WEBVTT 00:00:00.000 --> 00:00:02.480 Imagine building your own personal AI analyst. 00:00:02.720 --> 00:00:05.780 It sifts through complex financial data, generates 00:00:05.780 --> 00:00:08.660 charts, delivers a full market briefing instantly. 00:00:09.060 --> 00:00:12.400 And the best part, you build it without writing 00:00:12.400 --> 00:00:15.980 a single line of code. Welcome to the Deep Dive. 00:00:16.839 --> 00:00:19.039 Today we're exploring something really fascinating, 00:00:19.320 --> 00:00:22.739 a guide on building a technical analysis AI agent. 00:00:22.960 --> 00:00:25.199 Yeah, and using a no -code platform called NA10 00:00:25.199 --> 00:00:29.260 to do it. Right. Our mission is to see how anyone... 00:00:29.359 --> 00:00:31.699 really can create this sophisticated tool think 00:00:31.699 --> 00:00:35.500 of it like a uh a digital pit crew for analyzing 00:00:35.500 --> 00:00:38.719 stocks crypto forex all of it we'll look at what 00:00:38.719 --> 00:00:40.780 it does how it's built the tools it uses building 00:00:40.780 --> 00:00:42.700 it fixing it and then the bigger picture right 00:00:42.700 --> 00:00:45.420 real world use and the future of this whole no 00:00:45.420 --> 00:00:47.560 code ai thing okay so let's unpack this first 00:00:47.560 --> 00:00:49.359 part this isn't just some basic chatbot we're 00:00:49.359 --> 00:00:51.579 talking about no not at all this is an ai agent 00:00:51.579 --> 00:00:54.100 it's capable of serious autonomous financial 00:00:54.100 --> 00:00:56.219 analysis and what's really interesting is that 00:00:56.219 --> 00:00:58.399 billing it isn't just for pro developers anymore 00:00:58.829 --> 00:01:01.210 Exactly. That's the revolution here. This guide 00:01:01.210 --> 00:01:04.549 shows how N8, this no -code platform, makes it 00:01:04.549 --> 00:01:06.609 accessible. It kind of democratizes the whole 00:01:06.609 --> 00:01:08.849 process. And it sounds incredibly versatile. 00:01:09.030 --> 00:01:11.629 It analyzes, what, cryptocurrencies like Bitcoin, 00:01:11.989 --> 00:01:15.549 Ethereum? Yep. Major forex pairs like EURUSD, 00:01:15.670 --> 00:01:18.750 even stocks like Tesla or Apple. A really wide 00:01:18.750 --> 00:01:21.849 range. Wow. And it doesn't just pull raw data. 00:01:22.140 --> 00:01:24.859 No, it generates real -time candlestick charts, 00:01:25.040 --> 00:01:27.700 grabs the latest market news, and then puts it 00:01:27.700 --> 00:01:29.859 all together. A professional grade briefing, 00:01:30.060 --> 00:01:32.359 basically. The digital pit crew idea. Yeah, it 00:01:32.359 --> 00:01:34.620 jumps into action when you need it, ready to 00:01:34.620 --> 00:01:38.040 go. So the process involves choosing the right 00:01:38.040 --> 00:01:40.939 tools for technical snapshots. Right, gathering 00:01:40.939 --> 00:01:43.500 intel from different sources, like news feeds. 00:01:43.579 --> 00:01:45.620 And then pulling it all together. synthesizing 00:01:45.620 --> 00:01:48.480 it. Exactly. The output is a full market debrief. 00:01:48.500 --> 00:01:50.859 You get the charts, the technical analysis, market 00:01:50.859 --> 00:01:53.219 sentiment from the news, maybe even some trading 00:01:53.219 --> 00:01:56.859 insights. But, and this is important, this is 00:01:56.859 --> 00:01:59.599 purely for educational purposes, definitely not 00:01:59.599 --> 00:02:02.180 financial advice. Of course. Good disclaimer. 00:02:02.680 --> 00:02:07.040 So this digital pit crew, how does it decide 00:02:07.040 --> 00:02:10.699 what to do first? Does it just guess? No, the 00:02:10.699 --> 00:02:13.259 agent's brain, its core logic, actually looks 00:02:13.259 --> 00:02:15.659 at your request and intelligently picks the best 00:02:15.659 --> 00:02:18.300 first step, the right tool to start the analysis. 00:02:18.680 --> 00:02:21.400 Okay, a smart start. Now, all this magic happens 00:02:21.400 --> 00:02:25.340 on N8n. What exactly is N8n? Why call it a no 00:02:25.340 --> 00:02:28.780 -code command center? So N8n is this really powerful 00:02:28.780 --> 00:02:31.580 workflow platform, runs in your browser. The 00:02:31.580 --> 00:02:33.710 best way to think about it is like... Digital 00:02:33.710 --> 00:02:36.330 Legos. Digital Legos. I like that. Yeah. You 00:02:36.330 --> 00:02:38.189 connect these pre -built blocks, they're called 00:02:38.189 --> 00:02:40.789 nodes, to create pretty complex automations. 00:02:40.830 --> 00:02:43.150 And for most of it, you don't need to write actual 00:02:43.150 --> 00:02:45.270 code. That really makes it sound less daunting. 00:02:45.430 --> 00:02:47.349 So it's got a visual builder. Yeah. Drag and 00:02:47.349 --> 00:02:49.650 drop. Exactly. You drag, drop, connect the nodes. 00:02:49.770 --> 00:02:51.789 And you can test each step as you go, see the 00:02:51.789 --> 00:02:53.810 results right away. Real -time testing. Makes 00:02:53.810 --> 00:02:56.370 sense. Plus, a huge advantage is its integrations. 00:02:56.370 --> 00:02:58.430 It connects to hundreds of different services, 00:02:58.669 --> 00:03:01.889 APIs. It's a real hub. So even if you're not 00:03:01.889 --> 00:03:04.530 a coding wizard, You can visually build some 00:03:04.530 --> 00:03:07.409 pretty complicated stuff. That's the idea. It 00:03:07.409 --> 00:03:10.150 democratizes building these complex automations. 00:03:10.289 --> 00:03:12.509 Okay, so what's the biggest benefit of that visual 00:03:12.509 --> 00:03:15.310 workflow building? It lets you create complex 00:03:15.310 --> 00:03:17.849 automations just by connecting visual blocks. 00:03:18.189 --> 00:03:20.389 Let's dive a bit deeper then. Under the hood. 00:03:21.009 --> 00:03:24.129 How does this agent actually, you know, think? 00:03:24.310 --> 00:03:27.030 It's described as a multi -agent system, like 00:03:27.030 --> 00:03:30.370 mission control. Precisely. The heart of it is 00:03:30.370 --> 00:03:33.310 the AI agent node. That's the brain handles the 00:03:33.310 --> 00:03:36.349 reasoning, the decisions, delegates tasks. It 00:03:36.349 --> 00:03:38.870 runs the show. And it gets its instructions from 00:03:38.870 --> 00:03:41.020 a prompt. Like maybe directly from a Telegram 00:03:41.020 --> 00:03:42.960 message someone sends. Yeah, often mapped straight 00:03:42.960 --> 00:03:45.219 from Telegram. And for its intelligence, the 00:03:45.219 --> 00:03:47.319 actual thinking part, it connects to a chat model. 00:03:47.539 --> 00:03:50.580 Like ChatGPT or Claude. Right. And using a provider 00:03:50.580 --> 00:03:54.319 like OpenRouter here is kind of a pro move. Why 00:03:54.319 --> 00:03:56.139 is that? It gives you flexibility. You can easily 00:03:56.139 --> 00:03:58.879 switch between models, Claude, ChatGPT, Gemini, 00:03:59.020 --> 00:04:01.319 others, lets you pick the best one for the job, 00:04:01.400 --> 00:04:03.120 maybe the most cost -effective one at that moment. 00:04:03.300 --> 00:04:05.520 Oh, okay. Optimization. Then there's the prime 00:04:05.520 --> 00:04:09.199 directive or system message. Sounds serious. 00:04:09.680 --> 00:04:11.599 It kind of is. It's like it's standing orders, 00:04:11.800 --> 00:04:14.259 non -negotiable rules. And for this financial 00:04:14.259 --> 00:04:16.839 agent. The prime directive forces a specific 00:04:16.839 --> 00:04:19.540 sequence. First, technical analysis. Second, 00:04:19.759 --> 00:04:23.120 gather news. Third, synthesize both into a full 00:04:23.120 --> 00:04:25.600 assessment before replying. Got it. Step one, 00:04:25.639 --> 00:04:28.899 step two, step three, marching orders. Exactly. 00:04:29.139 --> 00:04:32.250 And it also has memory. A mission log. How does 00:04:32.250 --> 00:04:34.589 that work? Yeah, super important. There's a simple 00:04:34.589 --> 00:04:37.209 memory node. It usually uses the user's Telegram 00:04:37.209 --> 00:04:40.350 chat ID as a key. So it remembers the last few 00:04:40.350 --> 00:04:43.209 messages, say the last five, in that specific 00:04:43.209 --> 00:04:45.990 chat. Why is memory so important for this AI 00:04:45.990 --> 00:04:48.470 agent? It allows the agent to understand context 00:04:48.470 --> 00:04:50.290 and handle follow -up questions effectively. 00:04:50.670 --> 00:04:53.209 Without it, every message is brand new. With 00:04:53.209 --> 00:04:56.329 memory, it feels much smarter. Right. Context 00:04:56.329 --> 00:04:58.509 is everything. Makes it feel less like a tool 00:04:58.509 --> 00:05:01.339 and more like an assistant. Okay, now this next 00:05:01.339 --> 00:05:03.899 part sounds really cool. The tools. This is what 00:05:03.899 --> 00:05:05.819 makes it an agent, not just a chatbot, right? 00:05:05.920 --> 00:05:09.259 Chatbots talk, agents do things. Exactly. Tools 00:05:09.259 --> 00:05:11.360 are the game changers. The first one discussed 00:05:11.360 --> 00:05:13.980 is the chart paparazzi tool. Chart paparazzi. 00:05:14.000 --> 00:05:16.360 Yeah. It acts like a photographer and an art 00:05:16.360 --> 00:05:19.160 critic combined. Takes a real -time chart snapshot 00:05:19.160 --> 00:05:21.720 and then analyzes what it sees. And the mission 00:05:21.720 --> 00:05:24.040 briefing for this tool, the description, tells 00:05:24.040 --> 00:05:26.600 the main agent how to use it. Needs the symbol 00:05:26.600 --> 00:05:29.459 of prompt. Chat ID. Right. And a really smart 00:05:29.459 --> 00:05:31.860 thing to do, a pro move, is to actually list 00:05:31.860 --> 00:05:34.740 valid symbols inside the tool's description itself. 00:05:35.100 --> 00:05:37.800 Ah. So the AI knows up front what it can actually 00:05:37.800 --> 00:05:41.019 look up, like AAPL, BTC, USD. Precisely. Gives 00:05:41.019 --> 00:05:43.339 it the intelligence it needs. Prevents errors. 00:05:43.660 --> 00:05:46.459 So it knows exactly what to snap pictures of. 00:05:46.560 --> 00:05:49.939 Smart. And the back end calls. ChartImage .com. 00:05:50.060 --> 00:05:53.100 Yep. It uses the ChartImage .com API to get a 00:05:53.100 --> 00:05:56.410 professional trading view chart screenshot. Then, 00:05:56.449 --> 00:05:59.649 and this is key, it sends that image to an AI 00:05:59.649 --> 00:06:02.410 vision model. Like GPT -4 with vision. What's 00:06:02.410 --> 00:06:04.589 an AI vision model, simply? It's an AI that can 00:06:04.589 --> 00:06:06.810 see and interpret images, understand what's in 00:06:06.810 --> 00:06:08.110 the picture. So it looks at the chart patterns. 00:06:08.509 --> 00:06:10.930 Exactly. It analyzes the visual data on the chart. 00:06:11.269 --> 00:06:13.569 Chartimage .com is kind of the secret sauce for 00:06:13.569 --> 00:06:15.769 getting those nice real -time screenshots easily. 00:06:16.149 --> 00:06:18.889 Okay, cool. Then tool two, the field reporter. 00:06:19.509 --> 00:06:23.019 This gives the why behind the chart. News and 00:06:23.019 --> 00:06:25.019 sentiment. Yeah, because just looking at charts, 00:06:25.040 --> 00:06:27.420 pure technical analysis can be misleading sometimes. 00:06:27.519 --> 00:06:30.899 You need the context. So this tool calls a financial 00:06:30.899 --> 00:06:34.800 news API, pulls in up -to -the -minute news related 00:06:34.800 --> 00:06:37.959 to that specific asset, helps explain the price 00:06:37.959 --> 00:06:40.579 moves. Makes sense. And the guide mentions a 00:06:40.579 --> 00:06:43.459 golden rule of tool design. Yes. The quality 00:06:43.459 --> 00:06:45.980 of your tool descriptions is paramount. A good 00:06:45.980 --> 00:06:48.680 one needs specifics. what parameters it needs, 00:06:48.819 --> 00:06:51.180 examples, when the agent should use it, what 00:06:51.180 --> 00:06:53.740 the output looks like. Clarity is key for the 00:06:53.740 --> 00:06:56.339 AI to use it right. Absolutely. And for a real 00:06:56.339 --> 00:06:59.279 pro upgrade, you can even add another AI node 00:06:59.279 --> 00:07:02.279 inside the news tools workflow. To do what? To 00:07:02.279 --> 00:07:04.920 generate a market sentiment score. Imagine getting 00:07:04.920 --> 00:07:07.319 a score, say, from minus 10, very bearish, to 00:07:07.319 --> 00:07:09.879 plus 10, very bullish, based on the news it just 00:07:09.879 --> 00:07:12.300 gathered. Whoa. A real -time sentiment score 00:07:12.300 --> 00:07:15.139 for any asset. That's like a crystal ball, but, 00:07:15.160 --> 00:07:16.939 you know, based on actual data. Kind of, yeah. 00:07:17.060 --> 00:07:19.259 It distills a lot of news into one quick number. 00:07:19.519 --> 00:07:22.120 That's powerful. Okay, what's the most crucial 00:07:22.120 --> 00:07:24.480 element, then, in making these tools effective 00:07:24.480 --> 00:07:27.579 for the AI? The quality and clarity of the tool's 00:07:27.579 --> 00:07:30.439 description are the most important factor. Right. 00:07:30.519 --> 00:07:33.360 Let's get practical. The hands -on part, building 00:07:33.360 --> 00:07:35.629 this thing. Like assembling a high -performance 00:07:35.629 --> 00:07:38.589 car on an assembly line. Okay, yeah. Phase one 00:07:38.589 --> 00:07:41.550 is the foundation, building the chassis, the 00:07:41.550 --> 00:07:44.189 core engine. You start with a telegram trigger 00:07:44.189 --> 00:07:46.410 node. That's where requests come in. Then add 00:07:46.410 --> 00:07:48.790 the AI agent node, the brain. Connect your chat 00:07:48.790 --> 00:07:51.170 model. Right. And don't forget the simple memory 00:07:51.170 --> 00:07:53.449 node using the telegram chat ID for context. 00:07:53.750 --> 00:07:56.360 Crucial first step. do an initial test before 00:07:56.360 --> 00:07:58.620 adding all the fancy tools just make sure the 00:07:58.620 --> 00:08:00.860 basic trigger brain and memory are talking to 00:08:00.860 --> 00:08:03.699 each other test early test often good advice 00:08:03.699 --> 00:08:06.420 my dad used to say that about car engines so 00:08:06.420 --> 00:08:08.839 phase two is the specialists hiring the teams 00:08:08.839 --> 00:08:10.899 yeah this is where you build the sub workflows 00:08:10.899 --> 00:08:13.819 for your tools like the chart paparazzi or field 00:08:13.819 --> 00:08:16.779 reporter in the main ai agent node you use the 00:08:16.779 --> 00:08:20.180 call n8n workflow tool option and give each tool 00:08:20.180 --> 00:08:22.800 a really descriptive name So for the chart tool, 00:08:23.000 --> 00:08:25.720 the subworkflow would have inputs called chartimage 00:08:25.720 --> 00:08:29.480 .com using an HTTP request node. And then send 00:08:29.480 --> 00:08:31.579 the image to the AI Vision node for analysis. 00:08:31.759 --> 00:08:34.919 Okay. Then phase three, this pro -level API technique, 00:08:35.220 --> 00:08:40.279 the secret weapon, using CURL commands. Ah, yes. 00:08:41.230 --> 00:08:43.929 This is brilliant. For complex APIs, instead 00:08:43.929 --> 00:08:46.570 of figuring out all the settings manually, you 00:08:46.570 --> 00:08:49.850 can actually ask an AI like ChatGPT, give me 00:08:49.850 --> 00:08:52.450 the CURL command for this API call. What's the 00:08:52.450 --> 00:08:54.909 CURL command again, basically? It's just a text 00:08:54.909 --> 00:08:56.809 -based instruction for making a web request. 00:08:57.029 --> 00:08:58.950 Tells the computer exactly how to talk to the 00:08:58.950 --> 00:09:01.250 API. Okay, and you take that text? And you paste 00:09:01.250 --> 00:09:04.690 it directly into an NAN HTTP request node. There's 00:09:04.690 --> 00:09:06.649 an import option. And what happens? Boom, it 00:09:06.649 --> 00:09:09.009 automatically configures everything. The URL, 00:09:09.230 --> 00:09:11.509 the headers, the request. body, all the parameters, 00:09:11.710 --> 00:09:14.570 all set up for you. That's amazing. Whoa. Imagine 00:09:14.570 --> 00:09:17.320 how much time that CRL trick can save. avoids 00:09:17.320 --> 00:09:19.419 fiddling with all those manual settings. It's 00:09:19.419 --> 00:09:21.360 a huge time saver, prevents so many little errors. 00:09:21.620 --> 00:09:23.419 Yeah, I still wrestle with Promptriff myself 00:09:23.419 --> 00:09:26.559 sometimes, you know, getting the AI to consistently 00:09:26.559 --> 00:09:29.500 do what you want. So any shortcut like that is 00:09:29.500 --> 00:09:31.940 a blessing. What's the real benefit of using 00:09:31.940 --> 00:09:34.960 the CURL command trick? It automatically configures 00:09:34.960 --> 00:09:38.340 complex API requests, saving significant time 00:09:38.340 --> 00:09:40.659 and reducing errors. Sponsor read would occur 00:09:40.659 --> 00:09:42.779 here in a real episode. Okay, so you're building 00:09:42.779 --> 00:09:44.919 this complex system. Things are bound to go wrong 00:09:44.919 --> 00:09:46.889 sometimes, let's be real. This section is like 00:09:46.889 --> 00:09:50.570 the field medic guide for fixing problems. Exactly. 00:09:50.809 --> 00:09:53.009 The triage process. It helps you spot common 00:09:53.009 --> 00:09:56.330 issues, common injuries, things like API key 00:09:56.330 --> 00:09:58.330 errors. Maybe the data format isn't quite right 00:09:58.330 --> 00:10:00.909 between nodes. Parameter mismatches. Right. Or 00:10:00.909 --> 00:10:03.470 maybe you're hitting rate limits on an API you're 00:10:03.470 --> 00:10:05.750 using. Happens all the time. And the first aid 00:10:05.750 --> 00:10:08.409 kit is the debugging process. Yeah, it's systematic. 00:10:08.629 --> 00:10:11.629 Test each node one by one using N8N's execute 00:10:11.629 --> 00:10:14.500 step. Check the data flowing between them. Read 00:10:14.500 --> 00:10:16.860 the error messages carefully. Sometimes you can 00:10:16.860 --> 00:10:19.340 even paste the error into ChatGPT and ask it 00:10:19.340 --> 00:10:22.200 for help troubleshooting. Oh, using AI to fix 00:10:22.200 --> 00:10:25.019 the AI workflow. Nice. I've definitely spent 00:10:25.019 --> 00:10:27.360 hours chasing a missing comma or something tiny 00:10:27.360 --> 00:10:29.399 like that. Oh, yeah. It's rarely perfect on the 00:10:29.399 --> 00:10:31.620 first try. That's why you have to embrace iteration. 00:10:31.980 --> 00:10:35.159 Build, test, refine, repeat. It's just part of 00:10:35.159 --> 00:10:37.899 the process for anything complex. Okay, so you've 00:10:37.899 --> 00:10:39.779 got a working prototype. Now the professional 00:10:39.779 --> 00:10:43.419 playbook. Scaling up. Taking it from prototype 00:10:43.419 --> 00:10:46.899 to mass production. Kind of, yeah. Scaling the 00:10:46.899 --> 00:10:49.759 factory is about adding more capability, more 00:10:49.759 --> 00:10:52.659 tools, like maybe different chart timeframes, 00:10:52.759 --> 00:10:54.740 more technical indicators, pulling news from 00:10:54.740 --> 00:10:57.019 multiple sources, adding social media sentiment 00:10:57.019 --> 00:11:00.100 analysis, even tracking a user's personal portfolio. 00:11:00.279 --> 00:11:03.080 Lots of possibilities. Then optimizing the assembly 00:11:03.080 --> 00:11:06.460 line, performance and security. Crucial. You 00:11:06.460 --> 00:11:09.360 need to think about API rate limits, costs, making 00:11:09.360 --> 00:11:11.519 sure it responds quickly for the user, handling 00:11:11.519 --> 00:11:14.519 lots of users at once. And security. Non -negotiable, 00:11:14.620 --> 00:11:17.899 securely storing your API keys, maybe user authentication, 00:11:18.200 --> 00:11:20.879 and definitely having a clear financial disclaimer, 00:11:21.059 --> 00:11:23.639 protecting yourself and your users. Like building 00:11:23.639 --> 00:11:26.559 a fortress around your awesome AI. Makes sense. 00:11:26.779 --> 00:11:29.879 And finally, quality control. This is ongoing. 00:11:30.679 --> 00:11:33.909 Monitoring if the APIs you rely on are up. watching 00:11:33.909 --> 00:11:36.710 for errors, getting user feedback, and periodically 00:11:36.710 --> 00:11:39.350 checking if the tools in the AI model are still 00:11:39.350 --> 00:11:42.529 accurate and performing well. So beyond just 00:11:42.529 --> 00:11:45.269 fixing errors, what's a key part of maintaining 00:11:45.269 --> 00:11:48.190 a professional AI system? Ongoing monitoring, 00:11:48.490 --> 00:11:51.230 collecting user feedback, and regular validation 00:11:51.230 --> 00:11:54.110 of performance. All right, the end game. Turning 00:11:54.110 --> 00:11:56.629 this powerful prototype into something real, 00:11:56.730 --> 00:11:59.850 a real -world asset. Yeah, and the use cases 00:11:59.850 --> 00:12:02.129 are pretty broad. Financial advisors could use 00:12:02.129 --> 00:12:04.970 it to offer automated analysis to clients. Educational 00:12:04.970 --> 00:12:07.090 platforms. Definitely. For interactive demos 00:12:07.090 --> 00:12:09.470 showing market concepts with live data powered 00:12:09.470 --> 00:12:11.789 by the agent. Trading communities on Discord 00:12:11.789 --> 00:12:14.429 or Telegram could offer instant analysis to members. 00:12:14.690 --> 00:12:16.970 Imagine the value add there. Instant insights 00:12:16.970 --> 00:12:19.110 right in the chat. It's kind of democratizing 00:12:19.110 --> 00:12:21.710 financial expertise. And advanced integrations, 00:12:21.789 --> 00:12:23.649 like embedding it somewhere. Sure, you could 00:12:23.649 --> 00:12:25.889 deploy it as a Slack bot, Discord bot, embed 00:12:25.889 --> 00:12:28.129 it in a web dashboard. You could even connect 00:12:28.129 --> 00:12:31.309 it to personal financial data for portfolio tracking 00:12:31.309 --> 00:12:34.429 risk assessment. Potentially, yeah. With the 00:12:34.429 --> 00:12:36.690 right permissions and security, you could build 00:12:36.690 --> 00:12:39.429 custom reporting and analysis based on a user's 00:12:39.429 --> 00:12:42.909 actual holdings. Okay, zooming out a bit. The 00:12:42.909 --> 00:12:46.899 bigger picture. The future of no -code AI. This 00:12:46.899 --> 00:12:50.480 combination, visual builders like NAN plus AI 00:12:50.480 --> 00:12:54.240 assistance, it's dramatically lowering the barrier 00:12:54.240 --> 00:12:56.539 to entry for creating really professional AI 00:12:56.539 --> 00:12:59.379 systems. So non -technical builders get an edge. 00:12:59.539 --> 00:13:02.039 A massive advantage, potentially. Faster speed 00:13:02.039 --> 00:13:04.580 to market, lower costs, more flexibility compared 00:13:04.580 --> 00:13:07.220 to traditional code -heavy development teams 00:13:07.220 --> 00:13:10.440 sometimes. Whoa. Imagine the impact on financial 00:13:10.440 --> 00:13:13.720 accessibility. if almost anyone can build tools 00:13:13.720 --> 00:13:16.299 like this. The future really belongs to the fast 00:13:16.299 --> 00:13:18.080 and the adaptable, doesn't it? Seems that way. 00:13:18.200 --> 00:13:20.600 It allows innovation for more places. So what's 00:13:20.600 --> 00:13:23.159 the biggest shift no -code AI brings to building 00:13:23.159 --> 00:13:26.259 solutions? It dramatically lowers barriers, allowing 00:13:26.259 --> 00:13:28.039 non -technical builders to create professional 00:13:28.039 --> 00:13:30.659 systems quickly. So learning this stuff, no -code 00:13:30.659 --> 00:13:32.659 AI agent development, is not just about building 00:13:32.659 --> 00:13:34.899 one cool tool. It's about getting a foundational 00:13:34.899 --> 00:13:37.159 skill, right? Something increasingly valuable. 00:13:37.610 --> 00:13:39.990 Absolutely. The guide lays out some immediate 00:13:39.990 --> 00:13:42.529 actions for your first flight. Download free 00:13:42.529 --> 00:13:44.909 workflow templates. Join a community forum for 00:13:44.909 --> 00:13:47.250 help. Set up free trial accounts for services 00:13:47.250 --> 00:13:50.350 like Chart Image or an AI model provider. And 00:13:50.350 --> 00:13:53.509 just start simple. Build confidence with basic 00:13:53.509 --> 00:13:55.789 tests. There's a learning path outlined too. 00:13:56.129 --> 00:13:58.509 Beginner to expert. Yeah, you start with basic 00:13:58.509 --> 00:14:00.809 workflows, then learn to build custom tools, 00:14:01.090 --> 00:14:03.730 maybe link multiple agents together, and eventually 00:14:03.730 --> 00:14:06.389 you could be building commercial -grade AI services. 00:14:06.830 --> 00:14:08.889 It's a whole new career path, potentially, just 00:14:08.889 --> 00:14:11.629 waiting for curious minds. It really is. It's 00:14:11.629 --> 00:14:14.009 a shift in thinking, too. You go from just using 00:14:14.009 --> 00:14:17.129 AI. To becoming a creator of AI solutions. Exactly. 00:14:17.230 --> 00:14:20.250 You get the skills to rapidly prototype, test, 00:14:20.429 --> 00:14:23.509 deploy AI for almost any business need you can 00:14:23.509 --> 00:14:26.009 think of. The tools are there. The community's 00:14:26.009 --> 00:14:28.200 supportive. Sounds like the opportunities are 00:14:28.200 --> 00:14:30.240 pretty unlimited. What's the key mindset shift 00:14:30.240 --> 00:14:32.519 for those starting this journey? Moving from 00:14:32.519 --> 00:14:35.340 being a user of AI to becoming a creator of AI 00:14:35.340 --> 00:14:38.240 solutions. So today, we've seen how building 00:14:38.240 --> 00:14:41.399 these powerful, autonomous AI agents for complex 00:14:41.399 --> 00:14:44.259 stuff like financial analysis, it's actually 00:14:44.259 --> 00:14:46.299 within reach for many more people now. Yeah, 00:14:46.340 --> 00:14:48.820 platforms like NA10 let you be the architect. 00:14:48.940 --> 00:14:51.220 You design the brain, the prime directive, the 00:14:51.220 --> 00:14:53.299 memory. And a coupon with specialized tools, 00:14:53.600 --> 00:14:57.340 social forces, for charting. news analysis. It's 00:14:57.340 --> 00:14:59.919 not just about building a neat gadget. It's about 00:14:59.919 --> 00:15:02.620 being able to innovate quickly, deploy sophisticated 00:15:02.620 --> 00:15:05.960 AI, and that changes who gets to build the future. 00:15:06.120 --> 00:15:08.919 Well said. We really encourage you to explore 00:15:08.919 --> 00:15:11.700 these ideas. Maybe even try out a no -code platform 00:15:11.700 --> 00:15:14.500 yourself. If you can connect those digital Legos, 00:15:14.519 --> 00:15:16.860 what complex challenge could you solve with an 00:15:16.860 --> 00:15:19.399 AI agent? Join us next time for another deep 00:15:19.399 --> 00:15:22.500 dive into the ideas shaping our world. Outro 00:15:22.500 --> 00:15:22.860 music.