But before we get into that, I just want to recap like, you know, what's been the journey that we've been on. Right? So we started, you know, code coding agents took off, and a few people got really, really good leverage, right? And I think all of us were kind of asking like, is this AGI? You know, like did we achieve it? Then, you know, companies took that and said, "Well, if one person can do so well, let's just get everyone and let's mandate it." And like token max, right? And that was clearly a a galaxy brain moment, right? And then the inevitable happened, you know, AI slop shipped, and there's a bunch of sev twos. I'm not going to name which companies, but you know, essentially you saw people kind of retracting. They said, "I don't think I don't think this is the best option here." And eventually model prices you know, climbed. We saw, you know, people figured out that tokens have to be paid for. Like you just can't token max your way through life. And budgets got bolted on. And you know, essentially money is being lit on fire, and the money has to come from somewhere.

So, given this journey, I want to actually like this is the enterprise journey, right? And what does that do for a single developer? And I think this is an important framing cuz it really talks about people as a part of a team, right? And I want to look at it from like two axes. So, there is the fear axis where people lie on the spectrum, right? They're coming It's like Is it coming from my job? Like am I going to be out of a job? Or is it like a really handy tool? And they're really, you know, they're not that fearful. Versus like the confidence they have in how much they're executing it. So, they can either use it a lot or they can use it, you know, not that much because they don't really know how to use it that well. Now, when we started, like people said, "Oh, you know, what is this? Is this the end? Like am I needed?" And fear was pretty high. Utilization was pretty low cuz people didn't really know how to use it. And then when a few people got outsized leverage, you saw, you know, early adopters basically people saw them and people said, "Okay, well, it looks like I'm still kind of needed if I figure out how to use this thing. So, let me actually try using it, right?" And then we saw, you know, mandates and token maxing, and people kind of got a little skeptical. Like confidence stayed the same, but people tried to use it a lot more, right? And then we realized, uh you know, there's a bunch of slop shipping, there's self-tours, and I, you know, it's like I'm not really that scared cuz, you know, it just slip it just ships slop. Like I'm going to still be needed. And they don't even know how to use it that well cuz like now the confidence is greater, right? And so you got to figure out how to get people from all the way wherever they are on the spectrum to where they're not fearful and they're actually using it a whole lot more. And this is the framing that I want to like I want everyone to keep in mind as they're actually trying to get a team to adopt good like AI usage and good AI patterns, right? And so, the The is, you know, what does it take? Step one, create a Cloud MD. Step two, add some skills. Is that it? Do we like solve it? You know, I think we all know like you guys are here because like clearly life's not that simple and like stuff's messy, right? And I think a few people might ask, you know, why doesn't this work? Like isn't that what like everyone does? And I want to like just talk about a few things you might see that actually indicate that yeah, like this isn't working.

And so, I guess everyone's kind of thinking so, you know, how do we solve this correctly? And so, I think the first thing to realize is we need to frame it correctly, right? It isn't really an IC's job. It's a job for leadership. It's a job for the company, right? Making engineers work well with their agents is truly the most impactful thing you could do as an organization. Because that's going to enable your engineers to ship faster and with confidence and avoid, you know, a lot of incidents. If we live in this figure it out for yourself paradigm, like people are going to get outsized productivity, some people aren't, and like the people who are generating like 10 PRs a day are going to like look like, you know, gods compared to people who are shipping like one to two. And the one to two PR people are actually going to get left with the review burden. And that's actually a really, really bad thing. Cuz now not only can they not ship, they're going to actually see bad code and then curse the agents and hence not be able to get on to the let's ship 10 PRs, right? And so it's really important to do this. If it's a problem facing the team, there's a few things you can do, right? The most impactful things that you can do to set up your code base to like make it work well require team buy-in. You can't just like if you want to change the way your code base is organized, you can't do that as an IC, right? And if you're treated as a leadership problem, then you can do things like this.

So, you know, enough gyan or as like it's more like the Hindi way to say like, you know, I'm enough prof like I'm kind of giving you sermons. But, like, how do you really do this, right? Like, these are all principles. What's the real playbook? So, here's what we did and here's like I'm not going to over like emphasize on this is the exact way to do it, but this is like roughly how we did it and you can take from it what you choose. The first thing is do the basics, right? You got to do them right. Progressive disclosure, I can't emphasize this enough, is really, really powerful, right? Find your best ICs and find what how they are making the code base work for them. Take those practices and pass them or guide. People can't live in their own practices. And this is really hard for engineers to do it. It's basically accepting that my setup is imperfect. And like engineers don't like to hear that. But you got to figure out a way to find those best practices and ship them across. Make sure that that's kind of a shared setup.

The second thing we did was there's one high value skill that we invested in. In our case it was this thing called ship it. What it did was the moment you're done with your code, it takes care of everything from code done to PR ready for review. Which means you got to open a PR, figure out your opinions, handle the handle all the comments, you know, handle all the PR descriptions, the merge comments, everything, right? It handles CI failures. It basically runs through these loops. And what this meant was often the skill was running for over an hour. And that scared people, but once you actually figure out once they saw the value, they get invested, right? Because it's one skill which tells them, "Okay, this AI thing can actually work for me. I don't need to constantly baby sit it. I can trust it."

The third thing and really important is to close the loop, right? So we wired issues and boards into the repo. Like we added CICD. We added gigantic reviews. We have like a code gardener that actually goes back and looks through a whole bunch of like every night it'll run and look at the code and check if something like not organized correctly. What does correct organization mean will depend on your code base. Get people invested and I can't emphasize this enough. You have to win over the skeptics. It's really easy to say like the skeptic is just someone who's scared. It's really hard to get them to buy in, but if you can get them to buy in, you know you're doing something right. You have to get them to be able to edit and play with the shared setup cuz that's the true way you know that they're actually invested, right? And this is where you got to it ensure you're iterating constantly. If people are like and this is the hardest thing for engineers again cuz you're basically saying I'm never going to like get to perfection in my setup. But you got to be okay with that. You have to do it and you You to treat it like, you know, X% of your IC time is probably going to be spent on it trading on this thing, which is not going to lead to like meaningful PRs like up front, but it's useful and it's worth it.

And I think the biggest like the easiest way to say this is instead of saying like the model is so dumb, like we have to ask how can I make it smarter or how can I edit like and not This is where I have like crossed out the my. It's not a personal setup. It's the shared setup that you have to invest in. And it's a mindset, right? You have to go full send. And like I want to end you with I want to end with this. Like, I learned skiing like a couple years back and the first like the hardest thing for me was you actually have to commit to it. If you're pizza braking, you're going to crash. Like, no matter what. You have to commit to the speed in order to actually get and feel like, okay, that's how I can turn and that's how I can truly ski. And so, I'm going to leave you with this. Like, just be okay with be okay with failing. You have to, you know, go full send and be okay with falling. It's fine. The point is to be able to recover from that and that will allow you to truly feel the AGI. Yeah, well, that's that's me and I'm happy to take any questions.

Yep. Uh so, the I'm going to repeat the question for the recording. Uh strategies that you found best for progressive disclosure. So, I think a couple things, right? Uh the first thing is even in your skill.md files, don't overload it. Like, we've kind of set a hard limit for like 100 lines in your skill.md cuz your skill is really a folder. So, that's step one. Make sure and I think I spoke about this during the talk, but when you have like some code that requires like a runbook, make sure the runbook is reflected in the comments so that if a code if somehow the code like the agent figures its way into like grapping into the code base and find that file, it knows I need to go look at this for like all the description of how this is relevant. Right? You have to organize and I think this is why I talk about harness engineering because your entire code base can be set up to encourage progressive disclosure. Don't overload your cloud MD or your agent's MD file into like one big thing. You want to make sure that like it's a thin index that can point through the right files and that's what the agent gets in its like first prompt cuz that's what gets loaded when it starts to work. So these are like some really powerful strategies that and the way you know this is working is when you give it a prompt. When you give it the first prompt, see what it's doing. Is it grabbing or does it know where to go? But how much context is it burning when it like immediately? So is it like I think like 20, 25K tokens get taken anyway, but like how much more is getting added? If you're coming to like 40K, 50K, like something's wrong. That's not really progressive disclosure. So you have to figure out these boundaries and then like based on this it's an iteration cycle. All right. Well, if there there aren't any other questions, feel free to find me. Happy to talk about harness engineering in general or like anything else, but yeah, thank you for listening.