Speaker 1What are software factories and why is it going viral? I mean, it's basically this concept that allows you to use AI agents to actually ship software that isn't sloppy at all, that is more like a factory, more like think about an assembly line and you're just, instead of building physical products, you're building software. And that's kind of the dream. I mean, if you're able to just create this factory that builds software and it's valuable software and you can create multiple apps that generate revenue and add value to people's lives, that sounds pretty good to me. So in today's episode, I brought on Ross Mike and he clearly explains the entire process. By the end of this episode, you're going to understand how to set your own software factory up yourself. So enjoy the episode. I can't wait to see what you build. There's a reason why this concept is going viral and I'll see you at the end. Today's episode is brought to you by Brex. My company's been on Brex for a year and a half. And I started because I kept hearing... I kept hearing companies like Vercel, OpenAI, Anthropic were using Brex and I figured if they're using it, why shouldn't I? It's been a game changer. The thing that got me is how smooth it is. It's got high limit cards. It's got banking. It's got AI that handles the back office busy work like expense reports, which I don't want to do on its own. It's really just built for this agentic world. If you're building something new, it's time to get Brex. Check it out at brex.com slash solutions slash startups. Link in the description. Mickey, welcome back to the pod. By the end of this episode, what are people going to learn?
Speaker 2We're going to understand what this bizarre phrase software factory means. I'm actually going to show you how I run mine. It's a lot easier than you think. And it's definitely model and harness agnostic. So you don't have to purchase some different product to have a software factory. It's going to be fun and it's going to be simple.
Speaker 1Okay. So you're going to be learning how to run a software factory. So you're going to be learning how to run a software factory. So you're going to be learning how to run a software factory. I'm going to explain what it is, why it matters, how it works, how to think about it. By the end of this, people are just going to be able to boot up their own software factory if they want. Or if they think, you know what, this Ross Mike guy, I don't like software factories. I don't like what he's saying. They can pass. 100%.
Speaker 2100%. With the term software factory, there's been a lot of startups who've started. And I'm not here to knock anyone's hustle. But a software factory is complete. It's completely harness and model agnostic. Meaning it doesn't matter what model you use. It doesn't matter what harness you use. It should work. Right? Because a software factory is more about someone's workflow skills and domain knowledge. And it's packed up in specific skills that they use in their development process. Now, I want everyone to think like the last app that they built. You probably went on Codex, Cloud Code, Cursor, whatever it is. And you just typed, right? You said, I want to build this. And it built it out for you. You saw it. And you didn't like it. And then you made some changes. Right? And you saw the changes. Maybe you liked it. You deployed it to Vercel or to production. And you're good to go. Or you kept on iterating. That's the process. The whole point of a software factory is in each step of the development process, how can I best maximize the model's capability to get the greatest output? Right? And also, how can I move fast? Right? Because if we're using the term factory, there's some sort of structure. And speed. And conveyor belt nature that allows me to ship as quick as possible without losing quality. That's the long-blooded Michael Shumalis definition of software factory. I haven't lost anyone, hopefully, Greg.
Speaker 1That was perfect. Okay. So, understood. But, like, why does that matter?
Speaker 2The reason why it matters is intelligence is continuing to increase. We have amazing models like GPT-6 Astra. A good software factory allows... It allows you to systemize and use these models in a very efficient way versus just typing in and continuing to go back and forth. And I think it's better I just show you how mine works to give people an idea. Now, I'll give... My skills are available for free. No charge. Nothing like that. But I don't want you to blindly copy me. I would like for you to think about it, understand the process, and then apply it yourself. That being said, I have about five or six files that make... My software factory. I have an agents.md file. And for everyone who might not be aware of what an agents.md file is, it's basically this one document, this one markdown file that's injected into the system prompt. Sorry, not in the system prompt. That's injected into the agent chat every time you communicate with an agent. So, every time I say hi, if there's an agents.md file, before the hi is sent, the agents.md file is sent. And what's cool about this file is I can sort of dictate how I want the agent to... And we actually did a video not too long ago, Greg, where I talked about most people's agents.md file is useless because they were telling the agents.md file what the code looked like and already information that's in the code base that the agent can already know about. But if you look at mine, there's a simple workflow. And this workflow is something that's not native to the agent. So, it explains clearly how to do it. And I'll walk you through every single step. The first step is isolate. There's a skill called newfeed. And this is what it does. It says, every new feature starts in the fresh Git work tree branched from origin main. So, agents can work in parallel without conflicts. Never build on main. And if you know, when Michael is on Greg's channel, there's always diagrams. So, we're about to draw. So, with the first step, when I'm working on a project and I tell it to work on a feature, the first thing it's going to do is isolate. And what this basically means is you can think of... Greg and Mike's app. You can think of Greg's and Mike's app like the journey being, you know, we started here. We started prompting here. And this is when we launched a production. We've got thousands of customers. The way most people work with their agents is at every single step of the journey, they're building a feature. They're building a feature. They're building a feature. And it's a very linear process, right? One feature at a time. One feature at a time. One feature at a time. And if you... If you ever try to work on multiple features at the same time, sometimes there's conflicts, there's issues. People have, you know, oh, my agent deleted this file and overwrote this file. What this first step isolate does is the following. I'm going to show via diagram. So, let's say Greg was like, I really don't like our landing page. And I'm telling Greg, you know, our API calls can be faster. When Greg works on this feature, what the agent does using myagents.md, is it's going to create a new branch. And you can think of a branch as a copy-paste of the exact moment where the app is. So, Greg is going to work on a new branch, a new work tree of the app. A work tree is basically a copy of the app. Like, you can think of someone copying a block of text, pasting it in a new document, working on that document, and at some point going to merge it back in the original document. So, that's what Greg is doing. He has a new document working on that feature. And guess what? Mike has another feature he has to work on. So, I can do it at the same time or I can do it a different time. I now have my own branch. Here's what's cool. Me and Greg and another person or you yourself with 50 different agents can work on multiple features and there's not going to be an issue of one agent overstepping on another agent's work. This happens a lot to people. Have you ever seen tweets, Greg, of people saying, man, like I was working on this. And the agent deleted a bunch of stuff? Almost always, it's because people have their agents working on different features on the same branch. And the agent will do what you tell it to do. So, you told it to update the landing page, but then you also told it to make the API calls faster. And now, it's noticing, oh, these pages, the way they're calling the API suck. Let me delete these and write these again. But then it was working on a design on that page. So, issues start to arise. Isolate allows me. To work on multiple features at the same time, parallelly, without having an agent overstep on an agent. This is the first step of my workflow. This isn't native to the agent. So, this makes sense to exist in the agents.md file. And when Greg is done or when I'm done, and I'll explain like the workflow for this, but just to close the loop. When Mike's done, all I do is merge these changes back. And then what Greg's done, he can either do it before me or he can do it after me. But we're merging into the main document. And there's not going to be conflicts because we worked on a copy at first. So, this allows me to ship fast with multiple agents. If I show you, and I can maybe show here. If I show you my terminal, if you notice, there's four tabs of Bezalel. Three of them finished. But I literally have four different features on the same exact app. One's working on an email client. The other one is working on a computer environment, a Linux environment. The other one is doing a landing page update. So, I can work on these confidently while still having isolation. It's not native to the agent. This agents.md plus the new feature skill allows me to do that. I'll pause here. Any questions, Greg, so far?
Speaker 1Yeah, I mean, it's like crystal clear. The way I think about it is if you actually had a team, of engineers and you are trying to build an app. obviously wouldn't be building it all on main and having everyone just being pushing to main and stuff like that that just doesn't make sense i think um you know i'm non-technical and i think you have all of a sudden all these non-technical people starting to build apps and they're running into this uh you know you you basically made mention you're kind of like oh hey man like sometimes it happens that agents overwrite stuff i mean the truth is 95 percent of the time if you're built you're gonna have agents kind of mess up and overwrite things so this is like to me this you know makes a lot of sense and it's sort of a bigger idea which is how do you structure your you know the way you work with agents to be more like a team versus uh you know
Speaker 2yeah no just more like a team yeah i mean and i mean it's a better name uh team is better than
Speaker 1team but that's basically that's why i'm the marketer and you're the uh the engineer but yeah that's basically what it is right so isolate sounds like some sort of like whey protein that
Speaker 2yeah so if you guys check the link there will be a name update very soon but that's basically what this does it allows for me to have multiple agents working on different tasks all at the same time without overstepping each other right and there's also a cleanup process i won't get into like once branch like once the work is merged in the work tree gets deleted all that type of stuff happens so that's step number one number two is the actual building and this i find has this was a skill that i shared originally way back but now it's part of my workflow and i shared it with everyone is code structure we are going to talk about models soon uh but one thing about uh the models is they are great at doing the work it just might not be done the best way right especially when writing code um there's for example fable is i would say one of the first models to really write code that i would say huh like this is better than some of the best engineers i've seen right like fable runs writes really good code but even astro which is workhorse most powerful model my favorite model some of the code quality decisions it makes is and it's not that the model is not capable the models is just getting it done and if it could get it done in a sloppy way it'll get it done in a sloppy way what the code structure skill does it writes it in what's called a service letter architecture won't bore everyone but basically it's written in a way where let's say you had you needed human intervention you hired a developer very easy for the developer to catch on or you yourself are a developer very easy for you to catch on but even for your agents for them to come back to the code and read the code they'll be like oh like yeah like it makes sense like i've had like i've had gpt 5.6 all right code and it works it does what it's supposed to do but then i'll have fable review the code and fable will be like this is disgusting like there's duplications there's functions all over the place there's dead code right so just because it works doesn't mean it's written well this skill gives the agent a guideline on how to write code so going back to this diagram again i'm working on a new feature right the first thing that happens is isolate the second thing that happens is and i'm going to i hope people are seeing the factory nature of it the second thing that happens is the building and in building we're using a skill called code structure and basically in this process when i'm telling the agent oh build me uh this ending page build me uh this feature uh for example i've been working on this app and the one feature that i wanted built is i wanted a skills like repository where i can have different agents of mine connect to this app and store the skills and i basically told the agent build me that and as it was writing the code it kept referencing the code structure skill so it started to write code in a way that me as a developer i can review but you know god forbid i need to hire somebody to review the code it's not going to be the slop canon where they're confused and they don't know what to do or they overcharge you it's written in a way for a developer to understand and i find that it's not going to be the slop canon where they're confused and they don't know what to do or they overcharge you it's written in a way for a developer to understand and i find that if you use another agent that doesn't have context on your code base it will understand it very well so first we isolate excuse the bad name second we build right and all of these are done in an opinionated way that allow the agent to move fast and to do the thing as best as possibly can be i think this makes sense right greg yep keep going so step number three is prove here's the thing um you know agents can't pinky promise right so like if you push an agent enough well gpt six astra is the reason why it's a big leap in model capability is like it like the like it is the least hallucinating model which is fantastic but like that model aside most models you can kind of push to like lie or to believe something or sometimes it'll straight up be like oh i actually realize i didn't do this work for you so one thing that i have to do is i have to be able to have the agent prove the agent do is to prove the work that it did and this is probably my favorite skill there's two skills involved in this evidence-driven testing and basically what evidence-driven testing does if your machine has the capability to do it it will literally record the before state meaning before the feature or let's say you're trying to fix a bug it will record the bug in action and what it will do after is after it's done fixing it will record the bug in action it will record a working version after right so this is what evidence-driven testing does it proves that the fix actually was made because you'll be surprised sometimes the agent will write the code and it'll think it worked but it didn't test it or it didn't prove that it worked and it just told you it worked so i need to make sure that the agent actually proved this work but let's say let's say your machine doesn't have the capability to do that there's another skill called before and after and i can actually prove that it worked so i need to make sure that the agent actually proves actually let me pull up a pr to show this greg because i think it is better show you than i tell you this is a pr my agent made i didn't make this the agent made this and i wanted it to create an adamant email page and connect an email service that i made look at what it did it showed me a before state where the page didn't exist it just it didn't and it shows me the after state right so for every feature that i'm building every pr that i'm doing i am getting a before state and after state and the reason why this helps this helps me like i'll be honest i'm not reading all my code nowadays like i might like okay did this uh like let's see like barely it's a skim it's a skim situation i'll be honest the skims have even become less and less now but a lot of things that i'm doing now is i'm working on the front end where i make sure that it's following my code structure skill and i make sure i'm getting before and after screenshots right i can even pull up let me pull up another um example here's a more prominent example where i was working on a specific uh computer feature where i wanted to give my agent a computer and it just didn't work right the first run didn't work um i didn't even have like my software factory set up i was working on a different machine and it pushed the code and it didn't work as you can see nothing's going on i told my agent it didn't work use the skills use the factory and this is the after screenshot with it actually using the app right so these skills the prove and the before and after force the agent to give me factual like a before and after proof whether it's a video or it's screenshots and there are times where it'll do the before but after and it'll be like oh i just looked at the after screenshot or the after video and i didn't really finish the feature so i'll go back to what i'll go back to building right this is the factory nature of it i didn't have to tell it oh that yeah you failed your before and after go finish the the skills are written in a way where the agent knows okay the before and after criteria hasn't been met i have to go continue on building right so this gives me a visual representation of the work that's been done right so this gives me a visual representation of the work that's been done and makes me feel like i'm reviewing especially if you're a non-technical person it makes reviewing easier because you know i just look at some screenshots or a video right so in the building process at some point i'll have a pr where i get to see before and after and even though i might not understand all this mumbo jumbo it it will it will explain it will show me visual um proof that the work's been done now i already hear somebody asking what if the proof is not visual and there's actually uh a pr i'll show someone performance i think it's this one okay so i wanted to do another example here i wanted to do a performance update meaning for one of the apps i was building the clicks weren't snappy enough like you can see now everything is snappy it's loading fast that wasn't the case so i told the agent fix it and it did and it did end up giving me screenshots but let's say this was like something that it couldn't give me screenshots for it will write tests and then it'll give me the results in this case it checked the speed at which the page was loading before in this case one of the pages 815 milliseconds this is a sin in web development like this cannot happen and mind you this was written by gpt 5.6 soul right great model but it got it down to 60 817 61 so i have again actual proof by the agent that it's done what it said it did in the review process i'll pause right there anything i've missed so
Speaker 1far gregor does it so you know if you're trying to build a a software factory trust obviously is going to be a big part of that and i think what you're saying is hey we're if you know you're gonna if you're gonna have all these agents you know building features building apps we need to be able to trust the things that it's going to create so what you're saying is uh here are a agent manager where in this case mickey you're like you are the agent manager right you're not you're you're not deep in the code anymore you're kind of just looking at what's happening and what's cool about um the before and after visual stuff is it's kind of good for him you know millennials and gen z or people on you know instagram stories or snap stories stuff like that it's almost like you're just like clicking through story to story yes yes no like it's it's it's bite size basically that's
Speaker 2literally it right there right it's it's allowing me to build trust with the agent because and what's funny is like you said earlier it kind of clicked in my head this is what like normal organizations used to do with their engineers right it's like you build a feature and then there was someone whose job like a senior engineer whose job was to review your work and you would have this pr with this description and it would show okay basically this is the work that i've done and this is the test that i've written right so it's basically the same thing except now we're doing it with machines like that's essentially it and an example of the video um this is a this is me using cursor cloud agents it says proof of improvement and like this is a video of the agent at work using the app right so this allows me to your point like instagram tiktok i can watch this and see all right okay the agent actually built this and it works this makes it easy for me to not have to read code and i can just merge away and live my best life and go outside and touch grass so there's that now we have one final step and that is to build trust with the agent and i'm going to show you how to build trust with the agent and i'm going to show you how to build trust with the agent and i'm going to show you how to build trust with the agent and i'm going to show you how to build trust with the agent and i'm going to show you how to build trust with the agent step which is the ship step now the ship step i mentioned before and after but there's this skill called grep loop which uses a third-party service named greptile which is a code review agent now you don't need to use a code rate code review agent but if you're really serious about building software and it's going to be used by users i highly suggest using some code review agent greptile is my favorite code code rabbit macroscope there's tons of good ones out there but me using greptile they have this skill called grep loop and basically what this does and i think i'll show it with this pr greptile leaves these summaries and then it gives feedback for example this was the initial feedback it gave um on the pr there was some issue with you know pagination right here some menu space wasn't preserved so it gave this feedback meaning the agent that wrote the code missed these things and that's fine it happens right even humans miss these things right but what happens is greptile not only gives feedback it gives a confidence score now this is a five out of five because after the feedback was given if you see my name and then this line over here the feedback was addressed my agent addressed the feedback but before the feedback was addressed this score was a three out of five what that tells my agent is that there are things that it missed and it needs to look at it what the grep loop skill does and by the way this happens automatically someone doesn't have to write grep the agent will do it as follows it says it opens the pr with the before and after proof embedded in the description whenever the change has a visible surface measure numbers or output pairs when it doesn't it'll give you numbers right or screenshot and then look what the agent does it runs grep loop or grep grep apps the difference is grep loop apps if your file change was like ten thousand lines plus um that skill activates and you don't have to worry the agent does it itself but look what it does it says greptile reports five out of five until you get a three out of five so it's a three out of five so it's a three out of five so it's a three out of five so it's a three out of five so it's a three out of five so it's a three out of five so it will go back to build so check this out let's say we're at the point let me write this down we're at the point we're at built we're at um ship right and it's now running grep loop when i get a feedback score a confidence score and it's three out of five what now happens remember we were talking about loops this is actually a good loop what happens is this goes back to building now the agent goes back to step two it starts to build after it builds what it is what does it do it proves and then it ships and here's what happens automatically the agent will wait for a new score greptile then gives us a four out of five we caught some things but there's one final thing we missed go back to building right it builds it proves and guess what it does greg it ships and now i have a five out of five when i have a five out of five what's left now is for me to merge and i think maybe i have an open pr right here so i can show you what that looks like what's left for me is to just click merge when i click merge what happens is this is finally back in the main copy of the app of the main version of the app and i did this while working on 15 either simultaneous version uh features 15 different features with different agents sub-agents all that type of stuff what this allows and this is the factory nature it allows for an agent to have an isolated instance where it can work on its own it has guidelines on how to build it has a methodology to prove its work and then it has an external service proving its work to checking its work and if its work is not up to standard it has to continue in a loop working until that standard is met once i get a five out of five this is when i enter the picture this is what a software factory is notice we didn't talk about model we didn't talk about harness it's all workflows skills and a little bit of domain knowledge right not everybody works the same this is how i work but i found great results with this i'll pause right here greg let me know what i need to further explain our
Speaker 1our add-on i i'm like what's clicking in my head is just really this physical factory analogy for a software factory so just to like summarize i'm going to tell you how i'm i'm singing i want i want your thoughts so like the isolate piece and the step one um that's like a factory taking a custom order and you know giving it its own station so it doesn't mess with the rest of production right so you you you know you called it a work tree you know in software it's a branch a work tree an isolated environment but you know that's the basic concept yes number two uh build right build is the assembly line so the agent is actually like cutting and welding and assembling and wiring the product um obviously in software you're not doing that you're writing code you're changing files you're adding structure to things you're you're actually creating something that's real in a software in a software sense um step three is the proving step which is basically a fancy way of saying quality control basically yes basically right like before anything leaves the factory someone has to test it you're not just going to like create a product and not have people test it like does it turn on does it does it fit does it break under pressure like all the things i you know i'm picturing like a car factor or something like that in software you know you can run tests like um well you can run tests you can preview it you can do logs you and you know what you showed and then lastly the shipping piece um it's basically like once it passes quality control you know it's going out the door um but there's going to be some things that you have to like let you know uh you're gonna have to merge it you're gonna have to deploy the pr you're gonna have to do release notes you're gonna have to you know give feedback back to the product team because maybe it doesn't pass quality control and then you have to like do that
Speaker 2loop again right exactly i think i might actually rename everything you like i've written to what you said because like now i'm realizing like oh yeah my names are terrible that says make sense
Speaker 1that's exactly how this works cool so basically what we're doing here is we're taking a factory
Speaker 2and we're making a software factory basically so and this is why like i've seen again not to knock people startups and products and stuff like that like a software factory is not a product it's not a special harness it's not a like oh this company built a software no a software factory is literally just a bunch of markdown files and this is also another insane thing off topic maybe a different video is some startups are now an agent with a couple markdown files right we've really entered that time so i uh hope uh this made sense for everyone and it excites everyone i'm very excited with the time we're in right now because a lot of things are possible now 100 i mean no this is this
Speaker 1is insane that you're actually able to do this it's cool that you people like you are like sharing this because I think it's worthwhile. I want to just do one quick note on GrepLoop or any code review software. I think if you're serious, no affiliation with GrepLoop or anything like that, but I think if you're serious about creating software, having some code review software is pretty... I don't understand why you wouldn't use a GrepLoop, a CodeRabbit, one of these tools.
Speaker 2Because again, if you have in business and I know because a lot of business people are watching, we take the service we provide and all that stuff seriously, but it seems like with building software, we just don't care. And if you have people who are going to use your app, I don't know, there's a level of empathy I have for the user on the other side and a lot of these startups, because they've raised bajillions of dollars, they have a lot of free tiers. You can cycle through free tiers and use a bunch of this stuff for free, right? So I highly encourage, if you're building something that you're serious, you're passionate about, I would use a code review agent of any kind.
Speaker 1Cool. Thanks for coming on. Thanks for sharing the sauce. I'll include links for where to follow Mickey on the internet, on YouTube, all those places, his software that he's creating to go give him a follow and dude, I'll see you next time.
Speaker 2I appreciate you, Greg, as always. Thank you, everyone, for showing love and watching and yeah, we'll see you in the next one. one.
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