WEBVTT 00:00:00.000 --> 00:00:04.259 Imagine an AI, one that doesn't just chat with 00:00:04.259 --> 00:00:06.960 you, but actually acts, updating spreadsheets 00:00:06.960 --> 00:00:08.820 automatically, sending those crucial notifications, 00:00:09.380 --> 00:00:11.339 maybe managing your digital data without you 00:00:11.339 --> 00:00:12.599 lifting a finger. What if you could build that 00:00:12.599 --> 00:00:15.980 yourself? Beat. That's really the profound power 00:00:15.980 --> 00:00:18.539 of AI agents. Welcome to the deep dive. This 00:00:18.539 --> 00:00:20.300 is where we try to cut through the noise, just 00:00:20.300 --> 00:00:22.539 killing complex topics down to the core of what 00:00:22.539 --> 00:00:24.920 truly matters. Today, we're taking a deep dive 00:00:24.920 --> 00:00:28.609 into the fascinating and pretty empowering world 00:00:28.609 --> 00:00:30.829 of AI agents. You've almost certainly interacted 00:00:30.829 --> 00:00:33.250 with tools like ChatGPT, right? You prompt it, 00:00:33.250 --> 00:00:34.609 it gives you something back. But what if you 00:00:34.609 --> 00:00:37.570 could move beyond just being a user? to becoming 00:00:37.570 --> 00:00:40.030 an architect, actually creating your own bespoke 00:00:40.030 --> 00:00:42.549 AI assistant. So today we're going to unpack 00:00:42.549 --> 00:00:44.789 the essential components that make an AI agent 00:00:44.789 --> 00:00:47.189 tick. We'll walk you through a surprisingly practical 00:00:47.189 --> 00:00:48.969 example of building one, kind of from the ground 00:00:48.969 --> 00:00:51.609 up. And then we'll explore why this isn't just 00:00:51.609 --> 00:00:54.229 a neat trick, but maybe a skill becoming utterly 00:00:54.229 --> 00:00:56.250 foundational for the future. The future of how 00:00:56.250 --> 00:00:58.070 we work, how we interact with tech. Get ready 00:00:58.070 --> 00:01:00.070 to shift your perspective, maybe from just a 00:01:00.070 --> 00:01:04.260 consumer of AI to its creator. Okay, so... Let's 00:01:04.260 --> 00:01:06.219 begin by really unpacking this idea. We're all 00:01:06.219 --> 00:01:07.859 familiar with chatbots. They're designed mostly 00:01:07.859 --> 00:01:11.579 to talk, to generate text. But an AI agent, that's 00:01:11.579 --> 00:01:13.519 a different beast entirely. It's purpose -built 00:01:13.519 --> 00:01:15.640 to perform concrete tasks in the digital world. 00:01:15.959 --> 00:01:17.719 What's the fundamental shift in capability we're 00:01:17.719 --> 00:01:19.599 talking about here? Yeah, what's truly fascinating 00:01:19.599 --> 00:01:21.780 here is precisely that shift. Think of it like 00:01:21.780 --> 00:01:25.340 this. ChatGQT can talk to you, answer your questions. 00:01:25.900 --> 00:01:28.340 An AI agent, though, can talk to you. Understand 00:01:28.340 --> 00:01:30.680 what you mean, then seamlessly turn around and 00:01:30.680 --> 00:01:33.079 talk to Google Sheets to actually do something 00:01:33.079 --> 00:01:35.739 concrete, update a record maybe. Or it could 00:01:35.739 --> 00:01:38.540 talk to Slack to send a message. It really moves 00:01:38.540 --> 00:01:41.400 beyond just conversation to actual execution. 00:01:41.560 --> 00:01:44.000 Right, execution. And to get that level of execution, 00:01:44.140 --> 00:01:46.680 it's not just one big black box, is it? It's 00:01:46.680 --> 00:01:49.560 composed of three essential elements, almost 00:01:49.560 --> 00:01:51.900 like a digital nervous system guiding its actions. 00:01:52.359 --> 00:01:54.909 What are these core components? Exactly. So first 00:01:54.909 --> 00:01:56.829 we have the brain. This is the large language 00:01:56.829 --> 00:01:59.769 model itself in LLM, maybe something like OpenAI's 00:01:59.769 --> 00:02:02.409 GPT -4. It's doing the heavy lifting, you know, 00:02:02.590 --> 00:02:04.370 understanding language, reasoning, generating 00:02:04.370 --> 00:02:07.069 responses. But crucially, for an agent to be 00:02:07.069 --> 00:02:10.330 truly useful, this brain needs memory. Without 00:02:10.330 --> 00:02:12.629 it, every single interaction is a completely 00:02:12.629 --> 00:02:14.569 fresh start. Imagine trying to have a coherent 00:02:14.569 --> 00:02:17.310 conversation with someone who instantly forgets 00:02:17.310 --> 00:02:19.750 everything you just said. Yeah, that sounds incredibly 00:02:19.750 --> 00:02:21.990 frustrating, like having amnesia between sentences, 00:02:21.990 --> 00:02:24.750 basically. Exactly. It makes the agent pretty 00:02:24.750 --> 00:02:28.189 useless for any complex multi -step task. Okay, 00:02:28.229 --> 00:02:30.530 so memory is key. A truly forgetful assistant 00:02:30.530 --> 00:02:34.110 would be, well, not very helpful. So with that 00:02:34.110 --> 00:02:36.689 memory layer in place, what then allows this 00:02:36.689 --> 00:02:39.569 brain to actually do things out there in the 00:02:39.569 --> 00:02:41.229 digital world? Ah, that's where the tools come 00:02:41.229 --> 00:02:43.569 in. These are effectively the hands of the agent. 00:02:43.669 --> 00:02:46.009 They let it interact with the outside world through 00:02:46.009 --> 00:02:50.090 what we call APIs. An API application programming 00:02:50.090 --> 00:02:52.610 interface. It's basically a standardized way 00:02:52.610 --> 00:02:55.330 for different software apps to talk to each other. 00:02:55.629 --> 00:02:57.169 So we're talking about integrating with services 00:02:57.169 --> 00:03:00.550 like Google Sheets, Slack, Notion, various databases, 00:03:00.849 --> 00:03:03.889 email platforms, really any digital service that 00:03:03.889 --> 00:03:06.030 offers an API. This is how your agent can read 00:03:06.030 --> 00:03:08.650 data, write new information, or modify existing 00:03:08.650 --> 00:03:11.659 records. Got it. The brain thinks and remembers, 00:03:11.800 --> 00:03:14.620 the tools act. What's the secret ingredient then, 00:03:14.740 --> 00:03:16.819 the thing that truly brings this agent to life 00:03:16.819 --> 00:03:19.259 and dictates how it uses those tools? Is there 00:03:19.259 --> 00:03:21.539 a kind of command center orchestrating it all? 00:03:21.639 --> 00:03:23.840 There absolutely is, and this is arguably the 00:03:23.840 --> 00:03:26.080 most critical part. We can call it the brain 00:03:26.080 --> 00:03:28.960 stem, the system prompt. Now, this isn't just 00:03:28.960 --> 00:03:31.219 a simple instruction like be helpful. No, it's 00:03:31.219 --> 00:03:34.439 a meticulously crafted set of detailed, clear 00:03:34.439 --> 00:03:37.000 guidelines you give to the brain. It defines 00:03:37.000 --> 00:03:39.680 the agent's entire role, its precise objectives, 00:03:39.919 --> 00:03:41.680 how it should behave in different situations, 00:03:41.680 --> 00:03:44.240 and most importantly, how and when it must use 00:03:44.240 --> 00:03:47.460 those tools. A really well -written system prompt. 00:03:47.879 --> 00:03:50.219 That's where your human intent literally breeds 00:03:50.219 --> 00:03:52.550 life into an otherwise generic language model. 00:03:53.069 --> 00:03:55.949 It transforms it into a truly intelligent, autonomous 00:03:55.949 --> 00:03:58.849 agent designed for a specific purpose. That's 00:03:58.849 --> 00:04:01.389 where the real leverage is in shaping its intelligence. 00:04:01.750 --> 00:04:05.289 OK, so if we boil that down, what's the core 00:04:05.289 --> 00:04:07.870 defining difference between a conventional chatbot 00:04:07.870 --> 00:04:10.550 you might use every day and a fully fledged AI 00:04:10.550 --> 00:04:12.750 agent? Well, simply put, an agent doesn't just 00:04:12.750 --> 00:04:15.370 converse. It takes concrete, economist actions 00:04:15.370 --> 00:04:17.670 in the digital realm based on that conversation. 00:04:17.870 --> 00:04:22.160 And that ability to take concrete action. That's 00:04:22.160 --> 00:04:24.620 what truly unlocks their power. OK, now let's 00:04:24.620 --> 00:04:26.920 move from the abstract to the actionable, because 00:04:26.920 --> 00:04:28.939 here's where it gets really interesting. The 00:04:28.939 --> 00:04:30.899 source material we're diving into today walks 00:04:30.899 --> 00:04:34.220 us through a fantastic, practical example, building 00:04:34.220 --> 00:04:37.600 a subscription tracker AI agent. It sounds simple, 00:04:37.699 --> 00:04:39.680 but it's incredibly useful, and it really kind 00:04:39.680 --> 00:04:42.459 of demystifies the whole process. How does this 00:04:42.459 --> 00:04:44.920 agent actually function from a user's perspective? 00:04:45.269 --> 00:04:47.329 It really is a perfect starter project, yeah. 00:04:47.949 --> 00:04:49.990 You interact with it using natural language, 00:04:50.089 --> 00:04:52.189 just like you would with any chatbot. For instance, 00:04:52.250 --> 00:04:54.189 you might just say, hey, I just subscribed to 00:04:54.189 --> 00:04:58.870 Spotify Premium for 120 ,000 VND per month. The 00:04:58.870 --> 00:05:01.870 agent then quietly goes to work and parses that 00:05:01.870 --> 00:05:04.149 message, intelligently pulling out the specific 00:05:04.149 --> 00:05:06.709 service name that cost the frequency. OK, but 00:05:06.709 --> 00:05:08.910 what if you forget a detail? Or maybe you're 00:05:08.910 --> 00:05:11.839 a bit vague. Does it just guess? or does it actually 00:05:11.839 --> 00:05:14.120 engage with you? That's a great question. If 00:05:14.120 --> 00:05:16.899 something's missing or if it's unclear, it's 00:05:16.899 --> 00:05:20.160 actually designed to ask for clarification. Hey, 00:05:20.220 --> 00:05:22.220 you mentioned Spotify. What was the cost again? 00:05:22.360 --> 00:05:24.579 Something like that. And then crucially, before 00:05:24.579 --> 00:05:26.860 it does anything irreversible, like writing to 00:05:26.860 --> 00:05:29.720 your spreadsheet, it asks for your explicit confirmation. 00:05:30.439 --> 00:05:34.540 Okay, add Spotify. 120k VND monthly, is that 00:05:34.540 --> 00:05:37.540 correct? That confirmation step is key for keeping 00:05:37.540 --> 00:05:40.279 you in control, maintaining transparency. Once 00:05:40.279 --> 00:05:42.899 you confirm, then it automatically adds a new 00:05:42.899 --> 00:05:45.519 row to a designated Google Sheet with all the 00:05:45.519 --> 00:05:48.079 correct structured information. And this basic 00:05:48.079 --> 00:05:50.629 project, it isn't just a novelty. It's a perfect 00:05:50.629 --> 00:05:53.490 foundational blueprint for way more complex real 00:05:53.490 --> 00:05:56.290 -world agents. Think automated expense management 00:05:56.290 --> 00:05:58.930 or streamlined customer support. That is fascinating. 00:05:59.370 --> 00:06:01.509 Simple but powerful. Yeah. So to build something 00:06:01.509 --> 00:06:03.569 like this, what are the absolute basics? The 00:06:03.569 --> 00:06:05.089 accounts or platforms you need to get your hands 00:06:05.089 --> 00:06:07.329 on? Right. The essentials. You'll need access 00:06:07.329 --> 00:06:09.949 to N8AN. That's the workflow automation tool 00:06:09.949 --> 00:06:12.470 used in the example. You'll need an OpenAI API 00:06:12.470 --> 00:06:15.069 key for the brain. and of course a Google account 00:06:15.069 --> 00:06:17.850 to connect your Google Sheets. Gotcha. NEN, OpenAI, 00:06:17.970 --> 00:06:21.230 API, Google account. Now let's talk setup configuring 00:06:21.230 --> 00:06:23.670 that brain and equipping those hands within NEN. 00:06:23.990 --> 00:06:26.560 Where do you even begin in the workflow? Okay, 00:06:26.560 --> 00:06:28.399 so you start by setting up what's called a chat 00:06:28.399 --> 00:06:32.000 trigger in NEN. Think of this as your main communication 00:06:32.000 --> 00:06:34.360 gateway, right? The entry point for your conversations 00:06:34.360 --> 00:06:37.279 with the agent. From there, you add the central 00:06:37.279 --> 00:06:40.060 AI agent node itself. This is where all the intelligence 00:06:40.060 --> 00:06:42.199 will live. Then you connect the language model. 00:06:42.639 --> 00:06:44.939 The source material suggests a lightweight GPT 00:06:44.939 --> 00:06:48.920 model, maybe something like GPT 4 .1 mini. Sorry. 00:06:49.120 --> 00:06:51.740 The source actually recommended GPT 3 .5 Turbo, 00:06:52.160 --> 00:06:54.379 or a specialized mini model for beginners. It 00:06:54.379 --> 00:06:56.860 gives a good balance of performance, speed, and 00:06:56.860 --> 00:07:00.300 cost. And you connect your OpenAI API key here. 00:07:00.439 --> 00:07:02.019 It's worth pointing out that's a separate access 00:07:02.019 --> 00:07:03.639 key. It's different from just having a regular 00:07:03.639 --> 00:07:06.620 chat GPT plus subscription. OK. And as we touched 00:07:06.620 --> 00:07:09.459 on earlier, a raw LLM is essentially stateless 00:07:09.459 --> 00:07:11.680 by default. It forgets everything. It seems like 00:07:11.680 --> 00:07:13.959 a huge problem. So what's a critical step to 00:07:13.959 --> 00:07:16.920 give it a working memory to allow for fluid ongoing 00:07:16.920 --> 00:07:19.300 conversations? That's right. By default, they 00:07:19.300 --> 00:07:22.639 have that immediate amnesia. So to overcome this, 00:07:22.800 --> 00:07:25.759 we add a simple memory component. By setting 00:07:25.759 --> 00:07:28.779 a context window length, say, maybe around 14 00:07:28.779 --> 00:07:31.459 interactions back, it lets the agent remember 00:07:31.459 --> 00:07:33.740 the previous parts of your conversation. This 00:07:33.740 --> 00:07:37.019 is absolutely vital for a useful assistant. It 00:07:37.019 --> 00:07:38.839 stops it from asking the same things over and 00:07:38.839 --> 00:07:40.560 over or just losing track of what you're trying 00:07:40.560 --> 00:07:43.480 to do. It allows for that natural flowing dialogue 00:07:43.480 --> 00:07:46.360 without racking up huge processing costs for 00:07:46.360 --> 00:07:48.899 you either. Makes sense. So once the brain can 00:07:48.899 --> 00:07:51.319 think and remember, you then give it its hands, 00:07:51.560 --> 00:07:53.379 specifically a Google sheet in this case, how 00:07:53.379 --> 00:07:55.339 do you set that part up and connect it? Right, 00:07:55.500 --> 00:07:58.160 the hands. First, you just set up a simple subscription 00:07:58.160 --> 00:08:00.540 tracker sheet in Google Docs. Give it clear columns 00:08:00.540 --> 00:08:02.680 like service name, cost, status, whatever you 00:08:02.680 --> 00:08:06.040 need. Then, back in AGN, you link the sheet using 00:08:06.040 --> 00:08:09.439 the Google Sheets tool. The key here is configuring 00:08:09.439 --> 00:08:12.079 the tool. You tell it to append row for new entries. 00:08:12.439 --> 00:08:14.300 Then you map the columns in your sheet to the 00:08:14.300 --> 00:08:16.850 data the AI needs to fill in. You'll notice a 00:08:16.850 --> 00:08:19.629 little sparkle icon in AAN next to the fields. 00:08:20.050 --> 00:08:22.990 That sparkle icon tells the AI to infer the data 00:08:22.990 --> 00:08:25.269 for those columns from what you, the user, typed 00:08:25.269 --> 00:08:27.610 in. It's pretty smart. Oh, and it's also a good 00:08:27.610 --> 00:08:30.709 idea to rename the tool to something clear, like 00:08:30.709 --> 00:08:33.149 add new subscription. That helps the AI understand 00:08:33.149 --> 00:08:35.970 exactly what that tool is for. OK, mapping the 00:08:35.970 --> 00:08:39.029 columns, using the sparkle icon. And then comes 00:08:39.029 --> 00:08:41.409 what you call the true magic, right? The brain 00:08:41.409 --> 00:08:43.330 stem, the system prompt. This is basically the 00:08:43.330 --> 00:08:45.639 detailed job description for your agent. How 00:08:45.639 --> 00:08:48.019 do you even go about crafting something so critical? 00:08:48.179 --> 00:08:50.320 It sounds kind of intimidating. It is critical, 00:08:50.320 --> 00:08:52.360 but it doesn't have to be intimidating. It really 00:08:52.360 --> 00:08:55.080 is an art form, though. The source material suggests 00:08:55.080 --> 00:08:58.559 a brilliant approach, actually. Use ChatGPT itself 00:08:58.559 --> 00:09:01.320 to help you write the prompt. You feed ChatGPT 00:09:01.320 --> 00:09:03.299 the details of your workflow, what you want the 00:09:03.299 --> 00:09:05.320 agent to do, and you give it a strict structure 00:09:05.320 --> 00:09:09.029 for the prompt you need back. You tell it. Define 00:09:09.029 --> 00:09:11.409 the agent's precise role, its core objective, 00:09:11.649 --> 00:09:13.950 the entire interaction flow definitely, including 00:09:13.950 --> 00:09:15.970 that crucial confirmation step we talked about, 00:09:16.009 --> 00:09:18.990 specific tool usage rules, and even detailed 00:09:18.990 --> 00:09:21.750 data formatting instructions. The amazing thing 00:09:21.750 --> 00:09:24.389 is, even a tiny change in wording in this prompt 00:09:24.389 --> 00:09:26.710 can dramatically alter how the agent behaves. 00:09:27.149 --> 00:09:29.429 So once ChatGPT helps generate that powerful 00:09:29.429 --> 00:09:32.370 prompt, you just copy it into the AI agent node's 00:09:32.370 --> 00:09:35.039 system message option in NAN. Simple as that. 00:09:35.139 --> 00:09:37.840 Wow. Using AI to bootstrap the AI's instructions 00:09:37.840 --> 00:09:41.080 as ever. And then the moment of truth. You test 00:09:41.080 --> 00:09:43.120 it. How does that usually play out? Testing is 00:09:43.120 --> 00:09:45.259 absolutely essential, yeah. You type something 00:09:45.259 --> 00:09:48.299 like, add my new Netflix subscription. It costs 00:09:48.299 --> 00:09:52.600 260 ,000 VND a month. The agent analyzes your 00:09:52.600 --> 00:09:55.039 input, summarizes it back to you, asks for confirmation. 00:09:55.580 --> 00:09:59.500 OK, add Netflix, 260k VND monthly. Sound right. 00:09:59.690 --> 00:10:02.789 And only after you explicitly say yes does it 00:10:02.789 --> 00:10:05.250 activate that Google Sheets tool. And boom, a 00:10:05.250 --> 00:10:07.970 new row appears in your spreadsheet. It's incredibly 00:10:07.970 --> 00:10:10.409 satisfying when it works. And the power of a 00:10:10.409 --> 00:10:12.629 well -crafted prompt really shines through when 00:10:12.629 --> 00:10:14.950 it handles ambiguity, too. If you leave something 00:10:14.950 --> 00:10:17.509 out, it should ask, what's the cost? That shows 00:10:17.509 --> 00:10:20.250 the prompt is working intelligently. OK, so if 00:10:20.250 --> 00:10:22.230 I had to distill everything we've discussed about 00:10:22.230 --> 00:10:24.909 building this agent, what's the single most critical 00:10:24.909 --> 00:10:27.309 part for really making it intelligent? The system 00:10:27.309 --> 00:10:30.440 prompt. It's the operating brain. Its clarity 00:10:30.440 --> 00:10:32.419 fundamentally determines the agent's intelligence 00:10:32.419 --> 00:10:35.000 and effectiveness. Simple as that. Mid -roll 00:10:35.000 --> 00:10:37.039 sponsor read. All right. Once you have those 00:10:37.039 --> 00:10:39.399 basics down, the real fun begins, I imagine. 00:10:40.100 --> 00:10:41.799 Leveling up your agent. What are some of the 00:10:41.799 --> 00:10:43.960 first ways you can make it even smarter? more 00:10:43.960 --> 00:10:46.759 robust? Yeah, good question. First, a really 00:10:46.759 --> 00:10:49.419 common enhancement is duplicate detection. You 00:10:49.419 --> 00:10:51.379 wouldn't want an intelligent assistant adding 00:10:51.379 --> 00:10:55.019 the same Netflix subscription twice, right? So 00:10:55.019 --> 00:10:57.360 to implement this, you'd add a second Google 00:10:57.360 --> 00:11:00.740 Sheets tool. This one you configure to get rows, 00:11:00.980 --> 00:11:02.960 maybe rename it check existing subscriptions. 00:11:03.659 --> 00:11:05.899 Then you update your system prompt again. The 00:11:05.899 --> 00:11:08.490 prompt is key. to always check for duplicates 00:11:08.490 --> 00:11:10.730 before adding anything new. If it finds one, 00:11:10.850 --> 00:11:13.450 the prompt tells it to ask you, the user, what 00:11:13.450 --> 00:11:15.470 to do. Hey, I see Netflix already. Do you want 00:11:15.470 --> 00:11:17.750 to update it or add this one anyway? Ah, OK. 00:11:18.029 --> 00:11:21.230 Checking first. And building on that, what about 00:11:21.230 --> 00:11:24.110 making it capable of modifying existing entries, 00:11:24.149 --> 00:11:26.409 not just adding new ones? That seems like a natural 00:11:26.409 --> 00:11:28.730 next step. Exactly. That's update functionality. 00:11:28.750 --> 00:11:30.850 So you add a third Google Sheets tool. This one's 00:11:30.850 --> 00:11:33.429 set to update row, maybe named update subscription. 00:11:33.830 --> 00:11:36.029 And this is where your system prompt gets even 00:11:36.029 --> 00:11:37.850 more sophisticated. You have to instruct the 00:11:37.850 --> 00:11:40.450 agent on the precise logic. When should it use 00:11:40.450 --> 00:11:43.529 the add tool versus when should it use the update 00:11:43.529 --> 00:11:46.129 tool? It's usually based on your response after 00:11:46.129 --> 00:11:48.639 that duplicate check. layer of usefulness for 00:11:48.639 --> 00:11:51.539 sure. Whoa. Hang on. Imagine scaling this further. 00:11:51.600 --> 00:11:53.779 You could easily integrate, say, a FLAC tool 00:11:53.779 --> 00:11:55.799 to notify your finance channel, whatever new 00:11:55.799 --> 00:11:58.139 subscription is added, or maybe a Notion tool 00:11:58.139 --> 00:12:00.500 to create detailed notes linked to each entry 00:12:00.500 --> 00:12:04.659 automatically. It's really like stacking Lego 00:12:04.659 --> 00:12:06.679 blocks of data and actions, all controlled by 00:12:06.679 --> 00:12:09.210 just talking to it. Imagine orchestrating multiple 00:12:09.210 --> 00:12:11.190 applications seamlessly, having them talk to 00:12:11.190 --> 00:12:13.269 each other to automate entire workflows. The 00:12:13.269 --> 00:12:15.330 possibilities really open up there. They absolutely 00:12:15.330 --> 00:12:17.409 do. And as you venture deeper into building these 00:12:17.409 --> 00:12:19.649 agents, there are some essential golden roles 00:12:19.649 --> 00:12:22.289 for success, let's say. First, and this might 00:12:22.289 --> 00:12:24.830 sound obvious, but trust me, it's crucial. Say 00:12:24.830 --> 00:12:28.730 frequently, like CMDC Trial plus S should become 00:12:28.730 --> 00:12:32.259 pure muscle memory. Losing work. Especially when 00:12:32.259 --> 00:12:35.620 you're deep and tweaking a prompt is just incredibly 00:12:35.620 --> 00:12:37.740 frustrating. I still wrestle with pumped drift 00:12:37.740 --> 00:12:40.340 myself, you know, where you think you've nailed 00:12:40.340 --> 00:12:42.620 the perfect pumped and then suddenly the agent 00:12:42.620 --> 00:12:44.659 starts doing something completely unexpected, 00:12:45.000 --> 00:12:46.940 sending you down a debugging rabbit hole for 00:12:46.940 --> 00:12:49.980 hours. Saving often lets me backtrack easily 00:12:49.980 --> 00:12:52.000 to that last known good configuration before 00:12:52.000 --> 00:12:54.559 things went sideways. It's like a digital undo 00:12:54.559 --> 00:12:56.659 button for your sanity. Seriously. Oh, yeah, 00:12:56.659 --> 00:12:58.419 that's a classic. Definitely been there in other 00:12:58.419 --> 00:13:01.139 contexts. And then the wisdom of starts Simple. 00:13:01.419 --> 00:13:04.639 Expand incrementally. Precisely. Don't try to 00:13:04.639 --> 00:13:06.679 build Roman a day, right? Don't start with an 00:13:06.679 --> 00:13:09.179 agent juggling 10 tools and super complex logic. 00:13:09.600 --> 00:13:11.500 Get a single core function working perfectly 00:13:11.500 --> 00:13:14.860 first. Then slowly, methodically, add layers 00:13:14.860 --> 00:13:18.720 of complexity. Test each layer. Also, and we 00:13:18.720 --> 00:13:20.779 really can't stress this enough, the system prompt 00:13:20.779 --> 00:13:23.820 is key. Spend the most time refining it. Even 00:13:23.820 --> 00:13:26.179 a tiny change in wording, a misplaced comma, 00:13:26.460 --> 00:13:28.539 a subtle tweak in instruction can dramatically 00:13:28.539 --> 00:13:30.559 alter the agent's behavior and performance. It's 00:13:30.559 --> 00:13:32.960 that sensitive. And finally, test thoroughly. 00:13:33.399 --> 00:13:35.120 Don't just test the happy path where everything 00:13:35.120 --> 00:13:37.799 works perfectly. Try ambiguous inputs. Give it 00:13:37.799 --> 00:13:40.440 incorrect data. Even throw edge cases at it that 00:13:40.440 --> 00:13:42.240 it isn't explicitly designed for just to see 00:13:42.240 --> 00:13:44.500 how it reacts. That's how you uncover vulnerabilities. 00:13:44.659 --> 00:13:46.360 Right. Pushes boundaries. And a very practical 00:13:46.360 --> 00:13:48.700 tip for anyone when diving into this, monitor 00:13:48.700 --> 00:13:52.159 API costs. Yes, absolutely. Every time your agent 00:13:52.159 --> 00:13:54.559 thinks, meaning it makes a call to the OpenAI 00:13:54.559 --> 00:13:57.639 API, you incur a small fee. Those tiny fees can 00:13:57.639 --> 00:13:59.740 add up really quickly, especially with frequent 00:13:59.740 --> 00:14:01.700 testing or if the agent becomes heavily used. 00:14:02.059 --> 00:14:04.139 So always start with those lightweight or mini 00:14:04.139 --> 00:14:06.740 models we mentioned. And keep a close eye on 00:14:06.740 --> 00:14:09.679 your usage dashboard provided by OpenAI or whichever 00:14:09.679 --> 00:14:12.080 provider you use. It just saves you from any 00:14:12.080 --> 00:14:14.139 nasty, unexpected surprises on your build demo 00:14:14.139 --> 00:14:17.710 line. Good call. So for someone who's just starting 00:14:17.710 --> 00:14:21.129 dipping their toes into building AI agents, what's 00:14:21.129 --> 00:14:23.870 the single most important guiding rule to remember 00:14:23.870 --> 00:14:26.629 throughout their journey? Start simple, make 00:14:26.629 --> 00:14:29.070 sure your system prompt is crystal clear, and 00:14:29.070 --> 00:14:31.549 test rigorously. That's the foundation. You know, 00:14:31.549 --> 00:14:34.440 if we connect this to the bigger picture. learning 00:14:34.440 --> 00:14:37.120 this skill, building these agents. It isn't just 00:14:37.120 --> 00:14:39.279 about connecting apps or automating a few tedious 00:14:39.279 --> 00:14:41.799 tasks. It's profoundly akin to, say, learning 00:14:41.799 --> 00:14:44.580 programming back in the 80s or 90s or maybe database 00:14:44.580 --> 00:14:47.559 management in the 2000s. This ability to converse 00:14:47.559 --> 00:14:50.019 with, instruct, and orchestrate intelligent agents, 00:14:50.259 --> 00:14:52.080 it really feels like a foundational skill for 00:14:52.080 --> 00:14:54.120 the AI -driven world we are rapidly entering. 00:14:54.960 --> 00:14:57.320 You're essentially moving from being just a passive 00:14:57.320 --> 00:15:01.179 AI consumer to an active AI creator. And with 00:15:01.179 --> 00:15:03.990 that comes complete data control. which is huge, 00:15:04.710 --> 00:15:07.450 incredible process transparency, near infinite 00:15:07.450 --> 00:15:10.129 customization possibilities, and perhaps most 00:15:10.129 --> 00:15:13.169 importantly, you gain a deep first -hand understanding 00:15:13.169 --> 00:15:16.649 of both AI's immense capabilities and its current 00:15:16.649 --> 00:15:19.549 limitations. Ultimately, it's really about empowering 00:15:19.549 --> 00:15:22.200 you in this new technological landscape. Yeah, 00:15:22.259 --> 00:15:24.840 this deep dive really highlights how AI technology, 00:15:25.019 --> 00:15:27.340 when understood and wielded by individuals, truly 00:15:27.340 --> 00:15:29.740 empowers us. It's not necessarily about replacement, 00:15:29.899 --> 00:15:31.899 but enhancement. Your journey, should you choose 00:15:31.899 --> 00:15:34.220 to embark on it, is only just beginning. Which 00:15:34.220 --> 00:15:35.860 really raises an important question for you, 00:15:35.860 --> 00:15:38.379 the listener. What task, what tedious digital 00:15:38.379 --> 00:15:40.980 chore in your own life or work could be fundamentally 00:15:40.980 --> 00:15:43.539 transformed by your very own custom AI agent? 00:15:43.779 --> 00:15:46.039 Yeah, think about it. Experiment. Break things. 00:15:46.259 --> 00:15:48.460 Fix them. Don't be afraid to dive in and get 00:15:48.460 --> 00:15:50.580 your hands dirty. Have fun with that creative 00:15:50.580 --> 00:15:53.879 process. Every complex world -changing AI system 00:15:53.879 --> 00:15:56.059 started with just a simple idea and a simple 00:15:56.059 --> 00:15:57.759 first step. Go out there and build something 00:15:57.759 --> 00:16:00.259 amazing. We hope this deep dive has given you 00:16:00.259 --> 00:16:03.220 a useful shortcut to being well -informed and, 00:16:03.279 --> 00:16:05.700 maybe more importantly, inspired you to explore 00:16:05.700 --> 00:16:07.759 what's truly possible when you shift from just 00:16:07.759 --> 00:16:10.879 consuming AI to actually creating with it. Ochiiro 00:16:10.879 --> 00:16:11.279 music.