Building a Software Factory that actually works (Full Course)

0:00What 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, on today's episode, I brought on Ross Mike and he clearly explains the

0:37entire process. [music] By the end of this episode, you're going to understand how to set your own software factory up yourself. [music] 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 companies like Vercel, OpenAI, and 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

1:09cards, it's got banking, it's got AI that handles the back office busywork 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/solutions/startups. Link in the description. The startup by the contrast. [music]

1:32We're sipping time, baby. Mickey, welcome back to the pod. By the end of this episode, what are people going to learn? We'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

1:55and it's going to be simple. Okay, so you're 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 I don't I don't I don't like software factories. I don't like what he's

2:13saying." They can pass. 100% 100% With the term software factory, there's been a lot of like startups who have started, and you know, I'm not here to knock anyone's hustle. Um but a software factory is completely harness and model agnostic, meaning it doesn't matter what model you use, it doesn't matter what harness you use. Um 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, Claude Code, Cursor, whatever it is, and

2:52you 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 keep 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

3:28conveyor belt nature that allows me to ship as quick as possible without losing quality. That's the long bloated Mike Schmollis translate definition of software factory. Um I haven't lost anyone, hopefully, Greg. That was perfect. Okay, so understood, but like why does that matter? The reason why it matters is um intelligence is continuing to increase.

3:51We have amazing models like GPT-6 Astra. A good software factory allows you to systematize 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

4:20it 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 with her age what an agents.md file is, it's basically this one document, this one markdown file that's injected into the system prompt. That's inject 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

4:56act. 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 could 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

5:20to do it. And I'll walk you through every single step. The first step is isolate. There's a skill called new feature, and this is what it does. It says, "Every new feature starts in a 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

5:44to 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 uh Greg and Mike's app. You can think of Greg's and Mike app like the journey being, you know, we started here, we started prompting here, and this is when we launched the production, we've got

6:08thousands of customers. The way most people uh 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 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 ever try to work like like with on multiple features the same time, sometimes there's conflicts, there's issues, people have, you know, oh, my agent deleted this file, it overwrote

6:36this 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 um our API calls can be faster. When Greg works on his feature, what the agent does using my agents.md, is he's going to create a new branch. And you can think of a branch as a copy-paste of

7:02the 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

7:24document working on that feature. And guess what? Mike has another feature has to work on. So, I can do it at the same time, or I can do it at 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. If you ever see 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

8:02on 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

8:22page. 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 um the uh 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 when Greg's done, he can either do it before me, or he can do it after me. But we're merging into the into the main document,

9:04and there's not going to be conflicts cuz 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 Bezel uh 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 uh 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

9:37isolation. 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 back so far? Yeah, I mean it's like crystal clear. I think it's if the way I think about it is if you actually had a team of engineers and you were trying to build an app, you obviously wouldn't be building it all on main and 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. Um and I think you have all of a sudden all these non-technical people starting to build

10:16apps 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 override stuff." I mean, the truth is 95% of the time if you're build it you're going to have agents kind of mess up and and override things. So, this is like to me this is 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, yeah. No, just more like a

10:53team. Yeah, I mean and I I mean it's a better name. A team is better than isolate. I might change it to the team. [laughter] But that's basically Well, that's why I'm the marketer and you're the uh the engineer. [laughter] But yeah, that's basically what it is, right? So, it's Isolate sounds like some sort of like whey protein that I'm going to drink

11:12later. So, if you guys check the link, there will be a name of it very soon. But that's basically what this does. It allows for me to have multiple agents working on different tasks all of the same time without overstepping each other, right? And there's also a cleanup process I won't get into. Like once the 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 I shared originally way back, but now it's part of my workflow

11:42and I shared 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 Astra, which is workhorse, most powerful model, my favorite model, some of the code quality decisions it makes is uh

12:23and it's not that the model's not capable, the model's 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 layer 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,

12:53like 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

13:30factory 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 this landing page. Build me this feature." For example, I've been working on this app and the one feature that I wanted build 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

14:06way 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 cannon 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

14:30the 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? No? 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-6 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

15:13lie or to believe something or sometimes will straight up be like, "Oh, I actually realized I didn't do this work for you." So, one thing that I 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 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 a working version after,

15:53right? 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 will 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

16:16doesn't have the capability to do that. There's another skill called before and after. And I can actually, let me pull up a PR to show this, right? Cuz 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 admin email page and connect an email service that I

16:39made. 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, it did this, like, let's

17:07see, like 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 a lot of the 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

17:43[clears throat] 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 proof 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 then it'll do the after, and it'll be like, "Oh, I just looked at the after screenshot or

18:21the after video, and I didn't really finish the feature." So, it'll go back to what? It'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 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. It makes reviewing, especially if you're a non-technical person, it makes reviewing easier cuz, you know, I just look at some screenshots or video, right? So, in

18:55the building process, at some point, I'll have a PR where I get to see the 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

19:18um a PR I'll show some on 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 could see now, everything is snappy, it's loading and fast. That wasn't the

19:37case. So, I told the agent, "Fix it." And it did. And it did end up giving me screenshots, but let's say there This is like something that it couldn't give me screenshots for. It will write test, 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 850 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

20:06model. 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 far, 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 going to if you're going to 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

20:42saying is uh here are a couple skills that allow you as like the 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 um 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

21:14bite-size. Basically, that's literally it right there, right? It's it's allowing me to build trust with the agent cuz and what's funny is like you said it earlier and 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

21:47with machines. Like that's essentially an 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, Tik Tok, I 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

22:19outside and touch grass. So, there's that. Now, we have one final 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 review 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's 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

22:55this 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 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

23:20humans 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

23:39three 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 loop. The agent will do it automatically. What it does is as follows. It says it opens the PR with the before and after proof embedded in

23:59the description. Whenever the change has a visible surface, measured 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 loop ops. The difference is Grep loop ops, if your file change is like 10,000 lines plus, um that skill activates. Again, 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 resolved comments. Finished by presenting PR URL. Basically, what this means is it will The agent will take the

24:31feedback it it got. 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 where at build, where at um ship, right? And it's now running Grep loop. When I get a feedback score, 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

24:57building. 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 agents will wait for a new score. Reptile 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,

25:20and 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 a 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 Sorry, features. 15 different features. With different agents, sub agents, all that type of stuff. What this allows, and

26:02this 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 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

26:28picture. This is what a software factory is. Notice we didn't talk about model. We didn't talk about hardness. It's all workflows, skills, and a little bit of domain knowledge, right? Not everybody works the same. This is how I work. Um but I found great results with this. I'll pause right here, Greg. Let me know what I need to further explain or

26:49um or 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 seeing it and I want I want your thoughts. So, like the isolate piece in the step one, um that's like [clears throat] a factory taking a custom order and, you know, giving it its own station so it doesn't

27:15mess 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 in 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

27:47software 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 I'm picturing like a car factory or something like

28:13that. In software, you know, you can run tests like Well, you can run tests, you can preview it, you can do logs, you and you know, the screenshots 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 going to have to merge it. You're going to have to deploy the PR. You're

28:45going to have to do release notes. You're going to have to, you know, s- give feedback back to the product team because maybe it doesn't pass quality control and then you have to like do that loop again, right? Exactly. I think I might actually rename everything you like I've written to what you said cuz like now I'm realizing like oh yeah, my names are terrible. You know, what Greg says makes sense. That's

29:06exactly how this works. Cool. So basically what we're doing here is we're taking a factory and we're making a software factory. Basically. So and this is why like I've seen again not to knock people startups and 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

29:39couple markdown files. Right? We've really entered that time. So I hope this makes sense for everyone and this excites everyone. I'm very excited with the time we're in right now cuz a lot of things are possible now. 100%. I mean no, this is this is insane that you're actually able to do this. It's cool that you people like you are like sharing this cuz I think it's it's worthwhile. I want to just do one quick note on

30:05Grep Loop or any code review software. You know, I think if you're serious, you know, no affiliation with Grep Loop or anything like that, but I think if you're serious about creating software, having you know, some code review software is pretty like I I don't understand why you wouldn't use a Grep Loop or Code Rabbit,

30:27one of these tools. Something, right? Like it makes sense. Like cuz again, if you have like you know, we in in business and then I know cuz a lot of business people are watching, you know, we take the service we provide and all that stuff seriously, but it seems like with building software like we just don't care, right? And if you have people who are going to use your app, like I don't know, like there's a level of like empathy I have for the user on the other side, and you know, I like a lot of these like startups because they've raised bajillions of dollars, like they have a lot of free tiers, like

30:58you know, 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. Yeah. Cool. 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 his software that he's creating, too. Go give him a follow, and

31:23dude, I'll see you next time. I appreciate you, Greg, as always. Thank you, everyone for showing love and watching, and yeah, we'll see you in the next one.