The Innovators Studio with Phil McKinney

Every public company's R&D number is a lie hiding in plain sight. Not because anyone falsified it. Because the number was never built to tell the truth. It was built to satisfy an accounting standard written in 1974. And for fifty years, boards, analysts, and CEOs have been making billion-dollar innovation decisions based on a number designed by accountants to solve a different problem entirely. Here's what makes this genuinely strange. The real number exists. The government has been collecting it from every major US company for decades. It would answer the question every innovation leader and investor actually needs answered. And it is locked away by federal law. Confidential. Never published. Never seen by the people who need it most. It's sitting in a federal database right now. And there's a way to estimate it for any public company, without asking anyone's permission. I know it exists because I spent years building it from the inside. Why the R&D Signal Was Blurry When I was running innovation at HP, we discovered this problem firsthand. We had a connection between R&D investment and gross margin that held up across decades of HP history. Better than anything Wall Street was using. But the signal was blurry. None of us could figure out why. The answer came from a question someone on the team asked almost as an aside. What if R&D isn't one thing? Research and Development Are Not the Same Thing Think about what actually lives inside a typical R&D budget. There's a team somewhere investigating whether a new approach could enable a capability that doesn't exist yet. No product defined. No spec written. Asking whether something is even possible. And there's a team building the next version of a product that ships in eighteen months. Spec locked. Timeline set. Engineering executing against a defined target. Both show up on the same line in the budget. Both get called R&D. Both count equally toward the number that gets reviewed every quarter. They are not the same thing. One is Research. The other is Development. Research is the work you do when you don't yet know what you're building. The output is understanding. New knowledge that might enable future products nobody has designed yet. You can't know exactly what you'll find. If you already knew, it wouldn't be research. Development is the work you do when you know exactly what you're building. The spec exists. The product is defined. The question isn't what to make. It's whether it can be made, on time, at cost, at quality. One creates the future. The other delivers the present. And for fifty years, every public company in America has been required to report them as one indistinguishable number. When we split the HP data along that line, Research on one side and Development on the other, the signal sharpened immediately. Research spend, measured against gross margin three to five years later, was a meaningfully stronger predictor than the combined number had ever been. The blur hadn't been in the gross margin data. It had been in the R&D number itself. Two fundamentally different things, averaged together, producing a number that looked precise and predicted almost nothing. But splitting R from D at the company level was only the beginning. The model was still lying to us. Just more quietly. Why Company-Level R&D Splits Still Mislead Even with the split, something was still soft. HP wasn't one business. It was dozens. Printers, PCs, servers, software, each running on different timelines, different technology cycles, different competitive dynamics. What if the R/D split meant something different depending on where it was applied? We pushed it to the product line level. Then further, to the platform level within product lines. Printers were the clearest example. HP's printer business wasn't one story. There were platforms built on established technology. Mature ink systems, proven print head chemistry, products that had been shipping for years. And...

Every public company in the technology industry measures innovation spending the same way. R&D as a percentage of revenue. Why? Because Wall Street tracks it. Boards benchmark it. CEOs get fired over it. And it tells you almost nothing about whether the spending is working. Bill Hewlett and Dave Packard knew that. From the very beginning, they measured something different. Something the rest of the industry has been ignoring for seventy years. And the proof was sitting in a paper that Chuck House pulled out and sent to me after a conversation at a Computer History Museum board meeting. By the end of this episode, you'll know what that metric is, why it works, and why the one everyone else uses makes it nearly impossible to tell whether your innovation investment is building the future or just burning cash. Here's how I found it. The Question That Wouldn't Let Go In the last episode, I talked about the argument with Mark Hurd. The question was over whether HP should cut R&D as a percentage of revenue to match Acer. I knew Mark was fundamentally wrong. But I couldn't prove it. The only metric on the table was R&D as a percentage of revenue. That was what Wall Street expected. It's what shareholders expected. It's what the board expected. But I couldn't argue against it, because I didn't have the data. I needed a better metric. So I decided to go back to the beginning. HP's complete financial records dating back to the 1940s. Division by division. R&D project by R&D project. The actual operating data. I got access to all of it. The HP archive team gave me direct access to Bill and Dave's original notebooks. Now, data alone wasn't enough. It was mountains and mountains of data, and you're trying to extract the signal. What is the trigger in that data? The conversation that cracked it open happened outside HP. The Man with the Medal of Defiance I was at a Computer History Museum board meeting, standing next to Chuck House, and I shared with him the struggle I was having. A little context on Chuck. He spent twenty-nine years at HP. He was the Corporate Engineering Director and he helped launch dozens of products. He's also the recipient, from David Packard himself, of the Medal of Defiance. The Medal of Defiance was given to him because David had told him at one point to kill a product line. Chuck went around that decision, put the product into the catalog, shipped it, and it turned into a phenomenal success. When David gave Chuck the medal, the citation was something along the lines of: "for going above and beyond the stupidity of management and doing what was right." Chuck and Raymond Price co-authored a book called The HP Phenomenon, published by Stanford Press. It's the deep dive into the history of the innovation culture inside HP, all of the metrics used back in the Bill and Dave days that put in place the structure that allowed HP to be successful. By the time I'm at HP, Chuck had long since moved on. He was running Media X at Stanford, the university's research program on innovation, media, and technology. But we both served on the Computer History Museum board. At that board meeting, I shared the argument I'd had with Mark and the search for a better metric. I had a strong feeling there was something around gross margin. That R&D investment impacted gross margin. But a feeling isn't an argument. I needed data. I needed to correlate R&D spend to margin, and that's extraordinarily hard to do when you've got all these different product lines and divisions. Chuck got this little smile on his face and said, "I need to send you something." The Paper and the Whiteboard What he sent me was a paper. A journal paper he and a few of his colleagues had written decades before. And it laid out the connection between research investment and margin performance. The correlation I suspected but couldn't prove was right there on the page. I read it that night. The next morning I emailed Chuck, and I was just...

Twenty years. Nearly one thousand episodes on this show. And starting today, we're going to try something a little different this season. Season 21 is about the decisions that actually determine whether innovation lives or dies inside any organization. The real calls. Not the fluff stuff we read in academic textbooks. I want to actually put you in the rooms where these decisions are happening. What went right. What went wrong. My objective is to expose you to the patterns in innovation decisions so that you can recognize them. Recognize them in yourself, in the people you need to influence, long before you step into any landmines. So let's get into it. The Encounter on the Top Floor of Building 25 Making generational decisions on innovation investment can be a make-or-break moment. What I refer to as a CLM, a Career Limiting Move. In my case, it started with a chance conversation with Mark Hurd, HP's CEO. Let me take you back to 2005. HP headquarters is on Page Mill Road in Palo Alto, referred to internally as Building 25. The top floor is where all of the executive offices are. That's where Mark's office was. I was up there doing some meetings and got snagged by Mark. Now, Mark had a reputation. He was a big numbers guy. He believed in what he called extreme benchmarking. You tore into your competitors' numbers. You knew your own numbers in and out. Others had warned me about this. He had a famous quote that everybody shared: "Stare at the numbers long enough, and they will eventually confess." Mark believed you could not lead a critical role at HP if you did not know your numbers cold, inside and out. Didn't matter whether it was sales, CTO, a function, or a division. It didn't matter. And Mark tested everyone on the leadership team. Not just the leadership team. He would randomly stop employees and ask them for their numbers based on what group they worked in. It was non-stop. It was constant. To where support staff was literally constantly preparing briefing books for managers, VPs, leaders, just in case they got nabbed by Mark. In my case, I happened to be walking past his office. Mark waved me in. I sat down, and he immediately started drilling me on the CTO numbers. The number he focused on was R&D as a percentage of revenue. The Broken Benchmark: R&D as a Percentage of Revenue Now, if you've been a regular listener of this show, you know my opinion of that metric. R&D as a percentage of revenue is a meaningless number. It is absolutely meaningless. But every public company CEO at an innovation-dependent company, all the tech companies, AI companies, even automotive, they live by this number. It's a number that Wall Street looks at. You have to report it as part of your quarterlies, and from there it's simple math. When Mark grilled me, he was focused specifically on the PC group at HP. HP's number at the time for the PC group was about one and a half percent. R&D as a percentage of the PC group's revenue. Acer, which was a key competitor, was at 0.8%. Less than one percent. Roughly half of HP's number. Apple was at four percent. Mark's question, and he was really pounding on this, was: How do we get our ratios in line with Acer? Basically, he was saying: how do we cut costs so that our R&D expense as a percentage of revenue equals Acer at 0.8%? This is exactly the problem with choosing the wrong metric. Now I'm going to quote somebody who I think was probably one of the most insightful leaders in the business world. Charlie Munger. If you've ever watched any of his talks, he had a really strong opinion on certain metrics. Specifically EBITDA, earnings before interest, taxes, depreciation and amortization. Charlie referred to EBITDA as BS earnings. It was a metric Wall Street swore by, and Munger said it hid more than it revealed. His exact words: "Every time you see the word EBITDA, just substitute the word 'bullshit' earnings." R&D as a percentage of revenue is the same problem in a different...

The best decision-makers aren't better at deciding. They're better at controlling when, where, and how they decide. It took me twenty years to figure that out. Most people spend that time trying harder: more discipline, more willpower, more resolve to think clearly under pressure. It doesn't work. That's when mindjacking wins. Not through force. Through […]

The best decision-makers aren't better at deciding. They're better at controlling when, where, and how they decide. It took me twenty years to figure that out. Most people spend that time trying harder: more discipline, more willpower, more resolve to think clearly under pressure. It doesn't work. That's when mindjacking wins. Not through force. Through the door you left unguarded. The answer isn't trying harder. It's building systems that protect your thinking before the pressure hits. By the end of this episode, you'll have four concrete strategies for doing exactly that, and a one-page system you'll build before we're done. And I have something else to share at the end. Something I've been working toward for twenty years. Let's get into it. Why Willpower Fails and Design Works Ulysses knew his ship would pass the island of the Sirens. He also knew the song was irresistible. Sailors who heard it became incapacitated and drove straight into the rocks. He didn't try to be stronger than it. He had his crew fill their ears with wax and tie him to the mast, with strict orders not to release him, no matter what he said when the music reached him. His calm self setting rules for his compromised self. That's the core of everything in this episode. These are called commitment devices. The decision gets made early, when your thinking is clear, before you're tempted to take the wrong path. Studies tracking self-imposed contracts found that when people added meaningful stakes to their commitments, their follow-through nearly doubled. Not because they became more virtuous, but because they'd taken the choice off the table at the moment they were most likely to get it wrong. Stop asking "How do I resist?" Start asking, "What can I decide now, so I don't have to decide under pressure?" Before you can build the right commitments, you need to know exactly where your thinking breaks down. Not decision-making in general. Yours. Finding Your Personal Vulnerability Think back across the last few months. Where did your thinking most clearly cost you? Some people stall. They keep researching past the point of useful information, using "I need more data" as cover for avoiding a commitment they know they need to make. Others make their worst calls at the end of long days. Saying yes when they mean no, because no requires energy they've already spent. Some get caught by urgency. A deadline appears, the pressure closes off their thinking, and they move fast. Only later do they discover the deadline was manufactured to do exactly that. Others walk into a room with a clear position and walk out agreeing with the loudest voice, unable to explain exactly when they shifted. And some defend decisions past the point where the evidence says stop, because stopping would mean admitting something about themselves they're not ready to face. Identify yours. Write it down before we go further. Your primary vulnerability is a design target, not a character flaw. You can't build around something you haven't named. Four Strategies for Protecting Your Judgment Strategy 1: Control When You Decide Every morning I put on the same thing: a black golf shirt, blue jeans, and cowboy boots. Same brands, same routine, no decisions. My wife tolerates it. I've stopped apologizing for it. It's not a fashion choice. It's a cognitive load choice. Your brain has a finite amount of decision-making capacity each day. Every trivial choice draws from the same reserve you need for the decisions that actually matter. What to wear, what to eat, which route to take. Eliminating those choices doesn't just save time. It protects the mental fuel you'll need later. Decision-making capacity isn't flat across the day. It peaks early, when you're rested and fresh. It degrades, measurably, as conditions erode. The same call made at 8 a.m. and at the end of your seventh consecutive meeting aren't equivalent. Same person, different machine. Pull up your calendar from the last...

Ron Johnson was one of the most successful retail executives in America. He'd made Target hip. He'd built the Apple Store from nothing into a retail phenomenon. So when J.C. Penney hired him as CEO in 2011, expectations were sky-high. Johnson moved fast. He killed the coupons. Eliminated the sales events. Redesigned the stores. When […]

Ron Johnson was one of the most successful retail executives in America. He'd made Target hip. He'd built the Apple Store from nothing into a retail phenomenon. So when J.C. Penney hired him as CEO in 2011, expectations were sky-high. Johnson moved fast. He killed the coupons. Eliminated the sales events. Redesigned the stores. When his team suggested testing the new pricing strategy in a few locations first, Johnson said five words that explain everything that happened next: "We didn't test at Apple." Within seventeen months, sales dropped twenty-five percent. He was fired. And here's the part nobody talks about: Johnson had access to all the data. Every week, the numbers told the same story. Customers were leaving. Revenue was collapsing. The board was getting nervous. He could see it all. He just couldn't act on it. Because changing course would mean he wasn't the visionary who reinvented retail. He wasn't making a business decision anymore. He was protecting who he believed he was. That's the identity trap. And it doesn't just happen to CEOs. What if changing your mind didn't have to feel like losing yourself? Let's get into it. Why Identity Bias Looks Like Your Best Qualities The trap doesn't target bad thinkers. It targets good ones. Think about the entrepreneur who poured three years and her life savings into a startup. The data says it's failing. The metrics are clear. Her advisors are suggesting it's time to pivot or shut down. She has every analytical tool to evaluate this accurately. And she can't do it. She's plenty smart. The problem is that admitting failure would mean she's "a quitter." And she is not a quitter. That's not who she is. Johnson wasn't stupid either. He was brilliant. His identity as the retail visionary just happened to make him blind to the one thing that could save his company: the possibility that what worked at Apple wouldn't work at Penney's. He experienced his blindness as conviction. As leadership. And that's the disguise. Every other thinking error in this series, uncertainty, depletion, time pressure, social pressure, you can feel those happening. You know when you're tired. You know when you're rushed. But identity fusion is invisible from the inside. It disguises itself as your best qualities. The entrepreneur calls it perseverance. Johnson called it vision. The investor who won't sell a losing position? He calls it discipline. Your ego doesn't announce that it's taking over. It puts on a costume that looks exactly like your strengths. And your brain? Your brain is in on it. Why Changing Your Mind Feels Like a Threat When a belief becomes part of your identity, your brain defends it as it would defend your body. Challenge that belief, and your brain responds the same way it would to a physical threat. Not metaphorically. The same neural circuits that protect you from danger activate to protect you from being wrong. That's why arguments about strategy or direction can generate so much heat and so little light. You're not debating a position anymore. You're defending territory. And sometimes you defend it long past the point where the evidence says stop. A project you've poured months into. A strategy you championed. A hire you fought for. The data says cut your losses, but you keep going because walking away would mean all that time, all that effort, all that money was wasted. That's the sunk cost fallacy. And most people think it's about the money or the time. But it's not. Sunk cost is about identity. Think about that manager who spent eighteen months building a new system. The team knows it's not working. She knows it's not working. But scrapping it doesn't just waste eighteen months of budget. It means her judgment failed. It means she led her team down the wrong road for a year and a half. "I've invested too much to quit" sounds like a financial calculation. It's not. It's an identity statement. What she's really saying is: "If I quit, I'm the kind of person who...

When neuroscientists scanned the brains of people going along with a group, they expected to find lying. What they found instead was something far stranger. The group wasn't changing people's answers. It was changing what they actually saw. We'll get to that study in a minute. But first, I want you to remember the last […]

When neuroscientists scanned the brains of people going along with a group, they expected to find lying. What they found instead was something far stranger. The group wasn't changing people's answers. It was changing what they actually saw. We'll get to that study in a minute. But first, I want you to remember the last time you were in a meeting, and you knew something was wrong. The numbers didn't add up. The risk was being underestimated. And someone needed to say it. Then the most senior person in the room spoke first: "I think this is exactly what we need." Heads nodded. Finance agreed. Marketing agreed. The consultant agreed. And by the time it was your turn, you heard yourself saying, "I have some minor concerns, but overall I think it's solid." You're not alone. Research shows that roughly half of employees stay silent at work rather than voice a concern. And among those who stayed quiet, 40% estimated they wasted 2 weeks or more replaying what they didn't say. Two weeks. Mentally rehearsing the point they should have made in a meeting that's already over. That silence isn't a character flaw. It's your neurology working against you. And today I'm going to show you exactly why it happens and how to stop it. It starts with what was happening inside your head during that meeting you just remembered. Why Your Brain Surrenders to the Group Most people know about the Asch conformity experiments from the 1950s. People were asked to match line lengths, and seventy-five percent went along with answers that were obviously wrong. That result gets cited everywhere. But the more important study came fifty years later, and it revealed something the Asch experiment never could. In 2005, neuroscientist Gregory Berns at Emory University put people inside an MRI machine and ran a similar conformity task, this time with three-dimensional shape rotation. Like Asch, he planted actors who gave wrong answers. But unlike Asch, he could watch what was happening inside people's brains while the conformity was occurring. Berns expected the MRI to show activity in the prefrontal cortex, the brain's decision-making center, when people went along with wrong answers. That would mean they were knowingly lying to fit in. Just a social calculation. That's not what the scans showed. People who conformed showed no increased activity in decision-making regions. Instead, the activity showed up in the parts of the brain that handle visual and spatial perception, the occipital and parietal areas. The group wasn't changing people's answers. It was changing what they actually saw. Their brains were rewriting their experience to match the room. And the people who resisted the group? Their scans told a different story. Heightened activity in the amygdala, the brain's threat detection center. The same circuitry that fires when you encounter physical danger lit up when someone disagreed with the group. Berns put it plainly. The fear of social isolation activates the same neural machinery as the fear of genuine threats to survival. When you caved in that meeting, your neurology wasn't malfunctioning. It was doing exactly what it was designed to do. Keep you safe inside the tribe. This is why what I call mindjacking works so well. Algorithms manufacture social proof by showing you what's trending, what your friends liked, and what similar people chose. Your wiring responds the same way it does at the conference table. You're fighting your own threat-detection system every time you try to hold an independent position within a group. You can't turn off the wiring. But you can learn to catch it in the act. And that starts with one critical distinction. The First Skill: Separating Updating from Caving Sometimes the people around you know something you don't. Changing your mind in a group isn't always a surrender. Sometimes it's the smartest move in the room. The real skill is knowing which one just happened. You can test this in real time. When you...

“We need an answer by the end of the day.” Ten words. And the moment you hear them, something shifts inside your chest. Your pulse ticks up. Your focus narrows. Careful thinking stops. The clock starts. You probably haven't even asked the most important question yet. Is that deadline real? Most of the urgency you […]

"We need an answer by the end of the day." Ten words. And the moment you hear them, something shifts inside your chest. Your pulse ticks up. Your focus narrows. Careful thinking stops. The clock starts. You probably haven't even asked the most important question yet. Is that deadline real? Most of the urgency you feel every day is fake. Manufactured by someone who benefits from you deciding fast instead of deciding well. Most people can't tell a real deadline from a manufactured one. By the end of this, you will. Let's get into it. What Time Pressure Actually Does to Your Brain Last episode, we talked about decision fatigue. How your brain degrades over a long day. Time pressure is different. Fatigue is a slow drain. Time pressure is a switch. When the clock is ticking, your brain stops analyzing and starts reacting. Normally, the front of your brain runs the show: careful analysis, weighing trade-offs, long-term thinking. Under time pressure, a faster, older, more emotional region takes over. You don't feel less accurate. You feel more confident. Decades of decision science research have found that under time pressure, people's confidence in their decisions goes up while their actual accuracy goes down. You're not just thinking worse. You're thinking worse while being more sure you're right. That false confidence makes you predictably worse at three specific things. Evaluating trade-offs.You lock onto whichever side your gut grabs first.Considering consequences beyond the immediate.Second-order thinking goes offline.Recognizing what you don't know.Because you feel certain, you stop looking for what you're missing. And that's exactly what manufactured urgency is designed to exploit. This is mindjacking in its purest form. Someone engineers the pressure, your brain switches modes, and you make their decision instead of yours. The Urgency Trap: Real vs. Manufactured Not all time pressure is the same. Some deadlines are real. Your tax filing date is real. The board meeting on Thursday is real. The patient who needs a decision in the next ten minutes? That's real. These deadlines exist because of actual constraints in the world, not because someone manufactured them. A huge portion of the urgency you experience? It's engineered. "This offer expires at midnight." Really? Will the company stop wanting your money tomorrow? "We need your decision today." Why today? What actually changes between today and Wednesday? Manufactured urgency is one of the most effective persuasion tools ever invented. Countdown timers on websites that reset when you refresh the page. "Limited time" sales that somehow run every month. Negotiators who invent deadlines because pressure extracts concessions. Manufactured urgency is everywhere. And it works because of what we just covered. Time pressure flips you into fast-decision mode. When someone engineers urgency, they're not just rushing you. They're changing which part of your mind makes the call. The decisions that actually shape your career almost never show up with a countdown timer. The urgency trap pulls your attention to whatever is loudest, while the ones that matter sit quietly in the background. Until it's too late. Five Tests for Manufactured Urgency How do you tell the difference? I use five tests. Test One: The Source Test. Ask yourself: who benefits from me deciding quickly? If the answer is "the person creating the deadline," that's a red flag. Real deadlines serve the situation. Fake deadlines serve the person imposing them. The car salesperson who says "this price is only good today"? That deadline serves the dealership, not you. The surgeon who says "we need to operate within the hour"? That deadline serves the patient. Test Two: The Consequence Test. Ask: what actually happens if I wait? Not what I'm told will happen. What actually happens. "The offer expires." Does it? What would happen if you called back next week? In most cases, the offer magically reappears....

A nurse in Pennsylvania had been on her feet for twelve hours. She was supposed to go home, but the unit was short-staffed, so she stayed. During that overtime, a patient was diagnosed with cancer and needed two chemotherapy doses. She administered the first, placed the second in a drawer, and headed home. She forgot […]

A nurse in Pennsylvania had been on her feet for twelve hours. She was supposed to go home, but the unit was short-staffed, so she stayed. During that overtime, a patient was diagnosed with cancer and needed two chemotherapy doses. She administered the first, placed the second in a drawer, and headed home. She forgot about the second dose. It wasn't discovered until the next day. The patient was fine; they got the treatment in time. But think about what happened. This wasn't a careless nurse. This was a dedicated professional who stayed late to help her team. Her skills didn't fail. Her knowledge didn't fail. Her energy failed, and her judgment went with it. That's the trap. We assume our thinking stays constant, that the brain in hour fourteen is the same brain that showed up in hour one. It's not. Last episode, we tackled deciding under uncertainty. But fatigue does something different. Uncertainty makes you hesitate. Fatigue makes you stop caring. Why Your Brain Makes Worse Decisions by Evening You've probably heard the popular saying: "Making too many decisions wears you out, so by evening your judgment is shot." That idea dominated psychology for twenty years. Researchers believed decision-making drained from a limited mental reserve, like a battery running down. Then, independent labs tried to reproduce those results at scale, and the effect vanished. One study, 23 labs, over 2,000 people, found nothing. A second, 36 labs, 3,500 people, same result. The experience is real, though. People do make worse decisions after a long day of mental effort. What was wrong was the explanation. Your brain doesn't drain like a battery. After sustained effort, it shifts priorities. It starts favoring speed and ease over accuracy. Not because it can't think carefully, but because it decides careful thinking isn't worth the effort. Decision fatigue isn't your brain shutting down. It's your brain quietly lowering its standards without telling you. Decision Fatigue in the Real World That science isn't abstract. It plays out every day. Researchers at Brigham and Women's Hospital tracked over 21,000 patient visits. Doctors prescribed unnecessary antibiotics more frequently as the day went on. Not because afternoon patients were sicker. Because saying "here's a prescription" is easier than explaining why you don't need one. Five percent more patients received antibiotics they didn't need, purely because of timing. The same pattern shows up everywhere. Surgeons make more conservative calls later in the day. Hand hygiene compliance drops across a twelve-hour shift. Financial analysts grow less accurate with each additional stock prediction they make in a single day. The drift always goes in the same direction: toward whatever requires the least effort. That drift explains something we've been exploring across this series. When you're exhausted, someone else's conclusion isn't just tempting, it's a relief. The algorithm's recommendation saves you from having to evaluate. The expert's opinion saves you from forming your own. That's mindjacking, finding the open door. Fatigue doesn't just degrade your thinking. It makes you grateful to hand it over. Your Four Warning Signals Knowing the science is useful. But what matters more is catching fatigue in yourself before it costs you. Here are four signals that your judgment is compromised. Signal 1: The Default Drift. Someone proposes a plan that sounds... fine. Not great, not terrible. Two hours ago, you'd have pushed back, asked harder questions. Now you just nod. You're not agreeing because you're convinced. You're agreeing because disagreeing takes energy you no longer have. Signal 2: The Irritability Spike. A colleague asks a reasonable question, and it feels like an interruption. When your emotional response is out of proportion to the situation, it's not the situation. Your reserves are low. Signal 3: The Shortcut Reflex. A decision that should take twenty minutes takes...

You've got a decision you've been putting off. Maybe it's a career move. An investment. A difficult conversation you keep rehearsing in your head but never starting. You tell yourself you need more information. More data. More time to think. But you're not gathering information. You're hiding behind it. What looks like due diligence is […]

You've got a decision you've been putting off. Maybe it's a career move. An investment. A difficult conversation you keep rehearsing in your head but never starting. You tell yourself you need more information. More data. More time to think. But you're not gathering information. You're hiding behind it. What looks like due diligence is actually overthinking in disguise. The certainty you're waiting for doesn't exist. It won't exist until after you decide and see what happens. I call this mindjacking: when something hijacks your ability to think for yourself. Sometimes it's external. Algorithms, experts, crowds thinking for you. But sometimes you're the one doing it. That endless research? It feels like diligence. It functions as delay. You're not being thorough. You're mindjacking yourself. Today, you'll learn a framework for knowing when you have enough information, even when it doesn't feel like enough. Because deciding before you're ready isn't recklessness. It's a skill. And for most people, that skill has completely atrophied. The Real Cost of Waiting At a California supermarket, researchers set up a tasting booth for gourmet jams. Some days, the display showed 24 varieties. Other days, just six. The bigger display attracted more attention. Sixty percent of people stopped to look. But only three percent actually bought jam. When shoppers saw just six options? Thirty percent purchased. Ten times the conversion rate. More options didn't help people choose. More options paralyzed them. The jam study has been replicated across dozens of categories since then. The pattern holds. More choices, more overthinking, fewer decisions. Think about your postponed decision. How many options are you juggling? How many articles have you read? Every expert you consult, every scenario you play out in your head... you're not getting closer to certainty. You're adding jams to the display. And while you're researching, the world keeps moving. Opportunities close. Competitors act. Your own situation shifts. The decision you're avoiding today won't even be the same decision six months from now. Waiting has a cost. Most people dramatically underestimate it. The Two-Door Framework So how do you know when you have enough information? Jeff Bezos uses a mental model that's useful here. Picture every decision as a door you're about to walk through. Some doors are one-way: once you're through, you can't come back. Selling your company. Getting married. Signing a ten-year lease. These deserve serious deliberation. Most decisions, though, are two-way doors. You walk through, look around, and if you don't like what you see, you walk back out. Starting a side project. Trying a new marketing strategy. Having that difficult conversation. The consequences are real, but they're not permanent. The mistake most people make is treating two-way doors like one-way doors. They apply the same level of analysis to choosing project management software as acquiring a company. They're not being thorough. They're overthinking reversible choices. That's how organizations grind to a halt. That's how careers stall. That's how opportunities evaporate while you're still "thinking about it." Before you gather more information, ask yourself: Can I reverse this? If yes, even if reversing would be annoying, you're probably overthinking it. The 40-70 Rule General Colin Powell used a decision framework he called the 40-70 rule. Military leaders and executives have adopted it for decades. The Floor: 40% Never decide with less than forty percent of the information you'd want. Below that threshold, you're not being decisive. You're gambling. The Ceiling: 70% Don't wait for more than seventy percent. By the time you've gathered that much data, the window has usually closed. Someone else acted. The situation changed. The decision got made for you, by default. The Sweet Spot That range between forty and seventy percent is where good decisions actually happen....

You've built a toolkit over the last several episodes. Logical reasoning. Causal thinking. Mental models. Serious intellectual firepower. Now the uncomfortable question: When's the last time you actually used it to make a decision? Not a decision you think you made. One where you evaluated the options yourself. Weighed the evidence. Formed your own conclusion. […]

You've built a toolkit over the last several episodes. Logical reasoning. Causal thinking. Mental models. Serious intellectual firepower. Now the uncomfortable question: When's the last time you actually used it to make a decision? Not a decision you think you made. One where you evaluated the options yourself. Weighed the evidence. Formed your own conclusion. Here's what most of us do instead: we Google it, ask ChatGPT, go with whatever has the most stars. We feel like we're deciding, but we're not. We're just choosing which borrowed answer to accept. That gap between thinking you're deciding and actually deciding is where everything falls apart. And there's a name for it. What Mindjacking Actually Is Mindjacking. Not the sci-fi version where hackers seize your brain through neural implants. The real version. Where you voluntarily hand over your thinking because someone else already did the work. It's not dramatic. It's convenient. The algorithm ranked the results. The expert weighed in. The crowd already decided. Why duplicate the effort? Mindjacking is different from ordinary influence. You choose it. Every single time. Nobody forces you to stop evaluating. You volunteer, because forming your own conclusion is harder than borrowing someone else's. What exactly are you losing when this happens? The Two Skills Under Attack Mindjacking destroys two distinct capabilities. They're different, and you need both. Evaluation independence is the ability to assess whether a claim is valid. Not whether the source has credentials. Not whether experts agree. Whether the evidence actually supports the conclusion. Decision independence is the ability to commit to a path based on your own judgment, without needing someone else to validate it first. Both skills need each other. Watch what happens when one erodes faster than the other. A woman researches her medical condition for hours. Journal articles. Treatment comparisons. She understands her options better than most medical students would. She walks into the doctor's office, lays out her analysis. It's thorough. Sophisticated, even. The doctor reviews it and says, "This is impressive. You've really done your homework." She nods. Then looks up and asks: "So what should I do?" She can evaluate. She can't decide. Now flip it. Think about someone who decides fast. Trusts their gut. Never waits for permission. How often does that person get burned by bad information they never verified? They can decide. They can't evaluate. Lose either ability and you're trapped. Lose both and you're not thinking at all. The Four Surrender Signals How do you know when mindjacking is happening? It has a signature. Four internal signals that reveal the handoff in progress, if you know how to read them. Signal one: Relief. The moment you find "the answer," you notice a weight lifting. Pay attention to that. Relief isn't insight. It's the burden of thinking being removed. When you actually work through a problem yourself, the result isn't relief. It's clarity. And clarity usually comes with new questions, not a sense of "done." Signal two: Speed. Uncertainty to certainty in seconds? That's not evaluation. You found someone else's answer and adopted it. There's a difference between "I figured it out" and "I found someone who figured it out." One took effort. The other took a search bar. Signal three: Echo. Listen to your own conclusions. Do they sound like something you read, heard, or scrolled past recently? If your "own opinion" matches a headline almost word-for-word, it probably isn't yours. You're not thinking. You're repeating. Signal four: Unearned confidence. You're certain about a conclusion, but ask yourself: could you explain the reasoning behind it? Not where you heard it. The actual reasoning. If you can't, that confidence isn't yours. It came attached to someone else's answer, and you absorbed both their conclusion and their certainty without doing any analysis...

This week, I'm in Las Vegas, Nevada, at the annual Consumer Electronics Show 2026. If you've been following me for long, you know I do this every year. This is 20-plus years I've been coming to the Consumer Electronics Show. Normally, I don't cover tech and new products here—except for once a year at CES. […]

Welcome to this week's show. I'm recording this episode from my hotel room here in Las Vegas, Nevada, at the annual Consumer Electronics Show 2026. If you've been around this channel for long, you know I do this every year. This is 20-plus years I've been coming to the Consumer Electronics Show. Normally, I don't cover tech and new products on this channel—except for once a year at CES. And it's less about specific companies and what they've announced. You can find that on thousands of channels on YouTube or podcasts. What I like to talk about are the trends—the trends that are emerging—and give you my view and opinion on what they really mean for the innovation space. Are we really innovating, or are we just regurgitating the same thing year after year? I do have some notes here that I'll be glancing at as we go through this today, and we'll be splicing in videos I took on the show floor, along with video supplied to us by CES, to give you a feel for what was here and what's going on. The Show's Legacy First, let's recognize that the Consumer Electronics Show is now in its 59th year. It's a spin-off from the old Chicago music show back in the late 1960s. Yes, the late '60s. It's gone through some gyrations over the decades and remains one of the few big shows that survived COVID. Traditional Consumer Electronics As usual, one of the big emphases is TVs, displays, home automation, new refrigerators, new washers and dryers—true consumer electronics, things you would find and put into your home. This year was no different. The big manufacturers were here, along with a number of new smaller manufacturers showcasing new TV technologies. Micro LED is the new buzzword bouncing around the show, and there were plenty of displays to see. I'm a big TV guy, so I definitely had to check that out and see what could be the next TV I put into my house. The AI and Robotics Takeover The one thing about this year's show that was just overwhelming was robots and AI. They were everywhere. I couldn't even tell you how many times we saw AI applied to things that make no sense—though some applications were actually pretty smart. But how many AI toilets do you really need at any given show? On the robotics side, we saw all the familiar ones—like lawn mowers that automatically find your boundaries. One was actually selling the feature that you could program in graphic designs, and it would cut your yard in such a way that the design would appear in your lawn. We also saw humanoid robots, robots doing backflips, robots dancing with people, dancing hands where the fingers are moving. You could buy just the hands or the arms or the elbows and assemble your own robots. It was pretty crazy. Then we started seeing the combination of AI and robots—interactive robots where you could stand there, talk with them, point, and they would follow your commands. Pick up this item. Move this item somewhere else. Not programming through some controller, but simply pointing and talking to direct the robot to do what you want. The Evolution of Electric Vehicles One thing we've seen in past shows was the big emphasis on electric vehicles. This year, the EV car market—which we've seen slow down generally—also slowed down here at the show. However, what we saw in its place focused on two areas: Commercial EVs and Hybrids: There was significant attention on commercial use of EVs, particularly hybrid electric vehicles with combustion engines. Emergency Response Innovation: One exhibit that really impressed me was a fire truck supplied by Dallas Fort Worth Airport. This massive Oshkosh fire truck is a hybrid that uses electric motors for high torque and high acceleration—literally shaving seconds off response time. Given the limited distance on airport property, if there's a disaster or fire requiring quick reaction, the electric motors can accelerate very quickly. There are only about 15 of these trucks in the world, and something like six or seven are just...

Twenty-one years. That's how long I've been doing this. Producing content. Showing up. Week after week, with only a handful of exceptions—most of them involving hospitals and cardiac surgeons, but that's another story. After twenty-one years, you learn what lands and what doesn't. You learn not to get too attached because you never know what's […]