Nova: What can a software engineer, someone who builds logical, ordered worlds out of code, possibly learn from a man who finds purpose by running 200-mile races and carrying 130-pound rocks up mountains? It sounds like two different planets. But what if I told you they're both running on a surprisingly similar operating system? An algorithm for excellence built on one core principle: relentless, obsessive work.

asoiso for apple: That’s a fascinating premise. It’s the kind of cross-domain connection I love to explore. You’re looking for the universal source code behind success.

Nova: Exactly! And that's why I'm so thrilled to have you here, asoiso for apple. With your analytical mind, you're the perfect person to help us deconstruct this. Today, we're diving into Cameron Hanes's book, 'Keep Hammering,' to break down that very algorithm. We'll tackle this from two angles. First, we'll explore the foundational mindset of rejecting 'average' as a baseline for success.

asoiso for apple: Setting the initial parameters of the system, so to speak.

Nova: Precisely. Then, we'll discuss the practical, if extreme, strategy of over-preparation, and how embracing the 'unnecessary' can make the necessary feel easy.

asoiso for apple: I'm ready. Let's dive in.

Nova: So, asoiso for apple, let's start with that foundational code. In the book, Hanes has this moment of revelation that completely sets his trajectory. It's not a dramatic event, but a single, cold statistic.

asoiso for apple: Data-driven decisions. I like it already.

Nova: Right? So, picture this: Hanes is a young man in his late teens, feeling a bit lost. He's working a low-wage warehouse job, drinking beer, feeling like a 'small-town loser.' Then a friend, Roy Roth, calls him up and says, "Dude, you need to bowhunt." This call to action sparks something in him. He gets a bow, practices, and goes on his first hunt. He gets a shot at a massive bull elk... and he misses. Completely.

asoiso for apple: A classic failure state. The initial run of the program crashes.

Nova: A total crash. But instead of quitting, it ignites an obsession. He dedicates himself to it. And in his research, he discovers a key piece of data: the average success rate for a bowhunter hunting bull elk is about ten percent. One in ten.

asoiso for apple: So, a 90% failure rate is the accepted norm. That's a tough metric.

Nova: For most people, yes. But Hanes's reaction is immediate and visceral. He writes, "That’s never going to be good enough for me. Never was, never will be. Average sucks." In that one moment, he completely rejects the baseline. He decides he's not going to operate by the same rules as everyone else.

asoiso for apple: That's a powerful moment. It's like encountering a system requirement for the first time and immediately deciding it's unacceptable. In tech, you often see benchmarks for performance or error rates. The standard might be 99.9% uptime, but the best engineers I've read about are obsessed with that last 0.1%. They don't accept the 'average' standard. It's a fundamental choice about the quality of work you're willing to produce.

Nova: Exactly! So it's not just about the number, but the decision to reject it. How does that apply to someone just starting out, like in your first year as a software engineer? Is there a temptation to just meet the 'average' expectation?

asoiso for apple: Absolutely. The 'average' is just getting your assigned ticket done by the deadline. You fix the bug, you implement the feature, you check the box. The system works. But the 'Hanes' approach, the 'average sucks' mindset, would be to not just complete the task, but to truly understand the part of the codebase you're working in. It means writing cleaner, more efficient code than what was there before, adding comprehensive comments, and writing robust tests to ensure you leave it better for the next person.

Nova: So it’s about improving the entire system, not just patching a hole.

asoiso for apple: Precisely. It's a much higher bar, and it takes more effort upfront. But it's what separates a competent coder from a great one. It’s the difference between just doing a job and mastering a craft. That rejection of 'good enough' is the first line of code in a program for excellence.

Nova: I love that analogy of leaving the codebase better. It perfectly sets up this next idea, which is the 'how' behind rejecting average. It's one thing to say 'average sucks,' but Hanes's method for living that is... well, it's extreme. It's a principle of overkill, of 'training hard to hunt easy.'

asoiso for apple: So this is the execution of the algorithm. The practical application.

Nova: Oh, it's practical, but it sounds insane. There's this incredible story in the book. Hanes is at a Cabela's store giving a seminar, and he's talking about his training, which includes daily runs up a local mountain called Mount Pisgah. To demonstrate his commitment, he tells the audience he's going to carry a rock up the mountain after the talk.

asoiso for apple: Okay, that's a bold claim. A live demo.

Nova: A very live demo. So a group of guys from the audience follows him to the mountain. He finds a rock he thinks is about 70 pounds. He hefts it onto his shoulder and starts the climb. Now, this is a trail he normally runs up in 15 minutes. The carry, he says, was pure agony. It took him two hours. He was in immense pain, but he refused to quit. He gets it to the top, and this becomes a new weekly ritual for him.

asoiso for apple: That’s intense. But the key detail for me is the time difference. 15 minutes versus two hours.

Nova: Right! And here's the kicker. Later, out of curiosity, he takes the rock to a scale. It wasn't 70 pounds. It was 130 pounds.

asoiso for apple: Wow. So, from a systems perspective, what he's doing is intentionally introducing an extreme stressor to recalibrate his entire definition of 'difficult.' It's not just about getting stronger in a linear way. He's manipulating his own psychological baseline. After carrying 130 pounds for two hours, a simple 15-minute run up the same hill must feel like floating.

Nova: That's such a great way to put it! 'Recalibrating the baseline.' So, what's the software engineering equivalent of carrying a 130-pound rock up a mountain? It's not literally... well, carrying a server rack, I hope!

asoiso for apple: (Laughs) No, not quite. But the principle is directly applicable. The 'rock' is a self-imposed, seemingly unnecessary challenge. For example, instead of just learning a new programming language for a project, you decide to build a complex application from scratch using it on your own time. Or you find a bug in the open-source library you're using and you decide to learn the entire contribution process to submit a fix yourself.

Nova: So you're going way beyond the scope of the immediate task.

asoiso for apple: Exactly. It's doing something so far beyond the immediate requirement that when you come back to the actual task, it feels simple. You've already done the 'hard' thing in a low-stakes environment. You've built a massive buffer of knowledge and confidence.

Nova: So it's about creating your own challenges to build a massive capability buffer.

asoiso for apple: Exactly. A buffer. That's the perfect word for it. In engineering, you design systems with buffers and redundancies to handle unexpected loads. Hanes is doing that for himself, both physically and mentally. It reduces the risk of failure when it actually counts, whether that's drawing a bow on an elk or deploying critical code on a Friday afternoon.

Nova: This has been so insightful. We've deconstructed this 'Keep Hammering' algorithm into two key functions: first, a core command to reject 'average' in all its forms.

asoiso for apple: Right. You have to set a higher standard for yourself than the one that's given to you.

Nova: And second, a practical routine of 'overkill' preparation to build a resilience buffer, making the real challenges feel manageable.

asoiso for apple: It's a system built on a non-negotiable principle and executed through extreme, baseline-shifting practice. It's surprisingly logical, even if the application is intense. It's about building a personal operating system that's robust, resilient, and optimized for high performance.

Nova: It really is. Which brings us to our final thought for our listeners. We've talked about Hanes's 130-pound rock, this symbol of extreme, voluntary hardship. So, the question for you is: What is your 130-pound rock?

asoiso for apple: That's a great question to end on. It's not about the weight, it's about the principle.

Nova: Exactly. What's one, seemingly unnecessary, uncomfortable practice you could adopt in your own life or career that would fundamentally recalibrate your definition of 'hard' and make your everyday challenges feel easy? Something to think about. asoiso for apple, thank you so much for helping us break down this incredible mindset.

asoiso for apple: My pleasure, Nova. It was a great conversation.