WEBVTT 00:00:00.000 --> 00:00:02.680 Welcome to the Deep Dive. Today, we're aiming 00:00:02.680 --> 00:00:05.759 to really help transform your coding workflow. 00:00:06.400 --> 00:00:08.220 We're not just scratching the surface of chat 00:00:08.220 --> 00:00:10.839 GPT. We're going deep, looking at how you can 00:00:10.839 --> 00:00:14.560 actually harness its power for complex development 00:00:14.560 --> 00:00:18.100 tasks. Our goal, give you a shortcut basically 00:00:18.100 --> 00:00:21.420 to understanding how AI can be a serious copilot, 00:00:21.679 --> 00:00:23.920 saving you time, boosting your work quality. 00:00:24.679 --> 00:00:27.579 Our insights today, they're drawn from advanced 00:00:27.579 --> 00:00:31.140 chat GPT prompts for devs, optimized coding by 00:00:31.140 --> 00:00:33.859 Neil Phan. That just came out June 19th, 2025. 00:00:34.240 --> 00:00:36.280 Very recent, yeah. So get ready. We're about 00:00:36.280 --> 00:00:38.899 to unpack some really specific, actionable strategies. 00:00:39.380 --> 00:00:42.159 Everything from automation to, well, designing 00:00:42.159 --> 00:00:45.140 whole system architectures. Okay, let's unpack 00:00:45.140 --> 00:00:46.799 this. Well, what's really fascinating here, I 00:00:46.799 --> 00:00:49.219 think, is it's not just about the tools. It's 00:00:49.219 --> 00:00:51.200 the sheer cognitive load, right? The repetitive 00:00:51.200 --> 00:00:53.140 stuff developers deal with every day. Totally. 00:00:53.299 --> 00:00:55.520 And this deep dive, it tackles that head on. 00:00:55.619 --> 00:00:57.640 The article isn't just, you know, give me a code 00:00:57.640 --> 00:01:00.979 snippet. It's about getting high quality actionable 00:01:00.979 --> 00:01:05.019 results actionable across what is it 15 key development 00:01:05.019 --> 00:01:08.640 areas we're talking real benefits saving hours 00:01:08.640 --> 00:01:12.640 sure but also improving code quality maybe even 00:01:12.640 --> 00:01:14.120 solving problems you're kind of stuck on right 00:01:14.120 --> 00:01:16.019 now okay so let's kick things off with something 00:01:16.019 --> 00:01:20.299 familiar setting up CI CD pipelines from scratch. 00:01:20.459 --> 00:01:22.640 That's often a big headache, isn't it? Oh, absolutely. 00:01:22.680 --> 00:01:25.780 It's a huge pain point. Is AI genuinely a game 00:01:25.780 --> 00:01:28.480 changer here, or is it just like a nice to have 00:01:28.480 --> 00:01:30.700 tool? No, I'd say it's pretty much a game changer, 00:01:30.780 --> 00:01:33.120 especially for that initial setup. We've all 00:01:33.120 --> 00:01:35.959 spent, you know, hours wrangling with CircleCI 00:01:35.959 --> 00:01:38.280 or Render or whatever platform, trying to get 00:01:38.280 --> 00:01:40.620 that ComSig just right. The source shows how 00:01:40.620 --> 00:01:42.939 these advanced prompts can build a complete pipeline. 00:01:43.079 --> 00:01:45.140 Not just the config file, but setup guides too. 00:01:45.200 --> 00:01:46.909 Okay. The whole point is automating in the build, 00:01:46.930 --> 00:01:49.269 test, deploy cycle. You just tell it about your 00:01:49.269 --> 00:01:51.709 project tech stack, repo, where it's deployed, 00:01:52.209 --> 00:01:54.250 security needs. And then what you want the pipeline 00:01:54.250 --> 00:01:56.609 to actually do, build, test, security check, 00:01:56.829 --> 00:01:59.510 deploy, maybe documentation. And the example 00:01:59.510 --> 00:02:02.629 they use is super practical. A Python app, Django, 00:02:02.870 --> 00:02:05.590 PostgreSQL, Bitbucket, deploying to render, needs 00:02:05.590 --> 00:02:09.169 a safety check. And boom, out comes a CircleCI 00:02:09.169 --> 00:02:11.840 YAML file, ready to go. It's almost like having 00:02:11.840 --> 00:02:14.240 an expert right there doing it for you. Exactly. 00:02:14.300 --> 00:02:16.000 And think about it. It's not just saving your 00:02:16.000 --> 00:02:19.219 hours. It changes the team's agility. Right. 00:02:19.699 --> 00:02:22.719 What if you free up a whole day, every month, 00:02:22.960 --> 00:02:25.939 for every developer? What could your team build 00:02:25.939 --> 00:02:28.259 with that extra time? That's the real shift. 00:02:28.639 --> 00:02:31.900 Faster cycles, better testing, clear docs. OK. 00:02:31.900 --> 00:02:35.020 So sticking with workflow, once CI -CD is smooth, 00:02:35.199 --> 00:02:37.979 the next tangle is off in Git, right? Messy histories, 00:02:38.319 --> 00:02:41.389 branch conflicts, nightmare fuel. Sometimes. 00:02:41.650 --> 00:02:44.330 Uh -huh. We've all been there. How does AI help 00:02:44.330 --> 00:02:46.729 untangle that mess? Yeah, we've all stared at 00:02:46.729 --> 00:02:48.870 merge conflicts late at night wishing for a magic 00:02:48.870 --> 00:02:52.169 wand. AI isn't magic, but it gets pretty darn 00:02:52.169 --> 00:02:54.409 close for this stuff. Okay. ChatGPT can actually 00:02:54.409 --> 00:02:57.189 look at your repository state, suggest the steps 00:02:57.189 --> 00:02:59.990 to fix things, and give you the precise Git commands. 00:03:00.090 --> 00:03:02.590 Wow. It's designed for those tricky bits, resolving 00:03:02.590 --> 00:03:05.289 conflicts, cleaning up history. You describe 00:03:05.289 --> 00:03:07.409 the situation, your platform, say GitLab and 00:03:07.409 --> 00:03:09.550 what you want to achieve. Merge, squash commits, 00:03:09.650 --> 00:03:11.719 whatever. Right. So imagine you've got conflicts 00:03:11.719 --> 00:03:14.659 between, like, feature payment and main on GitLab. 00:03:15.180 --> 00:03:17.539 And feature payment has a ton of messy commits. 00:03:17.719 --> 00:03:19.759 Yeah, it happens all the time. Chat GPT guides 00:03:19.759 --> 00:03:22.360 you through the exact sequence. Get checkout, 00:03:22.520 --> 00:03:25.180 get fetch, get merge. Then it tells you how to 00:03:25.180 --> 00:03:28.259 spot the conflicts. Manually fix them, add commit. 00:03:28.539 --> 00:03:31.439 Step by step. Then the commands to squash those 00:03:31.439 --> 00:03:34.460 messy commits into one clean one. Get reset soft. 00:03:34.960 --> 00:03:38.300 Get commit -desham. Then push. check out main, 00:03:38.539 --> 00:03:41.039 pull, merge main, push main. It's like having 00:03:41.039 --> 00:03:43.439 a Git expert whispering in your ear. That's really 00:03:43.439 --> 00:03:45.979 useful. And just to mention for anyone listening, 00:03:46.159 --> 00:03:47.819 we'll put that full command list in the show 00:03:47.819 --> 00:03:49.960 notes so you can just copy paste. Perfect. So 00:03:49.960 --> 00:03:52.819 it resolves conflicts, cleans up history efficiently, 00:03:53.439 --> 00:03:55.560 gives you the right Git commands, really helps 00:03:55.560 --> 00:03:57.419 manage your repo, especially on something like 00:03:57.419 --> 00:03:59.819 GitLab. Exactly. So what does this really mean 00:03:59.819 --> 00:04:02.520 day to day? Less time fighting Git, more time 00:04:02.520 --> 00:04:04.719 actually coding. Right. And once your Git is 00:04:04.719 --> 00:04:07.409 clean and CICD is smooth, You're building faster. 00:04:08.409 --> 00:04:11.310 But is that fast code also performant code? Ah, 00:04:11.530 --> 00:04:14.129 good point. Finding and fixing inefficient code. 00:04:14.490 --> 00:04:17.029 That's another common, often frustrating challenge. 00:04:17.290 --> 00:04:19.629 It can really kill the user experience. Definitely. 00:04:19.769 --> 00:04:22.069 And this is where these advanced prompts can 00:04:22.069 --> 00:04:25.629 really make a difference. They analyze your code, 00:04:26.050 --> 00:04:28.610 find performance bottlenecks, and suggest specific 00:04:28.610 --> 00:04:32.009 optimizations. The goal is tackling things like 00:04:32.009 --> 00:04:34.329 slow database queries. You give it the language, 00:04:34.490 --> 00:04:37.110 the code snippet, the environment, Node .js on 00:04:37.110 --> 00:04:39.829 Vercell, maybe, and the problem, like a slow 00:04:39.829 --> 00:04:42.769 API response. The source uses a great example. 00:04:43.250 --> 00:04:46.350 A user's API in Node, using SuperBase on Vercell, 00:04:46.470 --> 00:04:49.199 taking like Five seconds plus for 10k record 00:04:49.199 --> 00:04:51.920 just because of a basic select. Yeah, that's 00:04:51.920 --> 00:04:54.000 bad. So what does it suggest? Well, the optimizations 00:04:54.000 --> 00:04:56.819 are super actionable. First, limit columns and 00:04:56.819 --> 00:04:59.699 rows. Use specific super base methods like select 00:04:59.699 --> 00:05:02.459 ID, name, email, dot range. That cuts down data 00:05:02.459 --> 00:05:04.519 transfer big time. OK, it makes sense. Second, 00:05:04.639 --> 00:05:06.959 add an index to the users table. Like create 00:05:06.959 --> 00:05:09.720 index, index user's name, on user's name, speeds 00:05:09.720 --> 00:05:12.339 up searches, filters, basic stuff, but easy to 00:05:12.339 --> 00:05:15.500 forget. And third, caching. Use Redis, maybe. 00:05:16.079 --> 00:05:19.540 Cache those query results for an hour. That drastically 00:05:19.540 --> 00:05:22.240 cuts down, hits to SuperBase, gets response time 00:05:22.240 --> 00:05:26.079 under, say, 100 meters. Wow. From over five seconds 00:05:26.079 --> 00:05:28.800 to under 100 meters. That's huge. It really is. 00:05:28.980 --> 00:05:31.579 You get accurate, ready -to -use optimization 00:05:31.579 --> 00:05:33.959 code. Perfect for bigger apps, especially on 00:05:33.959 --> 00:05:35.800 Vercel with SuperBase. It makes you think, right, 00:05:36.199 --> 00:05:37.759 what part of your app could use a performance 00:05:37.759 --> 00:05:41.300 check like this? Exactly. Food for thought. OK, 00:05:41.480 --> 00:05:43.899 moving on. Unit tests. We know they're vital. 00:05:44.199 --> 00:05:47.240 Catch bugs early, ensure code works. But writing 00:05:47.240 --> 00:05:49.180 them, especially covering all the edge cases, 00:05:49.839 --> 00:05:52.720 that takes time. A lot of time. Oh, yeah. It 00:05:52.720 --> 00:05:54.500 can feel like a drag sometimes, even though it's 00:05:54.500 --> 00:05:57.970 important. So how detailed can AI get here? Can 00:05:57.970 --> 00:06:00.970 it really handle the tricky edge cases? Surprisingly 00:06:00.970 --> 00:06:02.889 detailed. That's why these prompts are so valuable 00:06:02.889 --> 00:06:05.230 here. They generate comprehensive test cases. 00:06:05.250 --> 00:06:08.430 The whole idea is writing unit tests for a specific 00:06:08.430 --> 00:06:10.430 function or module. You just give it the language, 00:06:10.550 --> 00:06:12.269 the function name, the testing library. Jest 00:06:12.269 --> 00:06:15.050 is the example here. And the prompt asks for 00:06:15.050 --> 00:06:18.610 at least three test cases. Normal, edge, edge. 00:06:18.850 --> 00:06:21.069 So think about a calculated discount function 00:06:21.069 --> 00:06:24.449 in Node .js using Jest. The output gives you 00:06:24.439 --> 00:06:28.000 Specific tests, normal case, calculated discount 00:06:28.000 --> 00:06:31.819 120, returns 80. Makes sense. Edge case, 0 % 00:06:31.819 --> 00:06:34.459 discount, calculated discount 50, returns 50. 00:06:34.740 --> 00:06:38.259 Still simple. But then the important one, invalid 00:06:38.259 --> 00:06:41.300 inputs. Calling it with 100, 220, should throw 00:06:41.300 --> 00:06:44.139 an invalid input error. Ah, catching those type 00:06:44.139 --> 00:06:47.720 errors. Crucial. Exactly. It ensures robust coverage 00:06:47.720 --> 00:06:51.589 and does it efficiently. So. You get unit tests 00:06:51.589 --> 00:06:54.149 generated fast, covering key scenarios, including 00:06:54.149 --> 00:06:57.329 those vital edge cases, accurate just code, boost 00:06:57.329 --> 00:06:59.550 reliability in your node projects. That's a win. 00:07:00.110 --> 00:07:02.470 Okay, so we've got efficient code, good tests, 00:07:03.149 --> 00:07:05.110 solid building blocks. But how do they all fit 00:07:05.110 --> 00:07:07.269 together? System architecture, that feels like 00:07:07.269 --> 00:07:09.410 a big one. Crafting those design templates takes 00:07:09.410 --> 00:07:11.430 serious effort. It really does. It's often a 00:07:11.430 --> 00:07:13.649 very involved process. How much heavy lifting 00:07:13.649 --> 00:07:16.610 can AI actually do for architecture design? Quite 00:07:16.610 --> 00:07:18.990 a bit, actually. More than you might think. The 00:07:18.990 --> 00:07:21.170 source shows prompts generating full architecture 00:07:21.170 --> 00:07:24.069 designs, diagrams, technologies, the work. Really? 00:07:24.310 --> 00:07:26.709 Full designs? Yeah. The idea is create a whole 00:07:26.709 --> 00:07:30.230 template. You feed it system info type, requirements, 00:07:30.769 --> 00:07:33.410 tech stack. It proposes an architecture, lists 00:07:33.410 --> 00:07:36.189 key components, how they interact. and gives 00:07:36.189 --> 00:07:39.050 you a diagram. A diagram too? How? Using PlantUML 00:07:39.050 --> 00:07:42.170 syntax. It clever describes diagrams in simple 00:07:42.170 --> 00:07:44.649 text. So you can edit it, version control it 00:07:44.649 --> 00:07:47.629 like code. Huh, PlantUML. Okay. So the example 00:07:47.629 --> 00:07:50.430 is an online learning app on Vercel, needs 5K 00:07:50.430 --> 00:07:53.370 concurrent users, secure video, payments, Node 00:07:53.370 --> 00:07:56.430 .js, React, SuperBase. Right. The prompt suggests 00:07:56.430 --> 00:08:00.519 microservices. details the components, API gateway, 00:08:00.699 --> 00:08:03.259 user service, video, quiz, payment services, 00:08:03.939 --> 00:08:06.339 and the plant UAML shows users hitting React, 00:08:06.680 --> 00:08:09.240 going via the gateway to the services, SuperBase, 00:08:09.600 --> 00:08:13.060 Stripe. Wow. That generates clear designs fast 00:08:13.060 --> 00:08:15.699 and editable diagrams you can stick right in 00:08:15.699 --> 00:08:17.459 your docs. It seems perfect for that kind of 00:08:17.459 --> 00:08:19.360 app on Vercel SuperBase. It's a fantastic starting 00:08:19.360 --> 00:08:22.060 point. I have to ask. Are there pitfalls? Can 00:08:22.060 --> 00:08:24.259 you just trust an AI -generated architecture 00:08:24.259 --> 00:08:26.319 or does it sometimes miss things? That's a really 00:08:26.319 --> 00:08:28.139 important question. It's brilliant for getting 00:08:28.139 --> 00:08:30.800 that initial blueprint, that structure, but no, 00:08:30.860 --> 00:08:33.500 I wouldn't just blindly deploy it. You absolutely 00:08:33.500 --> 00:08:36.159 need human expertise to validate it. Does it 00:08:36.159 --> 00:08:39.539 really meet subtle business needs? Unique scaling 00:08:39.539 --> 00:08:42.600 issues, specific security policies your company 00:08:42.600 --> 00:08:44.840 has. Right, the nuances. Exactly. Think of it 00:08:44.840 --> 00:08:46.980 as a super smart co -pilot, not the autopilot. 00:08:47.360 --> 00:08:49.720 It builds the scaffolding fast so you can focus 00:08:49.720 --> 00:08:51.720 on the critical human refinement. That makes 00:08:51.720 --> 00:08:54.580 perfect sense. A powerful assistant, not a replacement. 00:08:55.460 --> 00:08:58.100 OK, speaking of complex stuff. Yeah. Integrating 00:08:58.100 --> 00:09:02.149 third party APIs. Always fun, right? Yeah. Authentication, 00:09:02.429 --> 00:09:04.570 error handling, performance. Yeah, it could be 00:09:04.570 --> 00:09:06.590 intricate. Lots of documentation reading. So 00:09:06.590 --> 00:09:08.909 how do prompts help here? Well, the source explains 00:09:08.909 --> 00:09:10.750 they can generate the integration code itself, 00:09:11.149 --> 00:09:13.750 including robust error handling and performance 00:09:13.750 --> 00:09:16.129 optimizations. OK. The goal is just streamlining 00:09:16.129 --> 00:09:18.809 it. Give it your project info, API name, what 00:09:18.809 --> 00:09:21.350 it does, your tech stack. It spits out integration 00:09:21.350 --> 00:09:24.190 code, handles common errors, suggests things 00:09:24.190 --> 00:09:27.139 like caching or rate limiting. Gotcha. The example 00:09:27.139 --> 00:09:30.679 is Stripe payments in a Node .js app. Express 00:09:30.679 --> 00:09:33.480 SuperBase on Vercell. Pretty standard setup. 00:09:33.580 --> 00:09:36.179 Right. And the generated code includes the Stripe 00:09:36.179 --> 00:09:38.919 payment intents .create call plus updating the 00:09:38.919 --> 00:09:41.860 order status in SuperBase. Nice. But crucially, 00:09:42.100 --> 00:09:45.039 it shows error handling. Catching specific Stripe 00:09:45.039 --> 00:09:48.100 errors like card declined or invalid API key. 00:09:48.200 --> 00:09:50.860 That's key. Handling errors properly. Definitely. 00:09:51.039 --> 00:09:53.950 And for optimization? It uses express rate limit 00:09:53.950 --> 00:09:56.509 to cap request to the payment endpoint, prevents 00:09:56.509 --> 00:09:59.809 abuse, keeps things stable. So faster, safer, 00:10:00.110 --> 00:10:03.049 Stripe integration, clear error handling, performance 00:10:03.049 --> 00:10:06.090 considered, ideal for node apps on Verzal. Exactly. 00:10:06.190 --> 00:10:09.049 Imagine integrating multiple services that efficiently. 00:10:09.370 --> 00:10:12.149 Cuts down research time massively. Yeah, no kidding. 00:10:12.509 --> 00:10:14.450 And that connects right into automating other 00:10:14.450 --> 00:10:17.049 repetitive tasks, things like backups, maybe 00:10:17.049 --> 00:10:21.610 deployments, monitoring, essential, but... Tedious. 00:10:21.710 --> 00:10:23.669 Duper tedious. The kind of thing everyone puts 00:10:23.669 --> 00:10:26.049 off. Can prompts generate scripts for that too? 00:10:26.149 --> 00:10:28.250 Yes, absolutely. Complete automation scripts 00:10:28.250 --> 00:10:30.309 with error handling and optimization baked in. 00:10:30.370 --> 00:10:32.070 Okay. The goal is just creating an efficient 00:10:32.070 --> 00:10:34.590 script for your specific task. Describe the task, 00:10:34.850 --> 00:10:37.470 platform OS, tools, services involved, and your 00:10:37.470 --> 00:10:40.090 preferred language, like Bash or Python. Right. 00:10:40.230 --> 00:10:42.389 The practical requirements specify needing good 00:10:42.389 --> 00:10:44.830 error handling and maybe security optimizations 00:10:44.830 --> 00:10:47.669 like encrypting backup files. Smart. The example 00:10:47.669 --> 00:10:50.730 given is backing up a super base database. Yeah. 00:10:50.860 --> 00:10:54.240 which is Postgres, right, to AWS S3, using a 00:10:54.240 --> 00:10:57.120 bash script on Linux with the AWS and SudoBase 00:10:57.120 --> 00:10:59.700 CLIs. OK, walk me through that script logic. 00:10:59.860 --> 00:11:02.440 It's pretty solid. It uses PGDump to export the 00:11:02.440 --> 00:11:05.980 database, then gzip to compress it, then GPG. 00:11:06.090 --> 00:11:09.570 with AES -256 encryption using a passphrase for 00:11:09.570 --> 00:11:13.409 security. License secure. Then AUS S3CP to upload 00:11:13.409 --> 00:11:16.730 the encrypted compressed file to S3. It also 00:11:16.730 --> 00:11:19.090 handles creating directories, checks for errors 00:11:19.090 --> 00:11:21.950 at each step, and cleans up temporary files afterward. 00:11:22.159 --> 00:11:24.960 a full secure solution. So automated, secure, 00:11:25.139 --> 00:11:27.740 efficient backups, concise script, clear error 00:11:27.740 --> 00:11:30.159 handling, perfect for SuperBase and S3 users, 00:11:30.440 --> 00:11:32.440 takes a critical chore off your plate. Exactly, 00:11:32.620 --> 00:11:34.539 frees you up. Okay, let's shift from operations 00:11:34.539 --> 00:11:36.919 back to planning. That very first step, analyzing 00:11:36.919 --> 00:11:39.259 user requirements. They can be so vague sometimes. 00:11:39.340 --> 00:11:40.879 Oh, tell me about it. Make it like Facebook, 00:11:40.960 --> 00:11:43.659 but for dogs, you know. Uh -huh, exactly. Trying 00:11:43.659 --> 00:11:45.580 to hit a moving target in fog, so are you saying 00:11:45.580 --> 00:11:47.740 AI can actually cut through that fog, take vague 00:11:47.740 --> 00:11:49.940 requirements and give us specs? It really can 00:11:49.940 --> 00:11:52.740 help clarify things significantly. Advanced prompts 00:11:52.740 --> 00:11:55.019 analyze those requirements, pull out key features, 00:11:55.179 --> 00:11:57.200 and create concrete specifications. How does 00:11:57.200 --> 00:11:59.500 that work? Well, the purpose is to take that 00:11:59.500 --> 00:12:01.659 fuzzy initial description, figure out the audience, 00:12:01.799 --> 00:12:04.559 the tech stack. Then the prompt asks for primary 00:12:04.559 --> 00:12:07.019 secondary features, detailed specs with constraints, 00:12:07.419 --> 00:12:09.419 and even suggests clarifying questions to ask 00:12:09.419 --> 00:12:12.029 the user. The example is a task management app 00:12:12.029 --> 00:12:15.490 for office remote workers. Node, React, SuperBase. 00:12:15.789 --> 00:12:19.190 Users want, create, track, complete tasks, get 00:12:19.190 --> 00:12:22.070 reminders. Pretty standard. The AI analysis breaks 00:12:22.070 --> 00:12:24.970 it down. Primary features, create, track, reminders, 00:12:25.389 --> 00:12:28.149 secondary, edit, delete, filter. Then the specs 00:12:28.149 --> 00:12:30.870 get detailed. Constraints like, store in SuperBase, 00:12:31.090 --> 00:12:34.299 1K tasks user limit. Load max 50 tasks at once. 00:12:34.320 --> 00:12:37.759 React UI. Use SendGrid 100 emails day limit. 00:12:37.899 --> 00:12:40.299 Wow, specific constraints. And crucially, it 00:12:40.299 --> 00:12:43.100 suggests questions. Needs user login. Which auth 00:12:43.100 --> 00:12:46.100 methods? Customizable reminder timing. Task edit 00:12:46.100 --> 00:12:48.440 history needed. Things you might forget to ask 00:12:48.440 --> 00:12:51.700 initially. That's fantastic. Turns vague into 00:12:51.700 --> 00:12:54.919 actionable specs. Saves huge analysis time, especially 00:12:54.919 --> 00:12:58.460 for apps on Versel. And those clarifying questions 00:12:58.460 --> 00:13:03.279 up front. Gold. Prevents rework later. Precisely. 00:13:03.500 --> 00:13:05.720 Get it right early. And that precision, does 00:13:05.720 --> 00:13:08.299 it extend to user documentation? Because docs 00:13:08.299 --> 00:13:10.000 often feel like the last thing anyone wants to 00:13:10.000 --> 00:13:12.419 do. Right. Often rushed or skipped entirely. 00:13:12.720 --> 00:13:15.440 Is AI the magic bullet for doc writing, making 00:13:15.440 --> 00:13:19.159 it less painful? Well, maybe not magic, but it 00:13:19.159 --> 00:13:21.039 definitely helps. The value of clear guides is 00:13:21.039 --> 00:13:23.220 huge. But yeah, it's time consuming. So what 00:13:23.220 --> 00:13:26.240 can prompts do? They can generate full user documentation. 00:13:26.299 --> 00:13:29.519 Yeah. Usage guides, FAQs, tips. The goal is just 00:13:29.519 --> 00:13:33.179 creating accessible docs. OK. the app name features 00:13:33.179 --> 00:13:35.740 audience. The prompt asks for guides for key 00:13:35.740 --> 00:13:37.759 features and FAQ with common questions, maybe 00:13:37.759 --> 00:13:39.919 a couple of tips. Example, a task app called 00:13:39.919 --> 00:13:42.399 TaskEasy. TaskEasy got it. It generates step 00:13:42.399 --> 00:13:45.120 -by -step guides, creating tasks, receiving reminders, 00:13:45.460 --> 00:13:47.419 and FAQ covering things like filtering completed 00:13:47.419 --> 00:13:50.019 tasks, tasks without due dates, troubleshooting 00:13:50.019 --> 00:13:53.340 emails, and tips like prioritize tasks, use filters 00:13:53.340 --> 00:13:55.500 effectively. That sounds really comprehensive, 00:13:55.820 --> 00:13:58.080 everything a new user needs. Pretty much. Get 00:13:58.080 --> 00:14:00.240 some started, answers common questions. So user 00:14:00.240 --> 00:14:03.179 -friendly docs, FAQs, tips enhance the experience, 00:14:03.700 --> 00:14:06.200 suits an app like TaskEasy on Vercel perfectly, 00:14:06.960 --> 00:14:10.240 frees up devs to build, not just explain, huge 00:14:10.240 --> 00:14:12.860 time saver. Definitely. Yeah. Now let's talk 00:14:12.860 --> 00:14:15.259 about something absolutely critical, security. 00:14:15.659 --> 00:14:18.399 Ah, yes. Can't forget security. No matter how 00:14:18.399 --> 00:14:21.200 cool your features are, if it's insecure, it's, 00:14:21.200 --> 00:14:24.519 well, useless or dangerous. True. So, props can 00:14:24.519 --> 00:14:27.399 help analyze security, too, and suggest fixes 00:14:27.399 --> 00:14:29.940 with code. Exactly. The source shows they can 00:14:29.940 --> 00:14:32.779 analyze your app, suggest enhancements, and provide 00:14:32.779 --> 00:14:34.559 the code to implement them. How does that work? 00:14:34.860 --> 00:14:37.019 The purpose is optimizing security. You give 00:14:37.019 --> 00:14:39.440 it app type, tech stack, any known concerns. 00:14:39.710 --> 00:14:42.409 It identifies vulnerabilities. Maybe three key 00:14:42.409 --> 00:14:45.409 ones suggest fixes with code or config, and explains 00:14:45.409 --> 00:14:48.730 why. OK, example. Optimizing a Node .js REST 00:14:48.730 --> 00:14:51.690 API for that task app on Vercel. Let's say it 00:14:51.690 --> 00:14:54.409 initially has no user auth or API protection. 00:14:54.669 --> 00:14:57.629 Big problem. Yeah, wide open. The analysis pinpoints. 00:14:57.789 --> 00:15:01.549 Lack of user auth. SQL injection risk. Missing 00:15:01.549 --> 00:15:04.649 HTTP security headers. Pretty standard vulnerabilities. 00:15:04.830 --> 00:15:09.519 And the fixes. Concrete code. For off .nojs middleware 00:15:09.519 --> 00:15:13.480 using JSON web token JWT to protect routes. For 00:15:13.480 --> 00:15:16.220 SQL injection, explain SuperPace's automatic 00:15:16.220 --> 00:15:18.320 parameterization, protect you there, good to 00:15:18.320 --> 00:15:20.940 know. That's handy. And for headers, using the 00:15:20.940 --> 00:15:23.059 helmet middleware and express, maybe with content 00:15:23.059 --> 00:15:26.320 security policy, to block XSS and other attacks. 00:15:26.539 --> 00:15:29.220 So it rapidly strengthens API security, gives 00:15:29.220 --> 00:15:32.000 you actual usable code, ideal for node apps on 00:15:32.000 --> 00:15:34.519 Vercel. Proactive defense, not waiting for a 00:15:34.519 --> 00:15:37.620 breach? Exactly. Much better approach. OK, nearly 00:15:37.620 --> 00:15:39.779 there. Last couple of points. Performance reports. 00:15:40.000 --> 00:15:41.940 Collecting and presenting that data can be a 00:15:41.940 --> 00:15:44.019 real chore. Yeah, pulling metrics from monitoring 00:15:44.019 --> 00:15:47.240 tools, formatting reports, it's often manual 00:15:47.240 --> 00:15:49.159 and tedious, like a scavenger hunt sometimes. 00:15:49.460 --> 00:15:51.639 So prompts simplify the scavenger hunt. That's 00:15:51.639 --> 00:15:53.720 the idea. They create the performance queries 00:15:53.720 --> 00:15:56.620 and the report templates. The purpose is generating 00:15:56.620 --> 00:16:00.259 a concise report. Give it app info type, monitoring 00:16:00.259 --> 00:16:02.740 tool, like Prometheus, metrics you care about. 00:16:02.830 --> 00:16:05.570 It suggests metrics, gives you the exact queries 00:16:05.570 --> 00:16:08.470 to get the data, and formats the template. Example. 00:16:08.590 --> 00:16:11.669 Node .js REST API using Prometheus. Tracking 00:16:11.669 --> 00:16:14.269 response time, error rate, throughput. Standard 00:16:14.269 --> 00:16:16.389 metrics. What about the queries? It provides 00:16:16.389 --> 00:16:19.909 the precise PromQL queries. For P95 response 00:16:19.909 --> 00:16:21.889 time, error rate percentage, request throughput 00:16:21.889 --> 00:16:24.629 per endpoint. No more guessing the syntax. Oh, 00:16:24.629 --> 00:16:26.990 that's huge. Getting PromQL right can be tricky. 00:16:27.169 --> 00:16:29.950 Tell me about it. Then it generates a clear markdown 00:16:29.950 --> 00:16:32.330 table template. Columns for endpoint, response 00:16:32.330 --> 00:16:34.350 time, error rate, throughput, maybe some example 00:16:34.350 --> 00:16:37.710 data. So, concise, readable reports, accurate 00:16:37.710 --> 00:16:40.549 Prometheus queries, ready to paste, helps you 00:16:40.549 --> 00:16:43.370 optimize, especially for apps on Vercel, actionable 00:16:43.370 --> 00:16:45.309 insights right there, less time measuring, more 00:16:45.309 --> 00:16:47.370 time improving. Exactly, focus on making things 00:16:47.370 --> 00:16:49.750 faster. Okay, last one, tying it all together. 00:16:49.809 --> 00:16:52.549 Okay. The software test plan, essential for meeting 00:16:52.549 --> 00:16:55.350 requirements, finding bugs early, but creating 00:16:55.350 --> 00:16:59.879 one, big task. Huge task. often feels bureaucratic, 00:17:00.100 --> 00:17:02.279 but is really important for quality. And prompts 00:17:02.279 --> 00:17:04.759 can generate these plans, too, including scenarios, 00:17:05.099 --> 00:17:08.000 scope, criteria. Yes. The purpose is streamlining 00:17:08.000 --> 00:17:11.119 your testing strategy. Describe the app, features, 00:17:11.480 --> 00:17:13.420 text stack. You define scope, what's in, what's 00:17:13.420 --> 00:17:15.920 out. Suggest test scenarios, including edge cases. 00:17:16.480 --> 00:17:18.519 And create a structured test plan table with 00:17:18.519 --> 00:17:21.319 success criteria. OK, like for our task, EasyRest 00:17:21.319 --> 00:17:24.930 API on Vercel. Right. Scope. Test create. edit, 00:17:24.950 --> 00:17:27.829 delete tasks, reminder notifications, test types, 00:17:28.329 --> 00:17:30.509 functional, integration, performance, security, 00:17:31.109 --> 00:17:33.549 exclusions, detailed UI testing, mobile testing, 00:17:33.829 --> 00:17:37.029 make sense, test scenarios, create tasks with 00:17:37.029 --> 00:17:40.150 valid inputs, edgecases .max .link, pass due 00:17:40.150 --> 00:17:42.869 date, test reminders, edgecases .no due date, 00:17:43.109 --> 00:17:45.630 near due time, test deleting tasks with permissions, 00:17:46.069 --> 00:17:48.529 edge cases, on -off user, nonexistent tasks. 00:17:48.569 --> 00:17:50.309 That was a lot of ground. And the table lists 00:17:50.309 --> 00:17:52.509 it all out clearly. Test ID features scenario 00:17:52.509 --> 00:17:54.970 type success criterion, like T1 create test, 00:17:55.250 --> 00:17:57.150 valid input. Functional tasks saved in SuperBase 00:17:57.150 --> 00:18:01.650 returns 201 status. Or T6 delete task. Another 00:18:01.650 --> 00:18:04.210 user's task security returns 401, unauthorized. 00:18:04.470 --> 00:18:07.069 That's a really clear, actionable test plan. 00:18:07.349 --> 00:18:10.509 Covers functional, security, integration. Perfect 00:18:10.509 --> 00:18:13.369 for apps on Vercell SuperBase. Helps catch bugs 00:18:13.369 --> 00:18:16.130 before they escape. Exactly. Builds confidence 00:18:16.130 --> 00:18:18.789 in your releases. Wow. OK, what an incredible 00:18:18.789 --> 00:18:22.170 deep dive that was. We've really seen how chat 00:18:22.170 --> 00:18:25.990 GPT can shift from just a coding helper to a, 00:18:25.990 --> 00:18:28.069 well, a genuine development partner. Yeah, it 00:18:28.069 --> 00:18:30.690 covers a lot. We hit so many areas, automating 00:18:30.690 --> 00:18:33.849 CICD, architecture analysis, performance tuning, 00:18:34.230 --> 00:18:37.269 generating tests, security hardening, documentation. 00:18:37.410 --> 00:18:39.930 And these prompts, they're not just theory. They 00:18:39.930 --> 00:18:42.950 offer practical, actionable solutions. Whether 00:18:42.950 --> 00:18:44.859 you're building on Drussel, using SuperBase, 00:18:45.119 --> 00:18:47.000 or just want to streamline your day -to -day. 00:18:47.180 --> 00:18:49.440 And that really leads to the key takeaway, I 00:18:49.440 --> 00:18:51.339 think. It raises an important question for everyone 00:18:51.339 --> 00:18:53.940 listening. What complex, time -consuming task 00:18:53.940 --> 00:18:56.180 in your development process could you transform 00:18:56.180 --> 00:18:58.539 next? Right. By applying these kinds of advanced 00:18:58.539 --> 00:19:00.779 AI prompting strategies, I really encourage you, 00:19:00.819 --> 00:19:02.980 grab one of these ideas, copy a prompt example, 00:19:03.380 --> 00:19:05.660 paste it into ChatGPT, tweak it for your needs, 00:19:05.759 --> 00:19:08.160 and just see what happens. Experience that transformation 00:19:08.160 --> 00:19:11.150 yourself. Absolutely. That's all for this deep 00:19:11.150 --> 00:19:13.769 dive. Go experiment, keep learning, and see how 00:19:13.769 --> 00:19:15.309 AI can boost your workflow.