Algorithms for Life: How to Delegate

Welcome to You To Me Research from our algorithms for life series by Valor Ingles. I'm your host. And I'm your expert. Today we are tackling the third installment of the algorithms for life series. And if you've been with us for the first two, you know we're sort of building on this idea. We're creating a kind of hierarchy of high performance operating systems. That's exactly right. It's a progression. Episode one was optimization, you know, getting your own house in order, fine-tuning your personal habits, your workflows, all the internal stuff. Right. How do you use your own time and energy most effectively? The next episode too is strategic selection. We talked about the opportunity abundance problem. You're optimized, you're efficient, and now you have all these great options. How do you pick the right path? Which of course brings us to today. Because even if you know how to optimize yourself and you know what mission to choose, you eventually hit a wall. Mm-hmm. Let's see, on a physiological limit. Yeah. You simply cannot do it all yourself. You run out of hours in the day. Exactly. You reach the absolute limit of individual scaling. And the only way, the only way to break through that ceiling is to get other people to execute your vision effectively. And that, of course, is the topic of today's deep dive. Delegation. And I have to admit, I came into this one feeling, I don't know, a little bit smug, maybe, pretty confident. I can see that. It feels like a solved problem. It does. I've read the management books. I know the standard advice. Higher smart people and get out of their way. Don't micromanage and power your team. It just feels like settled science, you know. It definitely feels that way. It's the cultural water we all swim in, especially in modern Western business. The idea of autonomy and empowerment is almost sacred. But, and there's always a but when you bring in a research stack like this one, looking at the papers you've pulled, it seems like that water might be poisoned. Poisoned is a strong word, but it's cool. At least murky, significantly murkier than the airport books for bestsellers would have us believe. Murky is a very generous way to put it. I think we're going to look at some data today that suggests a lot of the standard delegation advice, the stuff that's taught in MBA programs, the stuff you see shared on LinkedIn every single day is not just unfounded, but potentially actively harmful. Okay, well, let's rip the bandaid off then. You started the research packet with a statistic from a study by an organization called Leadership IQ and honestly reading it, it felt like a horror story for anyone who's ever hired someone or tried to build a team. It really does. And we need to set the stage for this one because the scale is important. This was a massive undertaking, a three year study involving over 20,000 new hires. 20,000. 20,000 across 312 different organizations. So this isn't some small quirky start-up survey. This is a comprehensive cross-industry look at hiring and retention. Okay, 20,000 hires. So they had line-finding. It was about warning signs, right? So the researchers went back and interviewed the hiring managers after the fact, after these new hires had been on the job for a while. And they found that in 82% of cases, the hiring managers admitted they saw warning signs during the interview process. 82%. That seems impossibly higher. Are you serious? 82%. So let me just get this straight. Four out of five managers are sitting in an interview. They see something that makes their gut, you know, arrogance. They talk about their last boss, some kind of rigid, absolute statement. And they just, what they just ignored it. They ignored it. Or more commonly, they rationalized it. They told themselves a story. What kind of story? Well, their technical resume is perfect. Or I'm just so desperate to fill this seed. I can't afford to be picky or the absolute classic. Oh, no, don't say it. I can fix them. The I can fix them, syndrome. It's not just for dating, apparently. It is definitely not just for dating. And the result, the consequence of ignoring those red flags within 18 months, 46% of those new hires failed. Nearly half gone within a year and a half yearly half fired quit or they got a performance review so bad it was clear they were on the way out. That is just a staggering level of inefficiency. I mean, if a factory had a 46% failure rate on its production line, it would be shut down by regulators. It's an environmental disaster. Absolutely. But in human capital, we just accept it as the cost of doing business. But here is the real kicker. The uncomfortable truth, very deep in that leadership IQ data. When those 46% of hires failed, why did they fail? Well, the default assumption is always confidence, isn't it? They couldn't actually do the job. They lied about their excel skills or they couldn't code in Python or they were just bad at sales, the technical part. That is the universal assumption. But the data says the complete opposite. The study found that 89% of those failures had nothing to do with technical skill. 89. 8. The failures were overwhelmingly attitudinal. They were about the so-called soft traits coachability, emotional intelligence, motivation, temperament. Only 11% of new higher failures were because they lacked the technical chops. This is okay. This is actually wildly disorienting if you think about how we structure the entire hiring process. Go on. Think about a standard interview loop. You spend 45 minutes on a technical case study. You spend an hour, maybe two, on a live coding test. You pour over their portfolio. We spend probably 90% of our vetting energy trying to answer one question. Can they do the task? Correct. That the focus. And you're telling me that the very thing we are spending 90% of our time testing that technical competence only accounts for 11% of the actual risk of failure. Precisely. We are optimizing for the wrong variable. It's like putting a state-of-the-art security system on your garden shed while leaving the front door of your house wide open. We're filtering for the 11% risk and just waving the 89% risk right on through. So the whole premise is flawed. We assume delegation is about finding someone with the right resume. Oh, they worked at Google for five years. They must be good. But the data suggests that delegation fails because we're handing critical tasks to people who, regardless of their beautiful resume, lack the the attitudinal architecture to handle the ambiguity and pressure of being delegated to you. Attitudinal architecture. I like that phrase. But it's also terrifying because attitude feels so subjective. How do you even measure that in an interview? That is the core problem, isn't it? And that's exactly why managers ignore the red flags. A technical skill is easy to measure. It's binary. Here is a test. You pass or you failed. A bad attitude. That's a feeling. It's a vibe. And in a dated driven world, we don't trust our feelings. So we default to the resume. We hire the paper. Okay, so the standard approach is clearly broken, which is usually the point in these deep dives where you bring in the academic cavalry. You show us the peer-reviewed frameworks that solve the problem. I wish you were that simple this time. I really do. When we look for advice on how to fix this, how to delegate effectively given this huge attitude gap, we run headfirst into what I call the evidence void. The evidence void. That sounds ominous. It is. The uncomfortable reality is that most of the popular delegation frameworks you see out there, the ones that get all the press, are what actual researchers call extraordinarily thin on evidence. Wait, hold on. What are we talking about here? Like the 70% rule. If someone can do it 70% as well as you, you should delegate it. That is gospel. I've seen that in a hundred leadership blog posts. It is. It's a fantastically catchy heuristic. But if you try to find the randomized controlled trials proving that 70% is the magic number that it's better than 60% or 80% or any study proving that following this rule leads to better profit margins, they just don't exist. So it's just made up. It's not fake. Exactly. But it's not science. The Center for Evidence-Based Management has a hierarchy of evidence quality. And this kind of advice at the very bottom. They call it consultant folklore. Ouch. Consultant folklore. That stings a little. It's basically the business equivalent of an old wives tale. It's, I'm a famous CEO. This is what worked for me. Therefore, it is a universal law of physics. And that's not how science works. So that is our mission for this deep dive then. We are going to try to move from folklore to physics, or as close to physics as we can get in the messy world of social science. Exactly. And we're going to tackle this on three levels. Lay it out first. Part one is the foundation. We're going to dig much deeper into that leadership IQ study. And we're going to identify the specific trait that does predict success. It's a hit and metric called learning agility. Learning agility. Okay. I'm intrigued. Part two is the evidence. This is where we put the folklore on trial. We're going to look at the founder mode versus manager mode debate that is absolutely tearing up Silicon Valley right now. And we're going to cover a critical finding out called the cross cultural reversal, which is essentially why your standard Western delegation advice might actually be toxic in other parts of the world. Toxic. That is a very strong word. The data supports it as we'll see. And then finally, part three, application. We're not just going to deconstruct. We're going to rebuild five specific research-backed protocols. You can implement it immediately so you can stop guessing and start actually delegating with some scientific confidence. I'm ready. Let's start at the beginning. Part one, the foundation. You mentioned that 89% of failures are attitudinal. Can you break that down for me? Attitude is a pretty big bucket. What specific things are breaking these teams? Right. So leadership IQ didn't just stop at attitude. They categorized the specific reasons for failure. And the number one culprit, accounting for 26% of all failures, was coachability. Coachability. The ability to take feedback. Or the inability in this case. The inability to admit mistakes, the reflexive defensiveness when someone points out a flaw. The complete inability to adapt behaviors even when you're explicitly asked to. It's interesting because coachability sounds like a junior level trait. You know, I need to coach my new intern. But this study looked at all levels of seniority, didn't it? Yes, all levels. And you could argue that uncouchability is exponentially more dangerous at senior levels. If an intern is uncouchable, you have a small problem. If a vice president cannot take feedback, they can crash an entire division. Their plast radius is huge. That's a great point. So 26% is coachability. What's next on the list of failures? Next up is emotional intelligence at 23%. So reading the room. Reading the room, understanding your own emotional state, managing relationships without causing friction, all that good stuff, then came motivation at 17% just do they have the drive to succeed and temperament at 15%. And the end, trelling way, way behind at the very bottom of the list was technical skills at only 11%. It really reframes the whole risk profile of delegation, doesn't it? When I hesitate to delegate something, my internal monologue is usually they won't do it right by which I mean the output will be technically flawed. The spreadsheet will have an error. The report will miss a key detail, but this data suggests the real risk isn't they will do it wrong. The real risk is, they will do it wrong, hide the mistake, get defensive when I pointed out, blame someone else, and then either quit in a huff or become a toxic presence on the team. That is exactly the dynamic. You've nailed it. The critical question isn't can they execute the function? The question is what happens when the function fails? Because in any complex work failure is inevitable. The environment changes, the client changes their mind. The data is dirty, something will go wrong. And if the person you delegated to cannot metabolize that failure and learn from it, you haven't really delegated anything. You've just created a future crisis for yourself that will be 10 times harder to solve. Metabolized failure. I love that term. So if technical skill is a red herring or at least just a baseline that doesn't actually predict success, what is the hero metric? You mentioned learning agility. Is that just a fancy buzzword for being smart? For having a high IQ? It really sounds like it doesn't it? Yeah. And that's a common misconception. But it is very distinct. Learning agility is formally defined in the research literature as quote, the capacity to extract generalizable lessons from diverse experiences and apply them to novel unfamiliar challenges. Okay, let's unpack that definition. Extract generalizable lessons. Right. It's not just about having an experience. Two people can go through the exact same failed project. Person A comes out of it and says, well, that was a disaster. My boss was an idiot and the client was unreasonable. They've learned absolutely nothing. They're blaming external factors. Completely. Person B goes through the same failure and says, okay, I see what happened. I realize that when we don't set a crystal clear agenda in the kickoff meeting, the project scope inevitably creeps. Next time, I'm going to enforce a strict agenda and get sign off before we start. Person B extracted a generalizable lesson, a rule they can use in the future. Exactly. And the crucial part is they can then apply that lesson in a totally different context. A sales call, a marketing campaign, whatever. That is learning agility. And the data on its predictive power is just incredibly robust. A major meta analysis by demuse and colleagues. And just to remind everyone, meta analysis is the gold standard of research as a study of other studies. They looked at 20 different field studies. Okay. They found that learning agility has a correlation, which in statistics is represented by renew of .74 with leader performance. 0.74 for the non statisticians listening, you have to calibrate that for us. Is that big? It's enormous. In social science, a correlation of .3 is considered meaningful. A correlation of .5 is considered very strong. For context, the correlation between a person's height and their weight in the general population is about .5. Wait, you're kidding me. So learning agility predicts leadership success better than a person's height predicts their weight. Significantly better. It is one of the single strongest predictors we have in the entire field of organizational psychology. It's almost a cheat code. If you have high learning agility, you are almost destined to be a high performer in a complex changing environment. Here's my skepticism again. You say learning agility. I still hear high IQ. Isn't this just a fancy way of saying smart people are good at figuring things out? You would think so. It's the most intuitive conclusion right. And I think that's the trap that most hiring managers fall into. They look at a resume and see a high GPA from top university. They see high SAT scores. And I think this person's genius, of course, they'll figure it out. Right. It's a proxy for intelligence. It's treated as one. But the data completely contradicts this across a massive sample of over 60,000 participants. The correlation between learning agility and IQ is 0.09. 0.09. That's basically zero. That's statistical noise is virtually nonexistent. There is no meaningful relationship. You can have an IQ of 160, a certifiable genius, and have absolutely zero learning agility. How is that even possible? It feels counterintuitive. Think about the archetype of the smartest guy in the room. We've all met this person. He processes information incredibly fast. He solves logic puzzles in his sleep. But what happens when he's wrong? What happens when reality contradicts his theory? He argues he rationalizes. He doubles down. He constructs a brilliant, eloquent, complex argument for why reality is wrong. And he is right. His high IQ actually becomes a defense mechanism against learning. He has never had to struggle to understand things. So he's never developed the muscle of humility or his systematic process for learning from failure. That makes so much sense. And actually now that you mentioned it, I've seen this play out. The people who just coasted through school on raw intelligence often hit a brick wall in the real world. The very first moment, the answer isn't in the back of the textbook. Exactly. The real world is messy and ambiguous. And in fact, the data goes even further. One specific dimension of learning agility that developing leadership dimension actually has a negative correlation with cognitive ability. It's negative point two to a negative correlation. So being smarter can actually make you worse at this. In some cases, yes. The leading theory is that people with lower raw cognitive processing power often have to compensate. They can't just rely on their brain. So they develop better systems. They seek more help. They ask for feedback constantly. They build checklists to check their own work. They rely on others. And that entire pattern of behavior seeking help checking assumptions is what builds learning agility. While the genius just trusts their own brain, which works 99% of the time until it catastrophically doesn't. This completely flips the script on hiring then. We're always told to hunt for the 10x engineer, the rock star genius. But maybe we should be hunting for the, I don't know, the scrappy system builder. We should be hunting for the person with the best process for improvement, not the person with the highest current database of knowledge. Because knowledge becomes obsolete in about five minutes. The process of learning does not. Okay, so we have a new target metric learning agility. But we still have this evidence void you mentioned. This problem of figuring out how to manage these people. You brought up the term indigenity earlier. And I'll be honest, my eyes glazed over a little bit. Why does that matter to a regular manager trying to delegate a task? It matters because it explains why so much popular business advice is complete garbage. Indigenity, and let's say it's slowly endogeneity IT, is a statistical problem where you can't tell the direction of causality. You see two things happening together, but you don't know if A is causing B or if B is causing A or if some other things C is causing both. Give me a real world example of that. Okay, think about the halo effect in business. We look at a wildly successful company. Let's say Google in its heyday. We observe that Google has free gourmet food, nap pods, and they delegate heavily to their engineers, giving them huge autonomy. Right. And those things become legendary. They do. So the business press concludes delegating heavily and offering perks causes success. But maybe just maybe Google only delegates that heavily because they are so incredibly profitable that they can afford to hire the top 0.1% of talent in the world. Maybe the immense success caused the unique culture of delegation, not the other way around. I see. So if a struggling startup with no money tried to copy Google's delegation style, they might just go bankrupt faster because they don't have the same caliber of people. Exactly. You're confusing correlation with causation. A major review by a researcher named Antonakis and his colleagues looked at the entire field of leadership studies and found that somewhere between 66% and 90% of them failed to properly address this problem of endogeneity up to 90%. That is a stunning indictment of the entire field. It is. It means most of what we read is just storytelling. We retroactively attribute success to a leader style. If the company stock goes up, we look at the CEO and say, she's a visionary delegator, a genius. If the stock goes down the next year, we look at the exact same behaviors and say she was disconnected, a move, and didn't have her hands on the wheel. The behavior didn't change just the outcome did. And we rewrote the narrative to fit the outcome. This reminds me of the classic business book Good to Great. I feel like for a decade, that book was on every executive shelf. It was the business Bible. And it's a perfect example of this problem. Jim Collins identified 11 great companies based on their stock performance and then worked backward to identify common leadership traits, including how they delegated. But what happened to those companies? Well, Phil Rosenzweig pointed this out in his book The Halo Effect. By 2012, just over a decade after publication, six of those 11 great companies had underperformed the S&P 500. Circuit City went bankrupt. Fannie Mae needed a massive government bailout. These companies weren't great because of timeless principles. They were just successful at that particular moment in time. And we assigned greatness to them after the fact. So the big takeaway here is that we need to be incredibly skeptical. Just because a famous CEO does something and is successful, that doesn't mean the thing they did is what made them successful. Exactly. We need to practice what some people call epistemic humility. Treat all this advice as a directional signal, a possibility, not as a law of physics. Speaking of directional signals, let's move into part two, the evidence. Let's put some of this folklore on trial. And I want to start by picking a fight with you. I had a feeling you would. I want to fight you on the 70% rule. Laf is bringing on. If someone can do it 70% as well as you, let it go. I use this. This is the rule that stops me from being a suffocating perfectionist. It's my personal mantra to stop micromanaging. Why do you want to take this away for me? I don't want to take it away from you at all. I just want you to understand why it works. And it's not for the reason most people think. It's not because 70% is some magic mathematical threshold discovered in a lab. It's not like it's 69% the project explodes and at 70% it's a roaring success. Precisely. It works because it functions as what's called a satisfying heuristic. Satisficing. That's a mashup word, right? It is. It's a portmanteau of satisfy and suffice, coined by the Nobel laureate Herbert Simon. In decision theory, it's the opposite of maximizing. Maximizing means finding the absolute 100% perfect solution. Satisficing means aiming for good enough. And humans, or at least perfectionist managers, are naturally maximizers. We are. But maximizing is incredibly expensive. It takes a huge amount of time, energy, and stress to get from 95% perfect to 100% perfect. The 70% rule is just a mental trick to force our maximizing brains into satisfying mode. It breaks the paralysis of perfectionism. Exactly. But there is a real psychological mechanism underneath it that is backed by evidence. Research on psychological empowerment shows that when you delegate tasks, where someone has good enough components, which 70% is a decent proxy for, it triggers a powerful positive feedback loop. How does that work? The employee feels trusted. My boss trust me with this important thing, even though I'm not perfect at it yet. That sense of trust boosts their internal motivation. Because they're motivated, they start to seek more feedback. The data shows a beta coefficient of 0.31 for feedback seeking behavior, which is a solid link. And because they're actively seeking feedback, they improve much faster. So by accepting a 70% quality level today, you are actually building the path to get them to 90% tomorrow. Correct. If you wait until they are at 90% before you delegate, you will never delegate. And they will never get the reps they need to learn. So biomains keep using the rule. Just know that it's a psychological trigger for you and them, not a law of nature. Okay, I can live with that. A calibrated understanding. Now, let's move to what you called the main event, the founder mode versus manager mode debate. This has been the dominant conversation in tech for the last couple of years. It really has. And the entire conversation orbits around one person, Brian Chesky, the CEO of Airbnb. Right. So set the scene for us. What happened? It's early 2020. COVID hits global travel evaporates overnight. Airbnb's revenue drops 80% in eight weeks. 80% that is an extinction level event for a travel company. It is now standard manager mode advice. The stuff they teach you at Harvard Business School says in a crisis, you trust your leaders. You delegate authority to the divisions. You stay at the 30,000 foot strategic level. Don't get in the weeds. Right. You're the CEO. Your job isn't to be reviewing button colors on the website. Chesky looked at that standard advice and did the exact opposite. He came to the conclusion that if he delegated to the existing divisions, they would all move too slowly and they'd just try to protect their own turf. The company would die by a thousand committee meetings. So he went full founder mode. And what did that actually look like in practice? He blew up the existing structure. He dismantled the divisions. He fired a layer of middle managers. And then he took on something like 40 to 60 direct reports. 40 to 60. The standard span of control and management theory is supposed to be what seven people five to seven is the textbook number. Yeah. He went 10 times that he effectively became the chief product officer for the entire company. He was in every meeting. He reviewed every single pixel on the website. He personally rewrote marketing copy. That sounds like an absolute micro management nightmare for everyone involved. It does. Sounds like it should have been a complete disaster. But let's just look at the scoreboard by Q3 of 2025. Airbnb was reporting $4.1 billion in revenue. They had a 50% EBITDA margin and they had shipped over 430 product upgrades in just two years. They emerged from the crisis leaner, faster and more profitable than ever before. So what's the lesson? Delegation is a lie. We should all just be obsessive micromanagers like Chesky. And this is the danger of this simple narrative, right? We see the one shining example of Chesky and we say see founder mode is the answer. Micro management works. But this is where we have to be so careful about survivorship bias. We see Chesky because he's the one who survived. We see Chesky. We see Steve Jobs. We don't see the thousands of other founders who tried to manage 60 people created a massive bottleneck where every single decision had to go through them drove all their best talent away and crashed the company into the ground. This is the central idea of the founders dilemma, isn't it? Exactly. The researcher, known Wasserman at USC, has incredible data on this. He studied thousands of startups and he found that on average, founders who cede control, who fire themselves from the CEO job, switch to manager mode and bring in professional leadership and up building companies that are worth 80% to 100% more. Whoa. So statistically speaking, letting go literally makes you richer. Yes. Wasserman calls it the rich versus king trade off. You can be king control every little decision, stay in founder mode or you can be rich, build much bigger company by embracing manager mode and giving up some control. Most founders choose king and end up with a smaller kingdom. So how do we square the circle? How do we reconcile the Wasserman data with the Chesky story? Was Chesky just a lucky outlier? No, I don't think he was just lucky. I think the synthesis, the real lesson here is that the right mode depends on the life cycle of the company or the project. Chesky was in an existential crisis, a crisis demands founder mode. You need speed, you need decisive disk, you need a singular unified vision. You cannot have a committee meeting when the building is on fire. You need one person to yell, everybody out this door now. But when the fire is out, when the fire is out and you move from survival to scaling, that same founder mode often becomes a liability. The thing that saved you becomes the thing that chokes you. The CEO becomes the bottleneck. So delegation isn't an identity. It's not I am a delegator or I am a micromanager. It's a gear shift. It is exactly a gear shift and the skill is knowing which gear the situation demands. Are you in crisis innovation mode? You might need to downshift into founder mode. Are you in stability scaling mode? You need to upshift into manager mode. Chesky proved that founder mode is a powerful tool, but it shouldn't be the permanent state for most leaders. That is a crucial crucial distinction. Okay, now I want to get to the part you flagged is potentially toxic. The cross-cultural reversal. Right, this is I think the biggest blind spot for most American and Western European managers. And to understand it, we need to talk about the weird problem in psychology. W-E-I-R-D. What does that stand for? It stands for Western, educated, industrialized, rich and democratic. It's an acronym for the type of person who is usually the subject of psychology studies. Okay, so us. And most of our listeners probably. This demographic represents about 12% of the world's population. 12%. But it represents about 96% of the samples in published psychology studies. 96%. So you're telling me that basically everything we think we know about human psychology is actually just the psychology of an American university undergraduate. For the most part, yes. And this massively distorts our view of things like motivation and delegation. The standard Western dogma, the thing we hold to be a universal truth is that empowerment is good. Autonomy is good. We say, don't tell me how to do it. Just tell me what to do and get out of my way. We crave autonomy. Absolutely. If my Bach told me exactly how to structure and write every single sentence of the script, I'd be incredibly annoyed. I'd feel micromanaged. Because you are culturally speaking, weird. But when researchers actually tested this assumption globally, the results completely flipped on their head. There was a fascinating study by Robert and colleagues and another one by Elon and O. They looked at how teams responded to delegation and empowerment in the US, Mexico, Poland and India. And what do they find? In the US, more empowerment led to higher satisfaction and better performance, totally predictable. But in India, empowerment was associated with negative satisfaction and lower performance. Negative. They actively disliked being empowered. That feels so alien. It's not that they dislike empowerment itself. It's at a violates a deeper cultural norm. The key variable here is a concept called power distance. Power distance. Define that for us. Power distance is a cultural dimension that measures the extent to which the less powerful members of the society accept and expect that power is distributed unequally. In high power distance cultures, the boss is the expert. The boss has the answers. There's a clear hierarchy and that hierarchy provides safety and clarity. Okay, I think I'm starting to get it. So if you're in a Western low power distance culture and your boss says here's a tough problem you figure out the solution, that feels like trust and respect. But if you're in a high power distance culture, that same action can feel like incompetence or worse abandonment. The internal monologue is why are you asking me? You're the boss. You're the one getting paid the big bucks to know the answer. Are you not qualified for your job? Exactly. Or it feels like you are throwing me into the deep end of the pool without a life fest and walking away. Uh, in that Elon and O experiment, the participants from high power distance cultures actually performed significantly better when they were disempowered, when they were given very clear, explicit step-by-step instructions. That is just wild. So if I'm a manager in Silicon Valley and I'm managing a remote team and say, Bangalore or Warsaw, and I use my standard empowerment and autonomy playbook, I might actually be hurting their performance and stressing them out. You might be doing exactly that. You think you're giving them a gift, the gift of autonomy, but they're experiencing it as the burden of ambiguity. You're forcing them to operate in a cultural framework that doesn't feel natural or safe to them. This connects directly to that anti-autonomy experiment you found, right? The one in the Norwegian retail chain. Yes, the study by Gidram and Reg. And what's so interesting is that Norway is generally a very low power distance egalitarian culture. But this study was in a specific context, a retail chain. Oh, and the management decided to run an experiment where they reduced employee autonomy. They took it away. They mandated strict, detailed scripts for how sales people should interact with customers. No more just be yourself or feel it out. That was the result. Sales increased by 5.6%. The number of transactions rose by 4.7%. Performance went up when autonomy went down. Why would that be? I thought everyone, especially customers, hated scripts. Customers might hate bad robotic scripts. But for the employees, the script did something very important. It reduced their cognitive load. If I don't have to burn mental energy deciding how to greet the customer or what the five key features of this product are or how to ask for the sale, I can free up all of that mental bandwidth to actually listen to the customer and respond to their specific needs. So autonomy isn't always a gift. Sometimes structures the gift, sometimes a clear plan is the kindest thing you can give someone. Exactly. And a recent paper from 2024 by Blundin and Stuffel found this exact thing. They discovered that employees often perceive delegated decisions not as an opportunity, but as a burden. It's the pleas of the Lord of God, don't make me decide where the team orders lunch from problem. Lapse, I feel that in my soul, the tyranny of choice. Now multiply that by a thousand high stakes corporate decisions. Sometimes the kindest most effective and most empowering thing a leader can do is not delegate. It's to provide clarity and structure. Okay, my head is spinning a bit. We have dismantled a lot of myths here. We've established that technical skills are a poor predictor of success that a lot of our standard advice is culturally biased and that even micro management has its place. So now, let's put it all back together. Part three, application. The five protocols, let's make this actionable. Let's start with protocol one. We know we need to hire for learning agility. So I'm a manager. I'm sitting across the table from a candidate. What do I actually ask them to figure this out? The big shift you need to make is to stop prioritizing questions about what have you done and start prioritizing questions about how do you learn? You need to find a way to verify that failure metabolism we talked about earlier. Okay, give me this script. What's the first question? Question one, tell me about a time you had to learn something completely new for a job, something you were totally unqualified for. Walk me through your process step by step. And what's a bad answer to that? Bad answer is vague. Oh, I'm a quick learner. I just, you know, googled it and figured it out. That tells you nothing. It shows they have no conscious system for learning. So what does a great answer sound like? A great answer is a system. Well, first thing I did was realize I was completely ignorant about X. So I broke the problem down into his three main component parts. Then I identified the top three experts on this topic inside the company. And I scheduled 30 minutes with each of them to interview them. From that, I built a small prototype which failed. I took that failure back to one of my experts, got their feedback, and then I iterated. You're not looking for the answer. You're looking for the algorithm they use to find the answer. Precisely. You want to see that they have a toolkit for dealing with the unknown because all important work is dealing with the unknown. Okay. What's question two? What is the harshest, most critical piece of professional feedback you've ever received? And what specifically did you do as a result of it? I like the word harshest. It forces them to go to a place of vulnerability. No fluff. It does. And what you're listening for here is the locus of control ownership versus defensiveness. A red flag answer is, well, I once had this boss who was a total micromanager and he just hated my creative style. That's externalizing. They're blaming the boss. So a good answer takes ownership even if the feedback was delivered poorly. Exactly. A learning agile person will say something like, my boss delivered the feedback in a really harsh way. But the kernel of truth in it was that I wasn't communicating my progress clearly enough. So as a direct result, I started sending a daily three bullet point summary email and our relationship completely turned around. Don't worship an action. Ownership an action. But the real secret weapon of Protocol One, the thing that almost nobody does is the real time test. And how do you do that without making the interview incredibly awkward? You give the candidate direct critical feedback during the interview itself. That feels confrontational. It's necessarily diagnostic. Let's say they're presenting a case study they prepared. You listen patiently. And then you say, that's a really interesting approach. Thank you for walking me through it. But I think there's a potential flaw in slide two. You overlook the regulatory risk. If the laws in this industry change, wouldn't this entire strategy fall apart? And then you just you watch their face. You watch their autonomic nervous system kick into gear. Do they get flutch? Does their posture stiff? And do they immediately interrupt you to argue and defend their original point? That's a huge red flag. We're into they get curious. Exactly. Does their posture lean forward? Do they say, oh, that is a fantastic point? I hadn't considered the regulatory angle at all. Let me think for a second. Okay, if that happened, I suppose we would need to pivot to. If they can process feedback and adapt their thinking in the high stress environment of an interview, they can definitely do it on the job. Because if they get defensive when they're actively trying to impress you, they will be an absolute nightmare to manage once they're comfortable guaranteed. Remember, 26% of all failures are due to coachability. You can test for that in 30 seconds with one challenging question. I love that. So powerful. Okay, protocol two. You call it the calibrated 70% heuristic. How do we use this rule of thumb without falling for the consultant folklore? We use it as a trigger to force action, but we calibrate the percentage based on the reversibility of the decision. Reversibility. Whether you can undo it or not. This is a concept Jeff Bezos talks about a lot. Type one decisions are irreversible, like walking through a one-way door. Type two decisions are reversible, like walking through a normal door. You can always walk back out. So how does that apply to the 70% rule? If a task is low stakes and easily reversible things like drafting an internal blog post, doing some initial research, creating a social media post, you should actually delegate at 50% competence. 50%. That's basically guaranteeing they have no idea what they're doing. It is. You are delegating for the purpose of learning, not for the purpose of a perfect outcome. They will probably fail. But because the task is reversible, the cost of that failure is very low. You can just delete the poster, throw away the draft. But the learning value for the employee is immense. This is how you build learning agility. You create safe-to-fail environments. But if it's a high stakes, irreversible type one decision. If it's irreversible, like sending a major contract to a new client or deploying new code, your production servers, you wait for 90% or even 95% competence. Precision matters more than learning in that moment. So 70% is just the average. You slide the number up or down the scale based on the risk. Correct. And you pair this with what I call a graduated autonomy timeline. You have to think of delegation not as a binary light switch on or off, but as a dimmer switch that you slowly turn up over time. Give me the phases of that timeline. Okay, for any new complex task, weeks one and two are supervised. I watch you do it or we do it together. Weeks three and four are checkpoint based. Show me the outline before you write the full report. Weeks five through eight are periodic review. Let's check in once a week. And only after all that do you finally move to exception based delegation. Which is don't talk to me unless the building is on fire. Exactly. This solves the boomerang delegation problem where you hand something off. They mess it up because you didn't support them and you end up having to take it back and do it all yourself at midnight. You didn't delegate. You abdicated. You just threw it over the wall. The dimmer switch prevents abdication. I like that protocol three the OPPY framework. You say this is for transferring tacit knowledge. Right explicit knowledge is the easy stuff. Click this button in the software. You can write that in a manual. Tacit knowledge is the hard stuff. It's judgment. It's intuition. It's why does this particular client need a gentle reassuring tone in an email. While this other client needs you to be blunt into the point. You can't write that in a user manual. So how on earth you transfer it. We steal a model from medical residences and the Toyota production system. The framework is called OPPY. It's an acronym for observation, practice, partnering, taking responsibility and you're on your own. Okay walk us through that cycle. It's typically a nine to 12 week cycle. The first phase is observation. For a week or two the delegate is just your shadow. They don't touch the keyboard. They just sit in on your meetings and calls and their only job is to ask why did you do that or what were you thinking when you said this. This builds their mental model of the work. Then practice. They try the task for the first time but you are hovering. Supervision is at 100%. You're right there to catch any mistakes in real time. Partnering. This sounds like the key shift. It is. Now you work as peers on the task. You split the presentation. You tag team a difficult client call. They get to see you handle a curve ball in real time and learn from your example. Then taking responsibility. Now the rules flip. They lead the project or the call. You are the shadow. You're there as a safety net but you don't intervene unless it's a true emergency. And finally you're on your own. The training wheels come off. The net is gone and you've successfully transferred not just the what but the how on the why. It sounds incredibly thorough but it also sounds slow 12 weeks is a long time. It is slow. Yeah. But if the Navy seals are fond of saying slow is smooth and smooth is fast. If you rush the transfer of tacit knowledge. If you skip these steps, you will spend the next two years fixing their subtle invisible mistakes. This is an investment that pays off 10 fold. Protocol four. Cultural adaptation. What's the immediate actionable move for a manager with a global team? First do 10 minutes of homework. Look up the power distance index for your team's primary location. You can use the data from Geert Hofstede or the G-Lo project. It's all free and available online. And once I know if they are from a high power distance culture. What do I do differently? You need to be more directive. Provide clear templates and examples. Define what a successful outcome looks like with explicit criteria. And crucially, do not ask broad open ended questions like, so what do you guys think we should do? Until you have built a tremendous amount of psychological safety on the team. To them, that question can sound like you have no idea what you're doing. And if they're from a low power distance culture like the US or Scandinavia. Then you do the opposite. You should be more participative. Ask for their input early and often. Focus on the what's the outcome and give them total freedom on the how. But the best move you say is the golden question. Yes. Because culture is a generalization. The individual in front of you might be an exception. So just ask them. For this next project, would it be more helpful if I gave you a detailed set of directions and a clear template to follow? Or would you prefer if I just gave you the end goal and you develop your own approach? It completely removes the guessing game. It does. It forces them to articulate their own needs. And it shows that you respect them enough to adapt your style to them. It's the ultimate act of managerial respect. Love that. Okay. Finally, protocol five, selective founder road. This is the protocol that resolves that tension between the Brian Chesky story and the no-mosserman data. The answer isn't that you have to be purely a manager or purely a founder. The answer is that you have to split the domain of your work. So what do we hold on to? What do we keep in our founder mode box? You kept the soul of the enterprise, the core vision, the definition of the product, what it is and who it's for, the cultural values of the team, and critically, the hiring standards for key roles. Chesky kept control of the product and the hiring bar. He delegated almost everything else. And you delegate the body. Exactly. You delegate the operations, the execution, the logistics, all the areas where technical experts are genuinely better and more qualified than you are. And you mentioned the supplies to delegating to AI as well. It's a perfect parallel. The vast majority of organizations are treating gender to AI as a manager mode delegation. They're just throwing tasks over the wall. Here, JetGPT, Remyah Marketing Plan, and the results are generic and often fail because the AI lacks the deep tacit context. So what do high performers do? High performers use founder mode with their AI tools. They get in the weeds, they craft detailed prompts, they iterate on the output 20 times, they treat the AI not as a magic black box, but as a very smart, very fast but very inexperienced junior partner that they need to train and coach using a framework like OPPTY. That is a profound shift in mindset. We're treating AI like a magic wand. We can just waste, but we should be treating it like a new intern. We need to personally coach and mentor. That is the only way to get breakthrough results. We have covered a massive amount of ground here today. From the attitude gap to the power of learning agility, we debunked the 70% rule and we found a way to resolve the founder mode debate. If you had to boil all this down to just three key takeaways for the leader who's listening right now, what are they? Take away one is simple. Who what? Delegation success is 89% about the person you delegate to. Specifically, they're learning agility and attitude and only 11% about the task itself or their existing technical skills. Hire the metabolism, not to the resume. Take away two. Tools, not rules. Frameworks like the 70% rule or the RICI matrix are useful thinking tools. They are heuristics to trigger action and overcome your own biases, but they are not scientific laws. Use them as a starting point for your judgment, but don't worship them as gospel. And take away three. Context is king. There is no universal best way to delegate. Your style must be a chameleon. It has to adapt to the culture of your team, their power distance, the stakes of the task, this reversibility, and the life cycle of your project, crisis versus stability. I just keep coming back to that opening statistic. 82% of managers, they saw the warning signs. They saw the arrogance in the interview. They saw the defensiveness and they ignored their own gut feeling probably because they were afraid to hold a line on some subjective vibe. They were afraid. They thought filling the empty seat on the org chart was more important than protecting the standard of the team. And 46% of the time that decision blew up in their face. It did. And that brings us right back to the final central thought of this whole deep dive. We always talk about delegation as the art of letting go. But I think the science suggests something quite different. What's that? The science of letting go is less about letting go and more about knowing what to hold on to the vision, hold on to the cultural standards, hold on to the hiring process for learning a disability. And then you can let go of the rest with confidence. That is the algorithm. That is the algorithm. Thank you for this. My brain is officially full, but in the best possible way. This has been incredibly clarifying. It's always a pleasure. For everyone listening, you can find the full research, all the citations, the leadership IQ study, the Wasserman data, and detailed write-ups of the five protocols at research.uda.me. That's yud.me. It's all there in the show notes. This has been Algorithms for Life, produced by Valor Ingalls. I'm your host. I'm your expert. Go forth and delegate responsibly. We'll see you next time.