The senior engineer's guide to AI coding: Context loading, custom hooks, and automation

There are people out there definitely like me that really want to know the advanced techniques that can leverage the most powerful parts of these AI powered coding tools. Where do you want us to get started that you think many people don't think about in terms of how they can use these tools? >> Context and diagrams is a great place to start. They're definitely the best way to get AI to do what you want. So, they have what are called mermaid diagrams. This is a way of visualizing database operations and it's a way of essentially compressing your application down into very small lines of text that show how your application works. Now for a human to read this, this is a big challenge. But an AI can consume this easily. I could even just say, "Please explain the authentication flow." And because it already has it in the context, it's not going to have to do a bunch of file reads and codebase exploration to figure this out. It's going to come up with results much quicker. >> If I gave you infinite junior to mid-career talent who is always available, who would do the work you would do if you had unlimited amount of time and no meetings? What would you do when a ticket came in? Like what would you do? Welcome back to How I AI. I'm Claire Vio, product leader and AI obsessive here on a mission to help you build better with these new tools. Today we have John Linquist at egghead.io who is a super user of AI powered engineering tools like cursor and claude code. Now, I love all you nontechnical folks out there, but this is an episode for the senior software engineers who really want to understand how they can use the power features of some of these AI engineering tools to really both optimize the quality of code that they're generating, but also become more efficient as they use their IDE, terminal, and AI assistance to write, check, and deploy code. This is a great episode for any of our advanced users out there. VPs of engineering, CTO, pay attention. Send this to your staff, engineers. Let's get to it. This episode is brought to you by work OS. AI has already changed how we work. Tools are helping teams write better code, analyze customer data, and even handle support tickets automatically. But there's a catch. These tools only work well when they have deep access to company systems. Your co-pilot needs to see your entire codebase. Your chatbot needs to search across internal docs. And for enterprise buyers, that raises serious security concerns. That's why these apps face intense IT scrutiny from day one. To pass, they need secure authentication, access controls, audit logs, the whole suite of enterprise features. Building all that from scratch, it's a massive lift. That's where Work OS comes in. Work OS gives you drop-in APIs for enterprise features so your app can become enterprise ready and scale up market faster. Think of it like Stripe for enterprise features. OpenAI, Perplexity, and Cursor are already using work OS to move faster and meet enterprise demands. Join them and hundreds of other industry leaders at works.com. Start building today. John, welcome to How I AI. I have to put some context here which is we have done quite a bit of coding with cursor vibe coding episodes but a lot of what our audience has asked for is early maturity less technical introductions to these tools. But there are people out there definitely like me um and definitely like folks that follow you that really do know how to write great software and want to you know as people say of course I'm a 9x engineer but how do I become a 10x engineer with some of these tools want to know really the advanced techniques that can leverage the most powerful parts of these AI powered coding tools and get you really high quality software. So I'm really excited about what you're going to show us today. And so where do you want us to get started that you think many people don't think about in terms of how they can use these tools? >> Yeah, I think uh context and diagrams is a great place to start for us. Um they're definitely the best way to get AI to do what you want. So um and we'll be using cloud code throughout. >> Oh, great. Okay. And so yeah, we've we've gotten a lot of kind of markdown files in How AI, but not a lot of diagrams. So why don't you walk us through >> how you use those those assets to help you code better. >> Yeah. So these diagrams are all generated from I can share a prompt with however you want to share with the audience um that can walk through your codebase and generate diagrams based on uh user actions or user interactions the events the channels whatever happens in your code to help the AI understand the flow and how the pieces are connected. Um I think Windinsurf recently came out with something called code maps, a similar concept. Um essentially preloading valuable context so that you have to remember that every time an AI starts it has no memory, no idea of what's going on in your application and people try and set up lots of rules and all the stuff around it. Um, but they usually don't include a lot of how does my application work and how do the pieces fit and so you get a lot of really bad edits because it doesn't understand if it if it modifies A, how does that impact B? Um, so we want to preload a lot of that. We can do that using diagrams. Uh, so for example, one of these diagrams um will have I I call they're markdown files with diagrams in them. So they have what are called mermaid diagrams and mermaid is a standard format for rendering diagrams inside of markdown. So this is a a way of visualizing uh database operations. And if you to zoom zoom in and look at uh how if a record exists then do this and that. Yes. No. And it's a a way of essentially compressing your application down into very small lines of text that show how your application works. Now for a human to read this, this is a big challenge. Uh we need to open up this big visual and it turns into like looks like an image. But an AI can consume this easily and it's like a very compressed very um robust way of explaining application. So we can feed these into our application at at the startup time. Um, and for the more advanced pro or the larger projects you get on, the more diagrams you'll have, and you can kind of pick and choose which ones to load. Um, I'm going to load them all in. And I'm just going to open um terminal up the editor area. So, the way I'm going to do this, if we look at Claude and we look at look at its options, um, you'll see a bunch of options. The one we're going to focus on is called append system prompt. So in there before we load in uh any sort of user prompt or anything we're actually going to say claude append system prompt system prompt and then you can drop in some text and we're going to drop in a command and this command can read in from our memory from AI/diagrams and then this is going to read through this is a called a glob pattern read through all of the markdown files essentially force them into claude once I do this. So this is reading all the files all the markdown files and this is cat will kind of concatenate them all together into a single uh text read. >> Yeah. One thing I want to call out for folks that are watching this that or or are listening and maybe not watching is two things. It seems like, you know, in your in your standard repos, you're creating a a memory um directory where you're going to structure some of the context and files you might want any of these AI tools to use. And I think everybody's like, "Oh yeah, I've created my agents markdown file or my clawed one." And I think you can actually structure your um context for these tools a lot more purposefully. And so I think this is a really good example of this. The other thing that I I think a lot of people are quite lazy about is they haven't explored the surface area of all the system commands available in cloud code. And so by using that help command, you can actually see things that not just chatting with clot code you can do, but you can actually inject into how claude operates. And appending system prompt is one of those ones that I think people probably underuse. >> Yeah, absolutely. Um, it's one I use constantly. Um, great points there. Um, so when when I let this run, you'll notice that there's um it's now prompting the user to do something. And we don't have to try and reference all of the files, which you normally do with AT. We don't have to try and tell it, you know, what we're going to work on. I could even just say, like, I use dictation all the time. Uh, please explain the authentication flow. And because it already has it in the context, it's not going to have to do a bunch of file reads and codebase exploration to figure this out. It's going to come up with results much quicker. This this does come at the cost of a lot more context, a lot more um tokens being used up front, but the work that you do, the time that you spend on these tasks is more valuable than that to me. So, you'll notice that there were no file reads in this. There were no um it did not search the codebase. It didn't do any of that stuff. It just simply had all that in context. And now I could take this and look through it, start creating plans, swap over to plan mode to how we want to uh update and um change authentication. So this saves again the the the trade-off here is the cost of many tokens up front but the value is you get a lot faster and a lot more valuable output as the tasks complete much faster the tasks are much more reliable because it understands what's going on in the codebase. >> Two things I think people should think about with this flow. one is I've said this in a couple episodes and and we'll call it out again in yours is I think that with LLM starting to become more of a part of how we do work and feed context and understand things like documentation or business context. This is the era of the the file type and I think so many people think about markdown and JSON files as effective ways to inject context into LLMs. I see a lot of course markdown files. I think more people now write markdown than they h than they have in many many years. And then a lot of we've had some episodes on using JSON for example to put realistic or semi-realistic data into prototypes. But we are having more and more episodes where people are discovering specific file types that have a specific context structure that are really useful for a use case. In this one, you have mermaid diagrams, which again are hard to parse as a human. And even if they turn into graphics, are still hard to parse as a human. Like I looked at that big diagram of my eyes crossed and I said, I don't I don't want to read this. But to a machine, it's very effective. We've also in some episodes talked about um image and multimedia file formats that not only contain image data, but contain metadata that you can use. And so I think this is an interesting moment where we can all use different file types in a more extensive way than our kind of human brains could because the machines are so good at using the different component structures or syntax of of those files. So I think that's pretty interesting and I think mermaid diagrams are one of those examples um of something that can be used really well. >> Yeah, absolutely. There's a lot of research being done into how they can compress all of this information down into like a single image. So, if I could take all of the diagram files and somehow come up with an image format that would store everything in there, could would the trade-off on tokens be there and would the trade-off on understanding be there as well? Um it's uh we we'll see if there's more file types that emerge and I'm huge um on video and using videos uh Gemini being the best model for uploading video and understanding um and recently built a tool that can take one of my six-hour workshops and uh process the entire thing and take out notes and examples and thoughts and frequently asked questions. And so each time I teach a workshop, I can iterate on it and um I don't have to go like search through the video some other way. It's >> you and I will have to trade notes because I did a very similar thing with our episodes which is it takes a video of our episode. It pulls out all the learnings, all the code snippets, screenshots where the guest and I look cute and put it into into a blog post. So So I agree on that. You know, the second question I had for you though is going back to these diagram files in this memory directory. Where in your development process do you find that you generate those files? So for me, I actually have a GitHub action that generates files almost exactly like you have with documentation and diagrams for new features um of a of a specific scope. And so I do it when a pull request is closed and then I go back and um update update our diagrams. I'm I'm curious where this falls in your where documentation like this falls into your workflow. >> Yeah, usually I think pull request is a a good paradigm there. Uh as soon as you have something working where you want it to be working and then you can say okay now this is working as expected. Please diagram it. I think for a lot of the projects, we already have pre-existing um code bases that don't have diagrams. And so that's that's been the major use case is taking existing stuff and um diagramming all of that so that our AI development is accelerated, I guess, is the buzzword. Um but yeah, if you're starting from scratch, you definitely just want to spike spike things out, get it working. Um don't worry about diagrams up front. um just use a plan mode, build something and once it's working, then diagram it out. And then even with the diagrams, um they're great to help walk you through like what did I just build? Like I didn't look any of this code. Uh show me diagrams of what the code is doing. And then if the diagrams look kind of wonky, you can just say there there's there's tools in there that people are working on where you can like drag around pieces of the diagram to say, well, I don't want this to navigate there. I don't want this user do that. We could I don't there's going to be so many tools in the next few years that emerge from all this. >> Yeah. And then I will give folks just a couple other use cases of generating mermaid diagrams from code that are not just about improving the efficiency of using something like cloud code. Um I use a lot of diagram generating out of our repo to answer very complex security and data flow requirements from our customers. This is a it's a workflow that is actually like pretty expensive if you ask an engineer to do it which is I have specific customer A they need a very specific data flow diagram of this part of our application so they can understand the third party parts of it again also if you're going through sock 2 compliance or any compliance like these are these are assets that historically have just been so tedious to create efficiently and effectively and now you can kind of generate them on demand. My last question for you on this diagram flow is do you find that you have the AI write or you would write documentation any differently than you would for a human audience or do you feel like there's enough overlap that the content format etc can be pretty consistent between the two? >> I would say could be pretty consistent. I I think they serve as a nice bridge between kind of human and AI. Um definitely think I I know people generate documents like you'll write code and then generate documentation around it using AI for both steps which is just wild but um yeah I think the markdown is kind of the language of the future for a lot of this um text and then there you can do images and everything inside of markdown files as well. So they can kind of and the front matter metadata. Um you'll you see claude using that extensively for their skills and commands. >> Yep. >> And everything. So um and anthropic is pretty good at pioneering all this stuff. So >> if they're using markdown then >> everybody else can. >> Yeah. >> Yeah. Uh again for people who want to like pull the thread a little further uh what what I do is yeah we generate a lot of AI code then on poll request we generate AI documentation internally for engineers and for AI obviously to use this context and then we take that code and we generate markdown customerf facing support documents again that really benefit from these workflows because then you say click button A move to section B save this and so you can really pull the thread on docu documentation from one asset and I think you're showing a place where it's really useful from the engineering perspective but it can start to become customerf facing and all sorts of interesting things. >> Yeah. And you could summarize the documents for customers. Um you could have it build little interactive demos. I mean there's the sky's is the limit. Like how however much you want to support customers there is if this is enough then then great. If it's not then it's an AI prompt away from >> something pretty. I guess >> this episode is brought to you by Times, the intelligent workflow platform powering the world's most important work. Business moves faster than the systems meant to support it. Teams are stuck with repetitive tasks, scattered tools, and hard to reach data. AI has huge promise, but struggles when everything underneath is fragmented. Times fixes that. It unifies your tools, data, and processes in one secure, flexible platform. Blending Agette AI, automation, and human-led intervention. Teams get their time back, workflows run smarter, and AI actually delivers real value. Customers now automate over 1.5 billion actions every week. Times is trusted by companies like Canva, Coinbase, Datab Bricks, GitLab, Mars, and Reddit. Try Time Tines at times.com/h how I AI. Great. So, you showed us how to just pull all of these documents into a system prompt. You get much more um performant use of something like Claude Code. And this seems like a command that you're using over and over again. And that's something you and I talked about before we started recording, which is how to alias and make more efficient your use of of different commands. So, should we should we pop over to that or anything else you want to show on diagrams? >> That's that's great. Let's do that. Um, so there are a lot of uh with with on Mac it's DSH is the default shell. Um, on Windows I do PowerShell. So, this look very different. Um, but depending on what tools you use the most, you can easily set up aliases for things like setting the default model for for claude or setting like if you want to do something completely dangerously so that once you open a new terminal, if you just type X now, anything I type has bypass permissions enabled. Or if I type H, this will be Haiku. It'll be much faster, but not quite as smart. Um or if I type in the scenario CDI um this will do that diagram loading um where once you have these systems in place these commands in place then you can just uh kind of capture them in the smallest like because I only because I use these a lot I I I keep them in very short shortcuts. Yeah, and I can imagine you could you could do something like this for project specific context to so you could do like CC dash whatever project you're working on. You could pull in the diagrams for just that initiative. So if you're going back over and over again into specific things that need specific context, this would be just a cheap shortcut to to get you into the mode of for example cloud code that you want. >> Yeah, absolutely. >> And you showed a lot of cloud examples here. Are there any other ones that you think are really really useful for folks or creative uses of this you think we should think about? >> So I tend to build any idea I come up with. Um so for example this is one I'm working on called sketch and this feeds into the Gemini uh Gemini CLI. So like what type of website do want to do I want to build? Let's do a store for selling uh Christmas decorations. And then let's make the homepage of that. Let's make it creative and artistic for a desktop website. We'll do the GitHub light theme for it. No reference image. Let's do five images and go ahead and generate it. And this is the sort of thing where um kind of beyond beyond the simple alias if you uh if you've never dived into creating what's called a CLI you can tell an AI like listen I want to use like this is a wrapper around um Gemini where it will execute Gemini with specific prompts. So you have to remember that you have these tools on your desktop which can do incredible things but you can also script them and this is a scripted way of generated generating images based on all of these um all these topics with or these concepts with pre-loaded prompts and I can say if I want to add another feature like you can just go in there and say please tweak the prompts or please add this feature please do this and then instead of um constantly thinking of oh what was that prompt again or was that idea I had. You can have these little CLIs and these little projects that are be just for you. Um because you just like build the tools that you need now. And um this is just spitting out these um my my mom lives with me and she's setting up Christmas decorations upstairs. This is why I'm thinking about this. >> So this >> Yeah, this is Gemini generating based on the prompt we fed in based on the color scheme. This is GitHub light Christmas store color theme. Um, and I told it to generate five variations of it. And then we could take one of these images and drop it into one of the um, drop it into one of the AIS and say, "Let's start building out this website. Let's break this into sections and go from there." And this is kind of like my uh, ideation inspiration sort of thing that that I use. One reason I want to make sure people are paying attention to this use case which is essentially you've exposed a command line interface to do a couple you know script a couple workflows around calling um nanobanana and some of the Gemini models to um >> to to do some things and there are two benefits I think to this that are really important. One is building command line tools has been so opaque and just kind of not fun for so many people for so long. Um I've built lots of them and how easy it is to build a really nice command line tool is such a treat for anybody who's ever had to build them and make them look good. Everybody has these cool ASKY only logos if in their in their command line tools which have been very tedious to make before. So I think one thing is these tools are just a lot easier to build. Two, from a product builder perspective, the reason why I like this move to these command line tools is the constrained UI space of the terminal actually make sure you don't get distracted in building UI around something as simple as this. Right? You just had like five questions you had to answer, a couple multi select. You could tab through those with your keyboard. If you were creating like a little wizzywig walkth through web editor thing here, I mean, one, I would have gotten really distracted about how it looks. Yeah. >> Two, you'd have to type into, you know, you'd have to run localhost and type into um your your your web browser. And so, I actually like the constrained UI space for speed of of prototyping on some of these ideas because you just don't get distracted by anything but the essential kind of toolkit. Um, and then you can get a really cool thing out the other end. >> My only problem is I've built more tools than I can remember and sometimes >> after like where was that thing? Um, >> yeah. I uh I also like what you how you started this this little segment which is you said you just build every idea you have. I think that is totally the move. While you have an idea, kick off something, get it built, build yourself a little throwaway repo. Um, you know, eventually the AI can crawl it and remind you everything that you built before, but this is pretty cool. >> And that's that's why I love dictation because all you have to do is start up a new terminal in a new folder and just kind of brain dump in there and then it'll try something and once you have something even if it's wrong, you can iterate on it. Yeah. >> If you have nothing, you can't iterate on nothing. And I think that's the magic of uh even for people who who hate AI tools. Like a sheet of paper full of things that are wrong is much better than a blank than than nothing because even if it's wrong, you you recognize it's wrong and it helps you think of what's right and what you want to build. >> Yeah, I say this a lot. It's easier to edit than author. So, let's get the authoring out of the way and then even if you completely revise the whole thing, it's a much easier starting sprouting point to work with something. >> Y >> Okay. So, I think we're going to close out and spend uh a little bit of time on your workflow for when you're doing more complex coding projects or features, how you keep those really high quality using some advanced techniques in um I think in cloud code and cursor. So when working on any excuse me when working on any project um often when the AI is generating code it'll often build out mistakes and so even it will say it's done you're like wait a second there were a ton of mistakes there why did you stop just fix it until the mistakes are done so for example um let's say it wrote out this code and there was this error in here and this error is something you'd usually catch with tools such as TypeScript uh or maybe it's formatting or linting or any sort of complexity tools um that they're code quality tools that you run before before you think the work is done. So you would run something like bun type check and you would see that it has this error but your uh claude code and the other agents don't know that this error exists. What Claude has and what cursor cursor and a few others have is the concept of hooks. And what this can do is so inside of claw, let's go here. You can set up what are called hooks. And um I'm going to set what's called a stop hook and hit add new hook. And just it shows you a bunch of examples. I'm accepting responsibility for all this. Bunch of warnings because it can run scripts that aren't checked by the AI. And I'm going to say the command for now is just be echo, which does nothing. And I'm going to add it to my project local settings. And now we have this echo hook. And this is defined in this settings local uh.json file. And this is for uh this is a local file for me. If you want it to be with your team, it' be settings.json settings.lojson is distribute. What we're going to do is instead of running this command, we're going to run a custom uh claw claude hook which I've defined inside of claude hooks. Uh and I called it index index.ts. You could call it stop or whatever. So from this script which is in this directory um I need to run this uh install for this package because I don't have it installed right now. So I'm going to bun install and propic and this is their um their clawed agent SDK. Now in the SDK they have um what are called hook inputs and other types you can use so that when you're dealing with hooks you have a lot more information. So like on this input you have all of this information around what the input name is and then what the session ID is and the current working directory permission mode and all that and you can use that to customize your hook. But we're gonna but what we are going to focus on is we're going to see step one were their files changed uh when we stopped. And a stop is once uh Claude has kind of finished its conversation and it's now waiting for you to do something. So we're going to check are there files changed? And we're going to if there's files changed we're going to say okay then let's go ahead and run that bun type check. And if there is a type check then we can say back to claude we can say hey there were typescript errors this is the report and then send them back the output that we showed in the terminal before and it'll continue. Otherwise, if there were files changed, then we can tell Claude to please, there's a prompt way down here. It says, "Please commit essentially. Uh, get the files, don't commit anything, anything sensitive, and go ahead and commit it." So, we set up this workflow of once a conversation is finished, check to see if any files have changed. If they have, you check to see if there's any TypeScript errors, which could be a type check or build errors or any sort of other um code quality uh guards you have in place. And if there are none, then go ahead and commit. And this saves you a lot of the overhead in your mind of uh here's all this extra stuff I have to do once something's done. >> Yeah. And what I want to call out for folks that are maybe listening and not seeing this code here is it's really what's nice about this is it's a combination of commands that you would run in the terminal to to just generate errors and see them yourselves, but then you can feed those back into clawed code in a more natural language way and give natural language instructions on what to fix or again default to some command um that's different which is this GitHub commit command. And so I like this combination of kind of like structured commands in in the terminal combined with natural language calls back into CL claude to then kind of put the bow on the end of any work that this AI system does. Is that kind of how you think about it? >> Yeah, exactly. um that the gotchas you have to think about here are when you're uh when you're communicating from a hook back to Claude, you're essentially using console log, which is one of the first things any JavaScript developer learns and you're sending back a JSON object. So, it's going to find that first console log and whatever gets back, uh that's what it's going to see as its uh as its input, its standard input. So you have to be careful if you're running commands like this. You you tell this one, please be quiet because if it's not quiet, then it would log back to the console and maybe interfere with something. Or if you want other logs or you're debugging the script, just use console error or any other way of showing logs. Um otherwise, console log turn it turns into this feeding instructions back to the agent. So, it's one of those gotchas that everyone falls into when when building this out. Uh, and just to just to demo it real quick, um, I'll just turn on Claude and I'll say um well, actually for this to work correctly, let's make sure we have everything staged and set up so that when it does the get check, um, let's just generate a message. So yeah, let's uh please create a fu.ts file on the root of the project. And we'll go ahead and accept this. And you'll see that it says stop hook returned a blocking error. And that error returns, please fix the TypeScript errors. And here's our prompt right here with this block. And it says I I'll fix a TypeScript error. So this is when it would have stopped. It would have stopped right here. But we hit the stop hook. Now it sees these errors. So it's going to go ahead and read that and says, "Oh, I found the mismatch quote. I fixed it." And now behind the scenes there's a cloud running which should it commit that fix. You make this a bit smaller. Show our graph here. And you'll see um this is the fix that it made was correct the quote syntax. This is what the little ha coup did in the background. So the stop hook ran twice. It ran once where it found the error and had files changed. And then the second time there were no more errors and so it ran the commit. And so that saved us all of that work of both passes. And now we have a completed task that has been error checked, fixed, and then commit um and conditionally enscripted in a way where this will be different for every single project based on your requirements, based on your codebase. Um, so this is definitely something that you have to like think through and set up yourself. It definitely saves so much time where you don't have to go back in and say, "Well, please fix this or please run this command or please do this." When you know part of your workflow is always the like if these things should always run, you might as well run them automatically. >> And something I have to say is I get so much push back from software engineers saying these tools don't really make me faster. The quality isn't as good. And I think if you make the investment as you've shown us in, okay, well, what things would it do to make the quality better or what things would it do that you can automate that would make you a little bit faster? And you put that effort in to understanding all the things that these um tools can do for you either programmatically or through prompting. I think you can actually see a lot of those efficiencies. And then I want to call out something that that you said which is you have this local settings but you can create settings that are shared across your team for anybody that's working in the repo and that's for our engineering leaders out there or larger engineering teams to really think about if you haven't created these hooks for key repos or key projects where everybody is benefiting from this when they're using something like clawed code then you're missing out on some of the scaled leverage I think of of these tools. And so I'd love to put somebody in charge in an engineering organization of figuring how stuff like this can work inside your codebase and then scaling it out either through training or through configuration into all the other engineers so that everybody's getting this baseline quality and this baseline efficiency. >> Yeah. >> Amazing. Well, okay. Other than you know type T type script errors, just pratt off a couple other use cases. You deleted a bunch of stuff from this hook. So, what are the things you think that people should bake into a stop hook like this for cloud code? >> Uh, definitely formatting. Um, I there's there's kind of the the mindset we've always had before of like pre-commit hooks or pre- push hooks, things that operate on the CI and these are a lot of things that can be um fixed before those are even run. So whether it's there's a lot of tools around um with linting it it could constrain the length of files um there's things like uh circular dependencies where I could check the imports to make sure that files don't reference each other um there's code complexity there's tools that say does this code look like any other code in the codebase where um this could be extracted into a function or something because there's like duplicate code throughout the codebase There's all sorts of analytics and tools you could run. Um some of them probably not as often as others because it's more expensive and you just have to make those um decisions based on you know the size of your team, the size of your application. But there's just just put into an AI prompt of chat GBT or any of them to say what are all make a long list of uh developer tools people run on pre- push or uh on pre-commit and you'll see the a huge list of them that you could uh pick and choose from. Well, and I'm going to take a tiny detour for um our very patient non-technical audience members that have maybe listened to this, which is these um posttool call hooks or post stop hooks in Claude can also be used when you're working on non-code. So, we have so many people using claude code to write documents to do all sorts of things. And so you could just think about what do I want automated after this tool is called or what do I want automated after Claude finishes writing my my document. And you could think about ways to use something like this not even for code quality review just for a post kind of task completion check. So I think just the general framework's really useful. It's obviously highly applicable to software development but I think people can think of other creative use cases for this as well. Yeah, absolutely. The the diagramming stuff, create an image of what we just did and send it to my mom to show her I'm working hard. Like anything you want, right? It's it's the sky's is the limit. So, >> okay. So, just to wrap up, these have been super useful use cases. I want to call them out. One is using um documentation and diagramming, specifically mermaid diagrams to preload as a system prompt in your claude code instance so that you don't have to waste the time of doing context discovery and you can really make sure that that context is preloaded. It's a little more expensive on the token side but a lot faster and these diagrams are much more um easily read by machines than by humans. So, it's a good format to get things in. We looked at aliasing some of your favorite Claude code instances and settings so that you can pop into your live dangerously mode. You can pop into your you have all my diagrams mode. Um, you can just pop into those with one, you know, one one or two letters, which I like. Uh, we got a little side preview that we didn't call out, but just how casually you use voice and transcription to enter in and out of these tools. What I like about the way you use AI is you were just like highly efficient. You're like, the minimum number of things I can type the better and you're pretty fluent in switching between voice and typing. So, we saw we saw a little of that. uh you encouraged us to create in particular little command line tools to build one-off ideas or tools. Yours was a website design generator using Nano Banana. And then you showed us how to use um claude hooks and in particular a stop hook to do some quality and other checks on code written by these AI tools and automate some of the processes um that you might do as a software engineer that you want our little AI software engineers to do instead. >> Just that in I'm looking 40 minutes. We did it pretty fast. >> Nice. >> This is great. Okay. Well, I'm going to ask you a couple lightning round questions and then we will get you back to your very efficient AI coding. My first question again, you're like me. We love cursor, we love Claude, we love VS Code. We have all of them open. You know, I think everybody's I think there's interface wars happening right now. Are are people going to love these terminal UIs and command line tools like Claude Code? Do people want the the IDE? I I noticed that you're on cursor 20, so you have the agents view, which is very simple and abstracts away some of the code, and you're in the editor view. I'm going to give you two two wars. I wanted your quick opinion right now. We won't hold you to it, of what you think wins for, I would say real software engineers, you know, writing real code out there. um the the friends that I talk to, you know, terminal UI, IDE or both. And then do you do do you have any hypothesis on I think particular in the the VS fork world, VS Code fork world, are there any modes or you know what do you think how do you think people can compete in the IDE world? >> Yeah, so I think you need both. I think you need an IDE and there are so many use cases for the CLIs. Uh the reason being that the CLIs have a lot of configuration and a lot of settings where um as you saw with the aliases, I could launch a version of cloud that loaded up a specific set of MCPS or a specific set of prompts and preload a bunch of things and do that in a single terminal command and be very um quick and fast with that and then set it off in the background and just have it running. Um, currently inside of uh inside of a cursor or inside of any of these um idees, there's usually a lot of okay, open the UI, navigate to this, and then navigate that, then switch over to this, then switch over to that. Um, and they try and streamline as much as possible with slash commands and whatnot. Um, but it's just not quite the same. But if you have an IDE and you're reading through the files and you're selecting lines and you want to modify certain bits like focused work, um there's so many use cases for IDE where um there there's a recent cloud tool where it has a IDE integration where it can check the diagnostics from the IDE and you'll see that with VS Code as well like the extensions you put into an IDE can be fed back into the agent. So there's a whole robust extensions ecosystem from idees because people build on top of these things their own workflows. And I don't think we've quite reached like we build our own CLIs from AI. I don't see a lot of people building their own cursor extensions or VS Code extensions which are very possible and you could feed those errors and warnings and company rules and everything um in very complex ways back into the agents. Um so that that will happen as well. And I think for one IDE to stand out above the other they have to separate themselves like cursor is doing with their agent mode. Um they have to make something unique and user friendly that once like people are not going to give you a bunch of time to convince them. uh you're going to have to open the agent and you're going to have to like see that click on browser mode and it's going to have to launch your dev server and you're going to have to click on the element and say I want this to look uh uh with more pink or purple or whatever and then um and then they want that to just work. um you'll see any sort of friction or frustration from any AI tool anybody puts out there um is is just instant uh dismissal from so many people like there's just the bar for quality is so high in the AI landscape because everyone can build anything that you have to focus on the UX you have to make that experience better than everyone else and that's where you you can see the cursor making the bold moves of like, okay, let's go full on agents. Like, you have to make those leaps. >> Yeah, I I agree. And, you know, just talking about this skepticism and high bar, what I love about this episode that we recorded today is it's really most relevant for software engineers with more experience, who are shipping highquality code, and who want to write production level code more efficiently using some of these tools. It's this is not, you know, I hope you all hung out and listened to it, but it's not for our vibe coders and our non-technical folks. Um, and so what would you tell kind of senior principal software engineers, engineering leaders? I get asked this a lot about how do I sell the value proposition of these tools into very skeptical organizations and what are as a more advanced software engineer the things that have just changed your life in the last year say you should never go back to doing it this way kind of how do you how do you make that pitch that >> the the first thing that jumps to mind is anytime an issue is opened like you can set up streamlined workflows that someone opens an issue and you can have claude automatically tackle it. You can set up triggers for linear, GitHub, whatever that once something happens, you can get that first pass to see, okay, can we at least find this without doing any work? Can we at least get that initial uh review in there of what's going on so that once we jump into the task I mean for my entire career someone throws an issue at you spend the first you know probably day or two orienting yourself to like okay I didn't write this code this is legacy from let's you get blame let's do all this stuff like all of that busy drudgery that you're going through to even get started on the issue. Um, it can wipe out so much of that. It can find who touched the files, who did this, like if if you have the diagram set up, what are the risks, the impacts, are there potential security things? Are there like it it's so great at surfacing um the you don't know what you don't know sort of scenarios where you hire so many contractors, you hire so many people who uh are new to these things and then you throw them into these tasks and they just don't know like they haven't spent time with the codebase and then um you ask them to fix these things they just have zero idea what sort of impact their changes going to have. The AIS can surface a lot of that and they can just be like, "Okay, we need to be super careful. This is, you know, in production and um this is cost going to cost us money if this goes wrong. Just tell me everything I need to look at." Like find every single debug path. Find every single um uh every why has this file changed over the course of history. Like write a summary of everybody who's touched this file so I can know why this function is the way it is. like there's just so much work that is just not writing code. Um, and all the exploration work is just so much easier to just say like everything I just said over the past, you know, 30 seconds is a prompt, which I could have just dictated, right? Um, and you just have to walk up to your computer and say, "I have this issue. Like, guide me through all this stuff." And um it's just it blows my mind that people be hesitant for those sorts of tools. I I understand if they're like, "Okay, maybe some of the code isn't perfect. We still have to do code reviews. We still have to like check for quality. We still have to run our tools to validate things." But if you're not using it to do to like inspect and investigate and write orientation and all that stuff, then like you're really missing out. like in in the enterprise space. >> Yeah. And on the other end, if you're not using it to document, so the next time somebody has to do that investigation, you have a little bit of an easier time, um you're al also missing out. So I do think on that that front and the back end. And what I often tell people is a good way to think about how to design your AI workflows is do not think in a task level orientation like I'm going to write code. I say, think about if I gave you infinite junior to mid-career talent who is always available, who would do the work you would do if you had unlimited amount of time and no meetings. What would you do when a ticket came in? Like, what would you do? And you'd say, well, I'd go trace who wrote the code. I would go figure out the history. I would make myself a really good tech spec. I would call out the risks. I would publish this in a way that my team could review it. I would have a senior engineer look at it and give me some really hard feedback. All of that could just become a prompt and then you know but so many people are just constrained by their time and and cognitive capacity and so they just go well I'm going to read the issue and I bounce around in the code a little bit and I guess I'm going to start coding. And so, um, you can kind of get to this model of optimal, not perfect, but like optimal workflow and then figure out how you can prompt or build workflows or hooks that would replicate that at least in an 80% way. Um, which is a lot better than not doing it. >> And something as simple as the commit messages are so much better than they used to be because developers didn't have to write them. I >> so much better >> for for people who are new to programming. Um, commit messages used to be like second attempt or like please work swear words like >> my my favorite one is just like 17 FS like or like trying this, trying that, trying this other thing. >> Yeah. Not these work plz. >> Yes. Yeah. You know, if anybody wants to vibe code a product, I always thought that startups would want a printed book of all their first years commit messages >> with like calling out the really funny ones. Oh, if somebody wants to vibe code a little uh GitHub API powered print uh business, I'm sure you could get a couple startups to print those out. Okay, last question. Yeah, >> this is probably challenging for you because you do a lot of dictation. So, you're probably actually pretty polite to AI given you would have to say frustrating things to it if you wanted to be mean. But when our our little friend Claude is going off the rails or you're really not getting what you want, what is your prompting reset start over technique? Have you found any any tricks that work particularly well? Yeah, it's it's really the um take the conversation, export it. A lot of them have the export commands. um drop the conversation with some of the code files into the um into chat GPT pro 5 or whatever it's called or Gemini uh deep think I believe is the and have it have them do a second set of eyes on it and then kind of start over rather than like if if things go off the rails and you can't fix it in about maybe one prompt of like where you see what's going wrong and just revert to the previous commit and kind of start over because there there there's always this underlying the AI is trying to go somewhere and you want it to go over here and you keep on telling it to to join on your path but it still wants to like get somewhere else that you don't quite understand. And so starting over from uh ground zero and like revising your original prompt is better than like trying to steer it to where you are when you've like drifted so far away. Um and that has to do it's so different with every model. It's so different with every prompt and all the context and project that it's like it can't give you like the here's instructions that work every time. But like starting over works every time. tossing a second set of eyes on the entire conversation where that AI isn't uh isn't invested in that conversation. It's instead critiquing the conversation. Um th those are my my two >> I think that second um that second workflow is so funny because I I think as somebody who's been a manager and a leader so many times sometimes I feel like I'm the reasoning model being brought in to mediate the the misunderstanding between two smart but misalign misaligned resources and so it's really funny to hear the idea okay like I am having a debate with my AI let's bring in like the third party. Let's mediate this conversation, have an objective set of eyes to see where we maybe are misunderstanding each other or going wrong and then reset and start start over. So again, I think you know this is the moment for folks with a lot of organizational and social skill thinking um to apply this to how you might design some of these flows um for for AI even though there are um beep boop machines that we're really using. >> Yeah. And and I would say kind of last thought on that is the recent planning modes that have been released with cloud code and cursor and all of them have eliminated a vast majority of that of that drift. >> Um so they've been fantastic releases which I strongly recommend for anything >> beyond like a small file change. Planning is awesome. >> Yeah, I love I love those features too. Okay, well John, this has been great. Where can we find you and how can we be helpful? >> Yeah, I'm on eggghhead.io. um that is I have tons of courses on AI tooling. I teach workshops through egghead.io. I send a newsletter out every week called AI dev essentials. Um you can find me on X and other platforms as well under my name. And that's it. I love to talk with anyone about all this stuff. Um my workshops are fun and we talk go way deeper into this super advanced stuff. So yeah. >> Great. and then maybe some of us can shop your possibly to be created Christmas and holiday decoration site. So you let us know >> back on then >> you let us know if that goes live. We'll drop into the show notes. Thank you so much for joining us and sharing your workflows. >> Thanks Claire. >> Thanks so much for watching. If you enjoyed this show, please like and subscribe here on YouTube or even better leave us a comment with your thoughts. You can also find this podcast on Apple Podcasts, Spotify, or your favorite podcast app. Please consider leaving us a rating and review, which will help others find the show. You can see all our episodes and learn more about the show at howiipod.com. See you next time.