WEBVTT 00:00:00.000 --> 00:00:01.419 You know, investment research, it used to be 00:00:01.419 --> 00:00:03.859 all about friction. Oh, yeah. Days, sometimes 00:00:03.859 --> 00:00:08.119 weeks, buried in SEC filings. Exactly. Trying 00:00:08.119 --> 00:00:11.779 to find that edge meant manually cross -referencing 00:00:11.779 --> 00:00:14.099 data, wrestling with just, well, information 00:00:14.099 --> 00:00:18.359 overload. Now it feels like we're seeing institution 00:00:18.359 --> 00:00:22.300 quality analysis, deep, contextual, auditable, 00:00:22.440 --> 00:00:25.239 almost instantly. And Chad GPT -5 seems to be 00:00:25.239 --> 00:00:27.179 at the heart of this shift. It really does. This 00:00:27.179 --> 00:00:30.070 feels... Well, profound, because it's maybe the 00:00:30.070 --> 00:00:34.009 first AI model that feels reliable enough, trustworthy 00:00:34.009 --> 00:00:37.130 enough for serious real money financial decisions. 00:00:37.210 --> 00:00:39.429 Welcome to the deep dive. Great to be digging 00:00:39.429 --> 00:00:41.189 into this. Today, we're going to try and peel 00:00:41.189 --> 00:00:43.229 back the layers on how professional investors 00:00:43.229 --> 00:00:45.250 are adapting. What are they actually doing with 00:00:45.250 --> 00:00:47.350 this? Yeah, the practical application. Our mission 00:00:47.350 --> 00:00:49.429 is to explore the structured methods they're 00:00:49.429 --> 00:00:52.310 using. We'll look at how AI tackles traditional 00:00:52.310 --> 00:00:54.890 fundamental analysis, the stock picking side. 00:00:55.130 --> 00:00:57.049 And then the technical side, too. Yeah. Chart 00:00:57.049 --> 00:00:59.549 patterns and timing. Exactly. And crucially, 00:00:59.670 --> 00:01:02.689 we want to uncover the prompts, the master prompts 00:01:02.689 --> 00:01:05.390 they use, and maybe most importantly, the human 00:01:05.390 --> 00:01:08.489 checks. The verification steps needed to keep 00:01:08.489 --> 00:01:12.430 this powerful tool, well, safe. Absolutely. What's 00:01:12.430 --> 00:01:14.670 really striking, I think, is how this seems to 00:01:14.670 --> 00:01:17.310 address the old trust problem. The hallucination 00:01:17.310 --> 00:01:20.909 issue. Right. For ages, AI was basically unusable 00:01:20.909 --> 00:01:23.870 for serious finance because of it. Models would 00:01:23.870 --> 00:01:26.969 just invent numbers. Make things up. Invent figures, 00:01:27.250 --> 00:01:30.489 create fake trends, make statements with zero 00:01:30.489 --> 00:01:33.310 factual basis. It turned analysis into something 00:01:33.310 --> 00:01:36.180 dangerous, like fiction. That risk. I mean, the 00:01:36.180 --> 00:01:38.920 AI just inventing a crucial number. That's the 00:01:38.920 --> 00:01:40.900 ultimate deal breaker in finance, isn't it? Completely. 00:01:41.120 --> 00:01:43.840 So what makes CGPT -5 the breakthrough here? 00:01:43.920 --> 00:01:46.319 Is it just smarter or is it something else? I 00:01:46.319 --> 00:01:48.219 think it's less about raw intelligence and more 00:01:48.219 --> 00:01:52.920 about being verifiable, auditable. It really 00:01:52.920 --> 00:01:54.920 comes down to audibility. We're seeing a huge 00:01:54.920 --> 00:01:57.239 drop in those hallucination rates. But the big 00:01:57.239 --> 00:02:00.200 thing, proper source citing. Like footnotes. 00:02:00.200 --> 00:02:02.459 Exactly like footnotes, like an academic paper. 00:02:02.560 --> 00:02:05.780 It shows you precisely. which SEC filing, which 00:02:05.780 --> 00:02:08.740 press release, which 10K generated that specific 00:02:08.740 --> 00:02:10.759 data point. Okay. That makes sense. It's building 00:02:10.759 --> 00:02:13.419 trust through transparency. Yeah. So here's a 00:02:13.419 --> 00:02:16.039 question then. If the AI is getting so much more 00:02:16.039 --> 00:02:18.139 accurate and it's citing its sources perfectly, 00:02:18.439 --> 00:02:21.979 what's the main competitive edge for it compared 00:02:21.979 --> 00:02:26.099 to, say, a really skilled human analyst doing 00:02:26.099 --> 00:02:28.979 the same deep dive manually? Yeah. That's the 00:02:28.979 --> 00:02:31.680 core question. What's the edge? I'd say the edge 00:02:31.680 --> 00:02:33.759 is the scale of contextual awareness analyzed 00:02:33.759 --> 00:02:36.639 instantly. Speed and breadth beat manual review 00:02:36.639 --> 00:02:38.699 every time when you're talking hundreds of documents. 00:02:38.879 --> 00:02:41.340 Right. Scale. And that scale brings us neatly 00:02:41.340 --> 00:02:44.439 into fundamental analysis. The classic approach. 00:02:44.680 --> 00:02:46.939 Trying to figure out a company's real intrinsic 00:02:46.939 --> 00:02:49.759 value, looking at its financials, its market 00:02:49.759 --> 00:02:51.719 position, the management team. All that good 00:02:51.719 --> 00:02:54.099 stuff. And the AI here, it's not replacing the 00:02:54.099 --> 00:02:56.699 analyst, is it? It's more like a super -powered 00:02:56.699 --> 00:03:00.120 research engine. Precisely. The key is effective 00:03:00.120 --> 00:03:03.740 delegation. You, the investor, you set the strategy, 00:03:03.879 --> 00:03:06.419 the framework. The AI does the heavy lifting, 00:03:06.620 --> 00:03:08.939 the relentless data sifting. So you use something 00:03:08.939 --> 00:03:11.219 called a master prompt framework. That's right. 00:03:11.300 --> 00:03:13.759 It starts broad. You define your investment strategy 00:03:13.759 --> 00:03:18.020 first. Are you looking for growth, value, focused 00:03:18.020 --> 00:03:20.319 on specific sector like tech or healthcare? You 00:03:20.319 --> 00:03:22.539 set the direction. Exactly. But then you get 00:03:22.539 --> 00:03:26.099 specific. Once the strategy is set, what's like... 00:03:26.280 --> 00:03:28.340 The most critical hard number you ask the AI 00:03:28.340 --> 00:03:31.180 to screen for first. Is it always about cash 00:03:31.180 --> 00:03:33.620 flow? Positive free cash flow growth is usually 00:03:33.620 --> 00:03:35.759 a pretty strong sign, yeah. Shows the business 00:03:35.759 --> 00:03:37.639 is actually generating cash. It's sustainable. 00:03:37.919 --> 00:03:40.259 Makes sense. But you need safety nets too, right? 00:03:40.360 --> 00:03:42.460 So the quantitative screening part needs hard 00:03:42.460 --> 00:03:46.460 metrics. Things like a liquidity ratio maybe 00:03:46.460 --> 00:03:50.439 above 1 .0, high gross margins, say, north of 00:03:50.439 --> 00:03:52.439 40%. Right. You're building criteria. Yeah. It's 00:03:52.439 --> 00:03:54.659 like stacking Lego blocks of data, building a 00:03:54.659 --> 00:03:56.960 solid foundation. And then there's a third step, 00:03:57.000 --> 00:03:59.879 which handles the, let's say, squishier stuff. 00:04:00.139 --> 00:04:03.199 Yeah. The qualitative screening. Management track 00:04:03.199 --> 00:04:07.340 records. Market sentiment. Yep. Leadership quality, 00:04:07.560 --> 00:04:09.939 competitive modes. Does the company have a real 00:04:09.939 --> 00:04:12.439 advantage? What's the buzz? The analyst consensus. 00:04:13.360 --> 00:04:15.580 Is management stable? Let's make this concrete. 00:04:15.740 --> 00:04:17.939 The source material used NVIDIA as an example. 00:04:18.100 --> 00:04:21.560 How does the AI output look? Well, when structured 00:04:21.560 --> 00:04:23.699 correctly, it doesn't just dump numbers on you. 00:04:23.759 --> 00:04:26.560 It synthesizes. Okay. So for NVIDIA, it might 00:04:26.560 --> 00:04:29.339 highlight, say, the massive revenue growth and 00:04:29.339 --> 00:04:32.600 data centers up, what was it, 427 % year over 00:04:32.600 --> 00:04:35.300 year? And the high margins. But it goes beyond 00:04:35.300 --> 00:04:38.259 just the numbers. Critically, yes. It translates 00:04:38.259 --> 00:04:40.920 that data into competitive intelligence. It points 00:04:40.920 --> 00:04:44.060 out how NVIDIA's CED ecosystem creates huge switching 00:04:44.060 --> 00:04:46.819 costs for customers. That's a qualitative insight 00:04:46.819 --> 00:04:49.639 derived from the data. Got it. But the key quality 00:04:49.639 --> 00:04:52.939 check is? Pricability. Always. Every key number, 00:04:53.040 --> 00:04:55.699 every claim needs that footnote back to the official 00:04:55.699 --> 00:04:59.490 source. The specific 10Q or 10K filing. no exceptions 00:04:59.490 --> 00:05:01.370 that makes sense you know you mentioned prompts 00:05:01.370 --> 00:05:03.370 i still wrestle with prompt drift myself sometimes 00:05:03.370 --> 00:05:06.029 getting the ai to consistently apply the exact 00:05:06.029 --> 00:05:08.009 same criteria over time oh absolutely it's a 00:05:08.009 --> 00:05:11.149 real challenge and beyond just consistency we 00:05:11.149 --> 00:05:14.050 also need the ai to consider context right like 00:05:14.050 --> 00:05:16.550 how does a recommendation fit with my existing 00:05:16.550 --> 00:05:20.310 portfolio or the current economic cycle rising 00:05:20.310 --> 00:05:23.579 rates falling rates That changes things. Hugely 00:05:23.579 --> 00:05:25.420 important. What does that prompt drift actually 00:05:25.420 --> 00:05:28.199 look like? Does the AI just get lazy or does 00:05:28.199 --> 00:05:30.459 it subtly change the rules on you? It's kind 00:05:30.459 --> 00:05:32.519 of more insidious than laziness. It's like the 00:05:32.519 --> 00:05:35.060 AI subtly shifts the emphasis of your criteria 00:05:35.060 --> 00:05:37.910 based on past chance. Or it might just... Forget 00:05:37.910 --> 00:05:40.209 a key negative screen you set up. Yeah. So if 00:05:40.209 --> 00:05:42.490 you ask it for value stocks, three days running, 00:05:42.569 --> 00:05:45.889 maybe on day four, it slightly relaxes your required 00:05:45.889 --> 00:05:48.069 liquidity ratio unless you explicitly state it 00:05:48.069 --> 00:05:49.930 again every single time. Constant vigilance required. 00:05:50.250 --> 00:05:53.250 OK, so thinking about fundamental analysis, if 00:05:53.250 --> 00:05:55.250 the AI is doing all the screening, analyzing 00:05:55.250 --> 00:05:58.649 financials, qualitative factors, what's one big 00:05:58.649 --> 00:06:00.610 challenge where human oversight is still absolutely 00:06:00.610 --> 00:06:03.069 critical? Defining the right criteria up front 00:06:03.069 --> 00:06:05.250 and crucially aligning those recommendations 00:06:05.250 --> 00:06:08.649 with the broader economic. cycle context the 00:06:08.649 --> 00:06:11.110 AI gives you data you provide the wisdom all 00:06:11.110 --> 00:06:12.970 right so the AI has helped us find potential 00:06:12.970 --> 00:06:15.310 value through fundamentals the next big question 00:06:15.310 --> 00:06:18.610 is when when to potentially buy or sell and maybe 00:06:18.610 --> 00:06:21.089 more importantly how to manage the risk involved 00:06:21.089 --> 00:06:23.550 timing and risk management and that speed and 00:06:23.550 --> 00:06:26.889 data processing power mmm it leads us right into 00:06:26.889 --> 00:06:30.730 part two Using AI for technical analysis. This 00:06:30.730 --> 00:06:32.589 is where it gets really interesting for traders. 00:06:32.870 --> 00:06:35.730 Technical analysis aims to predict price moves 00:06:35.730 --> 00:06:39.009 by studying past chart patterns, price and volume 00:06:39.009 --> 00:06:42.029 action. Right. And the AI becomes this expert 00:06:42.029 --> 00:06:45.410 chartist, spotting complex patterns across hundreds, 00:06:45.490 --> 00:06:48.129 maybe thousands of assets way faster than any 00:06:48.129 --> 00:06:50.389 human possibly could. And the technical master 00:06:50.389 --> 00:06:53.800 prompt for this. It's demanding. It needs two 00:06:53.800 --> 00:06:56.160 types of data. It does. That's a key innovation, 00:06:56.360 --> 00:06:58.300 I think. You have to give it the visual, the 00:06:58.300 --> 00:07:00.500 screenshot of the candlestick chart. That's for 00:07:00.500 --> 00:07:02.600 the pattern recognition part. Okay, the picture. 00:07:02.839 --> 00:07:04.980 But then you also feed it the raw numbers, the 00:07:04.980 --> 00:07:08.000 CSV file with the OHLCV data. Sorry, can you 00:07:08.000 --> 00:07:10.240 just quickly define OHLCV again for everyone? 00:07:10.360 --> 00:07:13.319 Sure thing. It's open high, low, close prices, 00:07:13.319 --> 00:07:15.699 and volume for each period. It's the mathematical 00:07:15.699 --> 00:07:18.420 backbone. So the picture and the numbers. Exactly. 00:07:18.459 --> 00:07:21.019 The numbers validate what the AI thinks it sees 00:07:21.019 --> 00:07:24.259 in the picture. ensures precision ah so that 00:07:24.259 --> 00:07:29.040 dual input it creates like an immediate internal 00:07:29.040 --> 00:07:32.439 check a verification system built right in precisely 00:07:32.439 --> 00:07:35.639 the visual pattern gets confirmed or denied by 00:07:35.639 --> 00:07:37.839 the hard mathematical data that must cut down 00:07:37.839 --> 00:07:40.779 errors significantly and it gives you exact measurements 00:07:40.779 --> 00:07:43.879 for setting stops targets risk management spot 00:07:43.879 --> 00:07:47.360 on wow that combination speed and precision it 00:07:47.360 --> 00:07:49.120 really changes the game for a trader doesn't 00:07:49.120 --> 00:07:52.199 it whoa imagine scaling that analyzing, I don't 00:07:52.199 --> 00:07:55.040 know, a billion potential trading setups every 00:07:55.040 --> 00:07:57.459 single day. The scale is mind -boggling. And 00:07:57.459 --> 00:07:59.439 that precision shows up in the examples. Like 00:07:59.439 --> 00:08:00.860 the head and shoulders pattern discussed for 00:08:00.860 --> 00:08:04.000 NVIDIA, that's a classic bearish reversal setup. 00:08:04.180 --> 00:08:06.810 Okay. The AI doesn't just flag it and say H &S 00:08:06.810 --> 00:08:09.509 pattern here. It explains why it sets the criteria, 00:08:09.670 --> 00:08:11.769 the specific price structure, the volume action 00:08:11.769 --> 00:08:13.629 that confirms it. And then it gives you the actionable 00:08:13.629 --> 00:08:16.509 levels. Exactly. Precise levels. Here's your 00:08:16.509 --> 00:08:18.750 potential entry point. Here's the stop loss, 00:08:18.990 --> 00:08:21.790 the price where the pattern is clearly invalidated. 00:08:21.910 --> 00:08:24.410 And here are the profit targets, often based 00:08:24.410 --> 00:08:26.769 on a measured move calculation. So it hands you 00:08:26.769 --> 00:08:29.449 a structured trade idea, potentially with a favorable 00:08:29.449 --> 00:08:33.169 risk reward ratio, maybe like 1 to 2 .2, ready 00:08:33.169 --> 00:08:35.389 to go. That's the goal. And you can get more 00:08:35.389 --> 00:08:37.730 advanced, too. Things like multi -time frame 00:08:37.730 --> 00:08:40.809 analysis. Checking if a pattern on, say, an hourly 00:08:40.809 --> 00:08:43.370 chart aligns with the trend on the daily chart. 00:08:43.450 --> 00:08:46.110 Exactly that. Adds conviction. And you can integrate 00:08:46.110 --> 00:08:48.730 it with option strategies, identifying key strike 00:08:48.730 --> 00:08:51.710 prices near the AI's levels, estimating timelines 00:08:51.710 --> 00:08:54.190 for choosing expirations. OK, so we've got the 00:08:54.190 --> 00:08:56.889 analysis, maybe even a specific trade idea from 00:08:56.889 --> 00:09:00.149 the AI. What are the crucial implementation steps? 00:09:00.330 --> 00:09:02.289 How do you actually make this research effective 00:09:02.289 --> 00:09:04.830 day to day? You absolutely need a structured 00:09:04.830 --> 00:09:08.509 daily routine and just relentless quality control 00:09:08.509 --> 00:09:10.950 of whatever the AI gives you. It's not magic. 00:09:11.070 --> 00:09:13.830 Mid -roll sponsor read placeholder. So that structured 00:09:13.830 --> 00:09:16.519 routine. Yeah. It's totally non -negotiable. 00:09:16.559 --> 00:09:18.139 You can't just casually chat with it and expect 00:09:18.139 --> 00:09:20.500 consistent results. Yeah. You need a daily analysis 00:09:20.500 --> 00:09:23.179 routine. Like a checklist. Sort of. Morning prep 00:09:23.179 --> 00:09:25.840 could involve checking overnight futures, seeing 00:09:25.840 --> 00:09:28.480 what economic data is coming out that day, analyzing 00:09:28.480 --> 00:09:31.600 pre -market gaps in your watch list stocks. Okay. 00:09:31.820 --> 00:09:34.100 Then, at the end of the day, an evening review, 00:09:34.360 --> 00:09:37.019 a performance post -mortem, what worked, what 00:09:37.019 --> 00:09:39.200 didn't, and then updating your watch list using 00:09:39.200 --> 00:09:41.879 fresh AI screenings based on today's action. 00:09:42.190 --> 00:09:44.850 Discipline is key. Absolutely. And quality control, 00:09:44.929 --> 00:09:47.450 the QC part, this is where the human judge becomes 00:09:47.450 --> 00:09:51.009 roaring back. It's critical. AI is a tool, an 00:09:51.009 --> 00:09:53.690 incredibly powerful one, but it's not a replacement 00:09:53.690 --> 00:09:56.080 for your own thinking. So always check the sources 00:09:56.080 --> 00:09:58.600 it provides. Always check the footnoted sources. 00:09:58.820 --> 00:10:01.000 Always try to cross -reference key data points 00:10:01.000 --> 00:10:03.539 independently if you can and just use basic sanity 00:10:03.539 --> 00:10:07.659 checks. Meaning, if the AI suggests a tiny biotech 00:10:07.659 --> 00:10:10.879 stock should suddenly jump 500 % based on some 00:10:10.879 --> 00:10:14.009 obscure regulatory filing it found. You probably 00:10:14.009 --> 00:10:16.309 want to verify that filing wasn't just, I don't 00:10:16.309 --> 00:10:19.029 know, a draft or misinterpreted. Does it make 00:10:19.029 --> 00:10:22.090 sense in the real world? That systematic skepticism, 00:10:22.169 --> 00:10:25.429 it saves you from potentially huge errors. And 00:10:25.429 --> 00:10:27.769 one really powerful technique for complex decisions 00:10:27.769 --> 00:10:30.769 is using chain of thought analysis prompts. Asking 00:10:30.769 --> 00:10:33.549 the AI to show its work. Basically, yeah. You 00:10:33.549 --> 00:10:35.250 ask it to walk through its reasoning step by 00:10:35.250 --> 00:10:38.169 step. First, check the fundamentals. Then confirm 00:10:38.169 --> 00:10:41.070 with technicals. Then assess the risk. Then, 00:10:41.070 --> 00:10:43.950 and only then. give the final verdict or recommendation. 00:10:44.269 --> 00:10:46.710 So you can follow its logic. Exactly. It makes 00:10:46.710 --> 00:10:48.590 the reasoning auditable, not just a black box 00:10:48.590 --> 00:10:51.750 answer. But that complexity, all that data, doesn't 00:10:51.750 --> 00:10:54.230 it risk leading to, you know, analysis paralysis? 00:10:54.309 --> 00:10:56.309 Too much information can't pull the trigger. 00:10:56.529 --> 00:10:58.789 That's a very real risk. Information overload 00:10:58.789 --> 00:11:01.149 is easy with these tools. So how do you fight 00:11:01.149 --> 00:11:03.250 that? We use strict filters and the prompts. 00:11:03.409 --> 00:11:06.470 You explicitly tell the AI, summarize your findings 00:11:06.470 --> 00:11:08.409 in exactly three bullet points. Two bullets only. 00:11:08.649 --> 00:11:12.629 Yep. Maybe. The single strongest bullish factor, 00:11:12.769 --> 00:11:16.450 the biggest risk or concern, and a clear, concise 00:11:16.450 --> 00:11:20.129 action recommendation. Constraints force clarity. 00:11:20.490 --> 00:11:22.909 Cut through the noise. That's smart. And what 00:11:22.909 --> 00:11:25.929 about the risk of just believing the AI too much? 00:11:25.950 --> 00:11:28.669 It sounds so confident sometimes. Overconfident. 00:11:28.769 --> 00:11:31.990 Huge pitfall. To counter that, you use skepticism 00:11:31.990 --> 00:11:35.110 prompts. Asking it to argue against itself. Pretty 00:11:35.110 --> 00:11:37.809 much. You force the AI to play devil's advocate. 00:11:38.210 --> 00:11:41.090 Ask it. What assumptions did you make here that 00:11:41.090 --> 00:11:44.549 might be wrong? Or why might sophisticated investors 00:11:44.549 --> 00:11:47.210 be selling this stock right now, even if it looks 00:11:47.210 --> 00:11:49.710 good on paper? Challenging his own conclusions. 00:11:49.870 --> 00:11:51.970 Building that critical challenge into the process, 00:11:52.029 --> 00:11:54.860 not just as an afterthought. That's how you aim 00:11:54.860 --> 00:11:56.840 for a sustainable edge, I think. Okay, so let's 00:11:56.840 --> 00:11:58.700 try and wrap this up, synthesize the big idea 00:11:58.700 --> 00:12:01.820 here. CGPT -5 seems like a genuine leap forward. 00:12:02.000 --> 00:12:04.259 It's making institutional -grade research much 00:12:04.259 --> 00:12:06.220 more accessible. Definitely feels that way. But 00:12:06.220 --> 00:12:07.840 it's not about just handing the keys over to 00:12:07.840 --> 00:12:10.659 the machine. It's more like a... A structured 00:12:10.659 --> 00:12:13.600 collaboration. Yeah, a partnership. Between human 00:12:13.600 --> 00:12:16.340 intuition, which sets the strategy, asks the 00:12:16.340 --> 00:12:19.580 right questions, and this advanced AI, which 00:12:19.580 --> 00:12:21.779 handles the massive scale of data processing 00:12:21.779 --> 00:12:24.080 and synthesis. That's a great way to put it. 00:12:24.100 --> 00:12:25.960 And the crucial takeaway, I think, no matter 00:12:25.960 --> 00:12:29.000 how smart this tech gets, is that you, the investor, 00:12:29.159 --> 00:12:31.700 you must still verify the critical data points. 00:12:31.899 --> 00:12:34.059 You have to understand your own personal risk 00:12:34.059 --> 00:12:36.720 tolerance. You have to manage your position sizing 00:12:36.720 --> 00:12:39.690 appropriately. The AI provides guidance, but 00:12:39.690 --> 00:12:42.009 the responsibility is still yours. Absolutely. 00:12:42.149 --> 00:12:44.669 The AI is your assistant, a powerful one, but 00:12:44.669 --> 00:12:47.549 it's never your master. You own the risk. So 00:12:47.549 --> 00:12:49.909 here's maybe a final thought to leave you with. 00:12:50.129 --> 00:12:52.750 If the AI can flawlessly analyze financials in 00:12:52.750 --> 00:12:55.490 seconds, if it can spot complex chart patterns 00:12:55.490 --> 00:12:58.409 instantly, calculate precise risk -reward ratios, 00:12:58.669 --> 00:13:01.610 all using auditable sources, what percentage 00:13:01.610 --> 00:13:03.429 of your investment decision process should still 00:13:03.429 --> 00:13:06.370 remain purely intuitive? That's a deep question. 00:13:06.779 --> 00:13:09.019 It's something worth exploring, I think, as you 00:13:09.019 --> 00:13:12.460 design your own systematic risk -managed approach 00:13:12.460 --> 00:13:15.440 in this new era. Where does human gut feel fit 00:13:15.440 --> 00:13:17.700 in now? We definitely encourage you to start 00:13:17.700 --> 00:13:19.779 thinking about structuring your own daily blueprint, 00:13:19.960 --> 00:13:22.299 maybe focusing first on those critical quality 00:13:22.299 --> 00:13:24.480 control and verification steps we talked about. 00:13:24.600 --> 00:13:27.139 Start small. Build the process. Exactly. We'll 00:13:27.139 --> 00:13:28.580 see you next time for the next Deep Dive.