25.370 --> 00:14:27.149 could fundamentally change how we even discover 00:14:27.149 --> 00:14:29.450 opportunities in the first place. That thought 00:14:29.450 --> 00:14:32.259 alone should really inspire you listening. Start 00:14:32.259 --> 00:14:34.659 by building your first detailed prompt blueprint 00:14:34.659 --> 00:14:37.620 today. Use these examples and just see how much 00:14:37.620 --> 00:14:40.179 faster and frankly smarter your research becomes 00:14:40.179 --> 00:14:42.340 even this week. Until the next deep dive.