Latest / Wits & Weights | Strength & Fat Loss Over 40 / The Biggest AI Mistake People Make With Fat Loss Over 40 | Ep 481

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The Biggest AI Mistake People Make With Fat Loss Over 40 | Ep 481 · Wits & Weights | Strength & Fat Loss Over 40

• 0:00
  Philip Pape: You now have access to more fitness information than any human in history.
• 0:04
  Philip Pape: Every answer about how to lose fat, how to build muscle, absolutely free just in seconds using AI.
• 0:12
  Philip Pape: But ask yourself how that's working for you.
• 0:14
  Philip Pape: You're probably not more consistent than you were a year ago, two years ago.
• 0:18
  Philip Pape: You're not any leaner.
• 0:20
  Philip Pape: And today I want to show you why AI, as you're probably using it, is not really much of an upgrade over a Google search.
• 0:27
  Philip Pape: It might even make things worse.
• 0:29
  Philip Pape: How to actually use AI so it's helpful and effective for you, and a few specific examples of the right and wrong ways to put it to work for your training and nutrition.
• 0:42
  Philip Pape: Welcome to Wits and Weights, the show that puts a popular piece of fitness advice under the microscope, finds the hidden reason it doesn't work, and gives you the deceptively simple fix that does.
• 0:52
  Philip Pape: I'm your host, Philip Abe, and this is an episode I've wanted to do for a while.
• 0:56
  Philip Pape: I think the timing is perfect because everybody and their mother is now using AI for their health and fitness, from Chat GPT to Claude to just random Google searches and everything in between.
• 1:09
  Philip Pape: There's Buco tools and software being generated that use AI.
• 1:14
  Philip Pape: You're asking it, how do I eat?
• 1:16
  Philip Pape: How do I train?
• 1:16
  Philip Pape: Is my plan any good?
• 1:18
  Philip Pape: And I think it's really, I think it's awesome that we have technology to play with like this.
• 1:23
  Philip Pape: And depending on who you are, if you're over 40, if you're navigating perimenopause or menopause, if you're lifting weights, you're trying to lose fat, trying to hold on to muscle, you've probably used AI by this point and asked it a question like, hey, what is the best workout for me given XYZ?
• 1:39
  Philip Pape: Or hey, build me a meal plan given my macros.
• 1:42
  Philip Pape: Am I am I right?
• 1:43
  Philip Pape: Am I right?
• 1:44
  Philip Pape: And if not, you're probably like, oh, I can do that.
• 1:46
  Philip Pape: Let me go try it out.
• 1:47
  Philip Pape: But I bet most of you have done that.
• 1:49
  Philip Pape: And I want to be totally careful and walk the line on this episode because I am definitely not anti-AI.
• 1:56
  Philip Pape: Not only do I use it all the time in my business as a power assist to save tons of time, especially on tedious type of work, but I built an AI coaching app.
• 2:06
  Philip Pape: So I use these tools every single day.
• 2:08
  Philip Pape: It this is not the, you know, robots are coming.
• 2:10
  Philip Pape: This is Skynet Terminator taking over the world episode.
• 2:14
  Philip Pape: And it's also not, hey, I, AI is the best and most amazing thing that will solve everything.
• 2:18
  Philip Pape: Oh, and the last thing, it's not.
• 2:20
  Philip Pape: I'm not gonna get into like how much water it sucks up and how expensive microchips are going to be and how the billionaires are gonna take over the planet.
• 2:27
  Philip Pape: I'm not getting into any of that stuff.
• 2:29
  Philip Pape: I'm gonna try to keep the focus narrow.
• 2:32
  Philip Pape: I think AI is a useful tool.
• 2:34
  Philip Pape: That's it.
• 2:35
  Philip Pape: Like any other tool, it's tool.
• 2:36
  Philip Pape: It's probably one of the most incredibly game-changing advances that we've seen in such a short period of time.
• 2:43
  Philip Pape: And that can be highly dangerous in many of our minds, of course, when there's not appropriate, you know, boundaries on it.
• 2:49
  Philip Pape: We saw this recently when Claude had to walk back the release of their latest mythos class model.
• 2:56
  Philip Pape: You don't have to know what I'm talking about, but basically they said, yeah, this is too dangerous.
• 2:58
  Philip Pape: Like people can create bioweapons or whatnot and you know, hack into banks and if they use it.
• 3:04
  Philip Pape: So we're gonna turn it off.
• 3:05
  Philip Pape: So I totally get all of that.
• 3:06
  Philip Pape: Like I'm pretty educated in what's going on there.
• 3:09
  Philip Pape: I love tech.
• 3:10
  Philip Pape: I'm into all of that.
• 3:11
  Philip Pape: But what this episode today is is about the gap between what AI can do and what most people use it for and how they use it.
• 3:19
  Philip Pape: And we're gonna kind of explore that gap so you can take advantage of the tool for yourself because ultimately I want you to be able to use the tool in an educated way to help you out.
• 3:29
  Philip Pape: That's it.
• 3:30
  Philip Pape: I want you to also stick around to the end of the episode because I'm going to give you a prompt.
• 3:34
  Philip Pape: It's a one-line prompt that you can paste into any AI chatbot that actually helps it help you better by pressure testing your plant rather than just totally agreeing with you.
• 3:46
  Philip Pape: A concept called sycophancy, AI sycophancy, which, you know, South Park made a really funny episode about that a while back.
• 3:52
  Philip Pape: You should look that up.
• 3:53
  Philip Pape: But a lot of people, a lot of people aren't aware that they can they can train or they can update settings in their AI to help it, help it do better for you.
• 4:02
  Philip Pape: And it just takes a few seconds to set that up.
• 4:04
  Philip Pape: So stick around for that.
• 4:05
  Philip Pape: But here's where we're going today.
• 4:06
  Philip Pape: I'm gonna show you the bottleneck that has nothing to do with information.
• 4:12
  Philip Pape: I'm gonna show you four things that AI is genuinely good at that can move the needle for you.
• 4:17
  Philip Pape: And I'm gonna show you the difference between using it well and using it more like a search engine, like a lot of people use it.
• 4:23
  Philip Pape: Okay.
• 4:24
  Philip Pape: So hopefully this is a great episode for you.
• 4:26
  Philip Pape: And as always, I love to start with hey, what is the conventional wisdom?
• 4:30
  Philip Pape: What do people talk about?
• 4:31
  Philip Pape: What do people claim that is true and maybe it's not?
• 4:36
  Philip Pape: And the information's been out there when it comes to health and fitness and all of this stuff.
• 4:41
  Philip Pape: It's been out there for over a decade.
• 4:42
  Philip Pape: I mean, I got into podcasting in my own personal journey because I was able to get access to great podcasts and books and videos.
• 4:49
  Philip Pape: And this was all before AI.
• 4:51
  Philip Pape: And if you think about it, everything you need to know, to know, okay, information to lose fat, to get strong, to do all the things we talk about, to improve your metabolic health, has been sitting on the internet for free, even since before some of you started your fitness journey, even going back to like the bodybuilding forums and going back to the early days of the internet.
• 5:10
  Philip Pape: How to set up protein and get enough, how to structure your lifting, progressive overload, energy balance, like all that stuff.
• 5:16
  Philip Pape: And if anything, we have more so much information now that it's confusing, right?
• 5:21
  Philip Pape: Like it's who who's telling the truth.
• 5:22
  Philip Pape: We have influencers, we have social media.
• 5:24
  Philip Pape: None of it is secret, I'll say.
• 5:26
  Philip Pape: And if it is purported to be a secret, they're probably trying to sell you something.
• 5:30
  Philip Pape: So, so none of it is gated behind a paywall.
• 5:33
  Philip Pape: You can find all the studies, you can find all the information.
• 5:36
  Philip Pape: You could have learned every relevant principle even 10 years ago without spending a dime, even though the science continues to get refined, is pretty darn close to what you would need to do.
• 5:46
  Philip Pape: And of course, we know this because people have been successful improving their health and fitness for much longer than we've had the internet.
• 5:52
  Philip Pape: And of course, we've now gotten just better and better at it.
• 5:56
  Philip Pape: So the question that should really bother you here is okay, if information is the thing standing between me and what I want, the body I want to be lean, to be strong, to be healthy, to stop binge eating and to get rid of food noise, whatever it is, you'd already have it, right?
• 6:12
  Philip Pape: You'd already have it.
• 6:12
  Philip Pape: You you'd be done.
• 6:13
  Philip Pape: Like you would have solved the problem, you'd have your plan, you'd execute, you'd be good.
• 6:17
  Philip Pape: Everybody who has a smartphone, which is like the entire world, would have what they want.
• 6:21
  Philip Pape: We'd be lean and strong.
• 6:22
  Philip Pape: They'd they'd be millionaires, billionaires, whatever.
• 6:24
  Philip Pape: Right.
• 6:24
  Philip Pape: And you, I know you've heard this argument plenty of times, right?
• 6:27
  Philip Pape: Everybody has access to the same information today.
• 6:30
  Philip Pape: Information is as cheap as it's ever been.
• 6:32
  Philip Pape: It's more democratized than it's ever been.
• 6:34
  Philip Pape: You know, started with the printing press and it just went from there.
• 6:37
  Philip Pape: And now we have the internet and now we have AI.
• 6:40
  Philip Pape: But that doesn't matter, apparently, because many of us are still struggling.
• 6:44
  Philip Pape: That's why you're listening to this podcast, because you're trying to figure out, okay, what is the secret or what is the thing I need to do?
• 6:50
  Philip Pape: So information was never the bottleneck.
• 6:52
  Philip Pape: And that's important because AI, the way most people use it, ChatGPT and Cloud and all of these, is a machine, a highly intelligent, you know, neural network machine learning trained, you know, whatever tech behind it machine for producing more information.
• 7:08
  Philip Pape: Now you might not like that, that's the case, because that's really what it's doing.
• 7:12
  Philip Pape: It's taking all of the knowledge that we have in human existence that it has access to and it's processing through that using very intelligent algorithms that are self-learning in many cases.
• 7:22
  Philip Pape: And I know that scares a lot of us, but it's faster, it's, I'll say, cleaner, it uses better grammar, it's personalized to your exact question.
• 7:30
  Philip Pape: I mean, now when you go to Google and you search, Google's smart about it.
• 7:33
  Philip Pape: They use Gemini to just to give you the answer at the top.
• 7:36
  Philip Pape: In fact, a lot of a lot of businesses don't like it because now there's sponsored results or their links at the top, people don't go to them anymore.
• 7:42
  Philip Pape: They just get the answer right from Google.
• 7:44
  Philip Pape: But it's still more information.
• 7:45
  Philip Pape: And it's still, it's like Wikipedia, it's kind of like what Wikipedia has done in a way, where you guys, you know this.
• 7:52
  Philip Pape: You go to Wikipedia and you search up something and then you can follow through with all the the references.
• 7:56
  Philip Pape: So if information was never the problem, then more information, even if it's better delivered, is not the solution, is it?
• 8:02
  Philip Pape: I mean, you tell me.
• 8:03
  Philip Pape: It has it solved things for you?
• 8:06
  Philip Pape: Or is it a marginal or maybe even large upgrade on something that was never really the problem?
• 8:13
  Philip Pape: So I want to talk about the actual problem.
• 8:16
  Philip Pape: Okay.
• 8:16
  Philip Pape: There's a researcher named Pascal Sheeran who did a big review of health behavior studies.
• 8:22
  Philip Pape: And across studies on exercise, on screening, on all kinds of health behaviors, he found that of the people who had a genuine positive intention to do the thing, to do the thing they wanted to do, they wanted to do it passionately.
• 8:37
  Philip Pape: They planned to do it, whatever that thing is, the median proportion who then did not follow through was 47%.
• 8:45
  Philip Pape: 47%.
• 8:46
  Philip Pape: So almost half of the people who intend to act don't.
• 8:50
  Philip Pape: And so I want you to sit with that because there's a lot of judgment today about, well, you just gotta do it, right?
• 8:55
  Philip Pape: You're just, I don't even want to say people get accused of being lazy, but we think of obesity and things like that.
• 9:00
  Philip Pape: Even if behavior is a part of the equation, okay, okay, let's say it is.
• 9:05
  Philip Pape: Are you able to follow through on that behavior?
• 9:08
  Philip Pape: Right.
• 9:08
  Philip Pape: And and as soon as you judge somebody else, like put point the finger at yourself and think of anything that you failed to follow through on in your entire life.
• 9:15
  Philip Pape: There's probably millions of things.
• 9:17
  Philip Pape: Okay.
• 9:18
  Philip Pape: The constraint was never knowing what to do.
• 9:20
  Philip Pape: It's that vast canyon between intending to do it and actually doing it.
• 9:25
  Philip Pape: Not only that, but consistently, especially on the days you don't feel like it, because that's how you get consistent.
• 9:31
  Philip Pape: The days you feel like it, you're gonna do it.
• 9:33
  Philip Pape: But there are probably more days you don't feel like it than there are that you do.
• 9:37
  Philip Pape: So knowing and doing are two completely different problems.
• 9:41
  Philip Pape: And AI, especially when it's used as a fact retrieval machine, only really solves that first problem, the knowing part.
• 9:49
  Philip Pape: And that's not really the problem that you have.
• 9:51
  Philip Pape: Does that make sense?
• 9:52
  Philip Pape: So, and okay, by the way, we have good data on the doing side as well, like actually following through.
• 9:58
  Philip Pape: There's a famous diet study by Danzinger, where they put people on four completely different popular diets: Atkins, Ornish, Zone, and Weight Watchers.
• 10:09
  Philip Pape: Now we're going back in the time machine, aren't we?
• 10:10
  Philip Pape: Okay, let's see.
• 10:11
  Philip Pape: I've tried two of those, Atkins and Zone.
• 10:15
  Philip Pape: And so they're completely different diets, different mechanisms, different macros, whatever.
• 10:19
  Philip Pape: And what they found is no meaningful difference between the diets.
• 10:23
  Philip Pape: What predicted whether someone lost weight was not the diet they were on, it was whether they stuck to the diet.
• 10:29
  Philip Pape: Adherence.
• 10:30
  Philip Pape: Okay.
• 10:30
  Philip Pape: Broken record, guys, if you ever, if you've already been following my podcast, you know this is a tenet of what we talk about is adherence.
• 10:37
  Philip Pape: That is the key.
• 10:38
  Philip Pape: It's not the mechanism, it's not the plan, it's the doing, the doing, the doing.
• 10:45
  Philip Pape: Okay, do it, just do it.
• 10:47
  Philip Pape: Okay.
• 10:47
  Philip Pape: So if you've been treating AI, I don't know why I'm in a good mood today, but if you've been treating AI as the thing that finally gives you the answer, I want to gently suggest to you that you're solving a problem you don't even have and you're ignoring the problem that you do have.
• 10:59
  Philip Pape: So we're gonna get into that now.
• 11:01
  Philip Pape: All right, so if information is not the bottleneck, behavior change is the bottleneck.
• 11:05
  Philip Pape: Let's talk about why this matters for how you use AI, because this is where I think it gets interesting.
• 11:12
  Philip Pape: AI is really, really good at some of the behavior change stuff, but it's not what a lot of people use it for.
• 11:19
  Philip Pape: All right, and I'm gonna piss off a lot of coaches, a lot of behavior change specialists who think you have to have a human in the mix all the time to help people change their behavior.
• 11:27
  Philip Pape: That's absolutely not true.
• 11:28
  Philip Pape: Okay, well, follow, follow me on the logic.
• 11:31
  Philip Pape: There's a study out of out of a team at Google.
• 11:33
  Philip Pape: Now take that with a grain of salt, a team at Google where they took a large language model, so that would be like a chat GPT type software, and they they directed it at activity coaching.
• 11:44
  Philip Pape: So activity coaching, coaching for activities.
• 11:48
  Philip Pape: And they tested on things like is the advice actionable?
• 11:50
  Philip Pape: Is it realistic?
• 11:52
  Philip Pape: Is it empathetic?
• 11:54
  Philip Pape: Does it motivate?
• 11:56
  Philip Pape: And what's so telling is that the model itself got significantly better at being actionable and realistic when they set it up well.
• 12:05
  Philip Pape: Okay.
• 12:05
  Philip Pape: In fact, big jumps in those two areas, but on empathy and motivation, the gains were not even statistically significant.
• 12:14
  Philip Pape: So the machine got better at the practical translation stuff, and it stayed pretty weak as a model or as a tool at the human stuff.
• 12:23
  Philip Pape: And so from that point, we can say, okay, so there are things that need to be kept with a human.
• 12:32
  Philip Pape: Like I just said, empathy and motivation.
• 12:34
  Philip Pape: There are now, having said that, there's a way to marry the two and kind of amplify the two.
• 12:38
  Philip Pape: We're gonna get into that, but first we need to understand the AI side of the equation.
• 12:42
  Philip Pape: So what's it what's AI good at?
• 12:43
  Philip Pape: I think there are four things.
• 12:45
  Philip Pape: Four things.
• 12:45
  Philip Pape: And a lot of you aren't even using it for any of these things.
• 12:48
  Philip Pape: Number one, and I think this is the big one, is it can recognize patterns in data.
• 12:53
  Philip Pape: Makes sense, right?
• 12:54
  Philip Pape: It can take a lot of the more data you give it, the more it can act on it.
• 12:57
  Philip Pape: It's really powerful for that.
• 12:59
  Philip Pape: So instead of when we think of food, not what should I eat, it's here's what I actually ate.
• 13:04
  Philip Pape: So here's my food log, macrofactor, whatever.
• 13:06
  Philip Pape: And I've given it to you for the last three weeks of data.
• 13:09
  Philip Pape: What patterns do you see in my eating to help me decide what to eat?
• 13:14
  Philip Pape: Now that's a very different question, isn't it?
• 13:16
  Philip Pape: Because now it is working with your reality instead of giving you a generic answer.
• 13:20
  Philip Pape: So it's using data, which makes a lot of sense.
• 13:23
  Philip Pape: And this can be used for a lot of things, like your lifting, right?
• 13:27
  Philip Pape: You can put in your workout logs, you can put in your biofeedback data, you could you could do everything that I have clients do as a coach, everything that they track, body measurements, weight, like you name it, you can give it that data.
• 13:40
  Philip Pape: In many cases, these tools are now integrated with Apple Health and whatnot, and it makes it even easier to do that.
• 13:46
  Philip Pape: And a lot of tools are being developed to take advantage of that as well, right?
• 13:50
  Philip Pape: Same thing with something very specific like your protein intake and looking at the patterns and saying, oh my goodness, it looks like my protein falls off here and here, and here's why.
• 14:00
  Philip Pape: Because if you're just tracking it in a food log, like let's say Macrofactory, you can kind of see that visually and figure it out on your own.
• 14:06
  Philip Pape: But what if there are things you can't really see as easily?
• 14:09
  Philip Pape: And I think the AI is great for that.
• 14:11
  Philip Pape: It can catch it in you know milliseconds or seconds.
• 14:14
  Philip Pape: So finding a signal out of the noise, as we say, in a pile of data.
• 14:18
  Philip Pape: And the more, and the bigger the bigger the pile of data, the better.
• 14:22
  Philip Pape: So that's what's great is you can feed it so much data, lab work.
• 14:25
  Philip Pape: I mean, just dump it in there.
• 14:27
  Philip Pape: All right, number two is accountability and a check-in structure.
• 14:31
  Philip Pape: Now you might say, well, isn't that the human part?
• 14:34
  Philip Pape: Well, no, again, we're talking about activities.
• 14:36
  Philip Pape: We're not talking about like empathy or motivation per se, although I'm going to argue that a lot of our motivation is intrinsic motivation that does come from checking in and accountability.
• 14:47
  Philip Pape: So let me get a little more precise on this part, on the accountability part, because it there's nuance here.
• 14:53
  Philip Pape: AI can scaffold a check-in, let's say.
• 14:57
  Philip Pape: Let's use the word scaffold, right?
• 14:59
  Philip Pape: Like a scaffolding around a building.
• 15:00
  Philip Pape: It can ask you the right questions on the right cadence.
• 15:04
  Philip Pape: What it cannot do, it doesn't care whether you lied to it, it doesn't know.
• 15:09
  Philip Pape: There are no stakes, there's no aspect of like empathy to it.
• 15:14
  Philip Pape: It's just cold calculated.
• 15:16
  Philip Pape: And it's like, if this is the check-in you want to do it.
• 15:18
  Philip Pape: And let me let me elaborate on this because there's there's a a data set in the research where they had 65,000 people using a coaching app and they compare people who had AI coaching alone versus people who had AI plus a human coach.
• 15:32
  Philip Pape: The group with a human with the AI lost over 74% more weight than the group that just had the AI coaching.
• 15:41
  Philip Pape: And it was the same app.
• 15:42
  Philip Pape: The only difference there was a human in the loop.
• 15:45
  Philip Pape: And the mechanism here is that the people with a human coach, they actually logged their food and their weight more often.
• 15:53
  Philip Pape: And it's not like the human had secret knowledge, the human just created stakes that made them actually do the thing.
• 16:01
  Philip Pape: So that's that's what's kind of interesting.
• 16:02
  Philip Pape: That's a motivation piece.
• 16:04
  Philip Pape: That's pretty cool, right?
• 16:05
  Philip Pape: That's why humans are gonna be important for a long time, hopefully for the rest of eternity.
• 16:10
  Philip Pape: But I wanted to talk about that difference, right?
• 16:13
  Philip Pape: So, in other words, AI can be incredibly useful, humans are incredibly useful, and men put them together and you have a very powerful combination.
• 16:22
  Philip Pape: Number three is a customized application of a general principle to your specific situation.
• 16:29
  Philip Pape: Anyone take physics, right?
• 16:31
  Philip Pape: Or, you know, you've heard of Einstein, where we talk about general relativity versus special relativity.
• 16:36
  Philip Pape: So think about that.
• 16:36
  Philip Pape: All the principles you read about or hear about on podcasts or this show, they're general principles.
• 16:41
  Philip Pape: At least I hope they're talking to you in terms of principles and not telling you this is the answer, the one answer.
• 16:46
  Philip Pape: Because there is no one answer.
• 16:48
  Philip Pape: There are principles, and then you have your specific situation.
• 16:51
  Philip Pape: So, like the principle of eating around 0.7 to one gram of protein per pound of body weight, everybody knows that.
• 16:57
  Philip Pape: But what's your body weight?
• 16:59
  Philip Pape: What's your goal?
• 17:00
  Philip Pape: What is your schedule?
• 17:01
  Philip Pape: What are you capable of eating?
• 17:02
  Philip Pape: Are you vegan, vegetarian, blah, blah, blah?
• 17:04
  Philip Pape: You know, are you dairy-free?
• 17:06
  Philip Pape: Like, how do you hit that number?
• 17:08
  Philip Pape: You know, all those things are the you parts of it.
• 17:11
  Philip Pape: Are you in fat loss or not?
• 17:12
  Philip Pape: This and that.
• 17:13
  Philip Pape: That's where a real person gets stuck.
• 17:15
  Philip Pape: That's where people get stuck.
• 17:17
  Philip Pape: Okay.
• 17:18
  Philip Pape: The translation, the translating that principle to your messy, chaotic real life, AI is great at.
• 17:25
  Philip Pape: It's actually great at because it's not just retrieving a fact, it is taking all the data that you've told it, finding the patterns like we just talked about, and then translating it to you.
• 17:37
  Philip Pape: And you actually don't need a human for that per se.
• 17:39
  Philip Pape: Okay.
• 17:40
  Philip Pape: Now, that's like there's a caveat on that because obviously if the AI is not asking the right questions or you're not feeding it all the data it needs, it can give you a garbage answer.
• 17:48
  Philip Pape: Whereas a human might say, Whoa, whoa, wait a minute, I need to know this and this as well.
• 17:51
  Philip Pape: But that doesn't mean AI can't do it.
• 17:54
  Philip Pape: Okay.
• 17:54
  Philip Pape: Understand the difference.
• 17:56
  Philip Pape: It has to be good enough to do it and you have to use it the right way.
• 17:58
  Philip Pape: And then number four is AI is good at asking the questions that you don't know to ask because you don't know what you don't know.
• 18:08
  Philip Pape: So, as an engineer, I come from the world of requirements for a product, and there's things that you know, there's things you know that you don't know, and there's things you don't know that you don't know.
• 18:18
  Philip Pape: So instead of like, hey, what's the best exercise to get bigger glutes?
• 18:23
  Philip Pape: Because I want a big butt, you say, Hey, what am I not considering about my training or my protein as I go through menopause and given my program right now because I want a big butt, right?
• 18:35
  Philip Pape: Or something like that.
• 18:36
  Philip Pape: Like giving it that context and then have it give you what the blind spots are.
• 18:42
  Philip Pape: You know, notice what I just said.
• 18:44
  Philip Pape: What am I not considering about dot dot dot?
• 18:46
  Philip Pape: Great prompt right there.
• 18:48
  Philip Pape: What am I not thinking about?
• 18:50
  Philip Pape: Right.
• 18:51
  Philip Pape: And so that would turn AI kind of like into a coach that asks you questions that you wouldn't think to ask of yourself.
• 18:57
  Philip Pape: So those are the four things pattern recognition in your data, an accountability structure, applying principles to your specific situation, and then uh kind of surfacing up these blind spots that you're not thinking of.
• 19:10
  Philip Pape: Now, what does every single one of those have in common?
• 19:13
  Philip Pape: Well, they all require you to bring something to the equation.
• 19:17
  Philip Pape: That is your data, your plan, your situation, your context.
• 19:22
  Philip Pape: I mean, until the day that AI is like hardwired into our brain, God help us all, you have to bring that stuff.
• 19:28
  Philip Pape: Now, I just I mentioned before, sometimes it's integrated with Apple Health or Aura rings or whatever.
• 19:33
  Philip Pape: And granted, that is kind of an automated way to do that.
• 19:36
  Philip Pape: I'm not saying it doesn't have to be automated, just you have to bring that stuff.
• 19:39
  Philip Pape: And so the good uses of AI, in my opinion, are a conversation about your actual life and getting some help on the blind spots and structure accountability, all that stuff.
• 19:49
  Philip Pape: Whereas a bad way to use AI would just be a generic search, a generic question, using it as kind of like an advanced Google.
• 19:56
  Philip Pape: Does that make sense?
• 19:57
  Philip Pape: This is honestly right now the perfect place to mention the thing that I've built that's out there that I think takes advantage of all of these in a very thoughtful way, where AI is the application layer.
• 20:09
  Philip Pape: It's not an information fire hose.
• 20:11
  Philip Pape: It just dumps information at you.
• 20:12
  Philip Pape: It really is the this intelligence or interpretation on top of your data.
• 20:18
  Philip Pape: And that's called Fitness Lab.
• 20:19
  Philip Pape: This is my app.
• 20:20
  Philip Pape: I'm giving you a shameless plug for it because it does exactly what I've thought through AI can do well, that can help in the fitness and training world, that also is pre-trained with lots and lots and lots of good evidence-based data, as well as my entire podcast, all my guides, all that fun stuff.
• 20:38
  Philip Pape: It's all trained into there.
• 20:40
  Philip Pape: Exercises, you name it.
• 20:42
  Philip Pape: What I've found is that people are kind of sick of just having more trackers, more tracking apps, right?
• 20:49
  Philip Pape: For training and nutrition, what do we need?
• 20:51
  Philip Pape: Well, we need a way to track our workouts, a way to track our nutrition.
• 20:54
  Philip Pape: And then we probably want to track some other measurements, right?
• 20:58
  Philip Pape: Our weight, our measurements, our photos, things like that, body fat.
• 21:01
  Philip Pape: And most people are tracking with a few of these apps.
• 21:04
  Philip Pape: Some people have app burnout.
• 21:05
  Philip Pape: That's what I find a lot.
• 21:06
  Philip Pape: But even when you're doing all that, you don't have a way to bring it all together unless you have a coach.
• 21:12
  Philip Pape: And we've talked before about human coaching, right?
• 21:14
  Philip Pape: It's expensive, it's hard to get a good coach.
• 21:16
  Philip Pape: It's getting more and more where it's, it's, you know, it's a tough industry, let's just say, for on both sides.
• 21:21
  Philip Pape: Okay.
• 21:22
  Philip Pape: And yet if I said, hey, I just want to use another yet another app, here's another tracker.
• 21:27
  Philip Pape: You're just tracking, tracking, tracking, tracking.
• 21:28
  Philip Pape: Even if you're tracking in a notebook, how are you using that information?
• 21:32
  Philip Pape: Even if you're doing something like starting strength and you're using a notebook and tracking your lifts, do you truly know what decision to make at your next session based on that data?
• 21:40
  Philip Pape: That's what Fitness Lab does.
• 21:43
  Philip Pape: It is not trying to be your tracker, it can definitely track lots of things.
• 21:46
  Philip Pape: It integrates with Apple Health, all that good stuff.
• 21:48
  Philip Pape: We tried to reduce as much friction as possible on that side.
• 21:51
  Philip Pape: But if you still are tracking in other apps like MacroFactor or a workout app, it can work alongside it in a really cool way.
• 21:58
  Philip Pape: And it does what we talked about before.
• 22:00
  Philip Pape: The more data you have, the better it can actually use that data to help you do what you need to do.
• 22:05
  Philip Pape: So, what it does is the four things I talked about.
• 22:07
  Philip Pape: It look at your patterns, it looks at your biofeedback, like sleep and hunger, et cetera, at things like your protein.
• 22:13
  Philip Pape: If you've been feeding it meals, not like a tracker, but more like an analysis tool.
• 22:18
  Philip Pape: Your training, it tells you what's going on.
• 22:20
  Philip Pape: It tells you here's what, here's the pattern, and here's the questions I want to ask you to make sure you do the right thing next so that you don't have to stress about it.
• 22:28
  Philip Pape: So basically gives you daily coaching.
• 22:29
  Philip Pape: It gives you activities each day.
• 22:31
  Philip Pape: It adapts to you.
• 22:32
  Philip Pape: You can talk to it anytime and it can adjust any of those activities based on what you need.
• 22:36
  Philip Pape: If you're like, man, I'm burnt out.
• 22:37
  Philip Pape: I don't want to track, it'll say, okay, let's just limit it to one or two activities a day and we're still going to make progress.
• 22:43
  Philip Pape: All right.
• 22:43
  Philip Pape: Right now, we're running a summer special from June 23rd through Friday, July 3rd.
• 22:48
  Philip Pape: If you're hearing this afterward, I want you to reach out to me.
• 22:52
  Philip Pape: I can probably get you a secret discount.
• 22:54
  Philip Pape: But during the promotion, it's 20% off going to our link witsandweights.com slash app.
• 22:58
  Philip Pape: Go to wits and weights.com slash app.
• 23:01
  Philip Pape: As of this episode dropping, you've got about five days left.
• 23:04
  Philip Pape: And if you've been listening to all of this, you're like, okay, I get it.
• 23:07
  Philip Pape: I need that application layer to do something productive with the data.
• 23:11
  Philip Pape: I don't need more information.
• 23:12
  Philip Pape: I want to lose fat.
• 23:13
  Philip Pape: I want to get rid of that belly fat.
• 23:15
  Philip Pape: I want to know how to train.
• 23:16
  Philip Pape: I want to progressively overload and get stronger.
• 23:19
  Philip Pape: I want to deal with my sleep issues.
• 23:21
  Philip Pape: I want to deal with my food noise.
• 23:23
  Philip Pape: All of that, it's going to help you with that.
• 23:25
  Philip Pape: Go to witsaweeits.com slash app and grab that 20% off discount.
• 23:29
  Philip Pape: I would recommend signing up for the year subscription because you'll save even more doing it that way versus the shorter one.
• 23:35
  Philip Pape: Go to witzawaits.com slash app for fitness lab today.
• 23:40
  Philip Pape: Okay, let's get back to it and talk about okay, how do you use AI?
• 23:45
  Philip Pape: I think the fastest way to fix this is with a few examples, right?
• 23:49
  Philip Pape: A bad use versus good use of AI.
• 23:51
  Philip Pape: So a bad use of AI is opening it up.
• 23:54
  Philip Pape: And again, any AI I'm talking about.
• 23:56
  Philip Pape: Heck, even my own app, if you just ask it this way and you say, like, what's the best workout for a woman over 40?
• 24:02
  Philip Pape: Or weight loss for women in perimenopause is a super common search.
• 24:06
  Philip Pape: Well, you're gonna get a perfectly reasonable, totally generic plan that you will not end up doing.
• 24:11
  Philip Pape: That's that is the honest answer.
• 24:13
  Philip Pape: You'll just see it, you'll say, like, okay, that's nice.
• 24:16
  Philip Pape: Kind of like an article in the newspaper.
• 24:17
  Philip Pape: That's nice.
• 24:18
  Philip Pape: You see this, honey?
• 24:18
  Philip Pape: Okay, moving on.
• 24:19
  Philip Pape: I'm gonna go have my uh oatmeal now.
• 24:21
  Philip Pape: All right, now why aren't you gonna do it?
• 24:23
  Philip Pape: It's because it has nothing to do with you, your lifestyle, your equipment, your dieting history, your particular issues, right?
• 24:30
  Philip Pape: We've we've kind of nailed this or hammered this to death, but you know what I mean.
• 24:34
  Philip Pape: It's an answer to a question that unfortunately has a thousand correct answers, kind of like the infinite universes, the multiverse, right?
• 24:41
  Philip Pape: Spider-Man, the multiverse.
• 24:42
  Philip Pape: Anyone watching Nick Cage and Spider-Noir, awesome show on Prime.
• 24:45
  Philip Pape: Uh, when do I find time to watch TV?
• 24:48
  Philip Pape: I I'm only one episode in.
• 24:50
  Philip Pape: So anyway, it's a thousand permutations of an answer, and it's not going to help you.
• 24:55
  Philip Pape: That's the information fire hose.
• 24:57
  Philip Pape: That's more plan, but no more progress.
• 24:59
  Philip Pape: We don't want that.
• 25:00
  Philip Pape: A good use of that would be pasting in your current program, the one that you're actually running right now.
• 25:06
  Philip Pape: So it could be a screenshot from your workout app.
• 25:08
  Philip Pape: You can type it in, you can take a photo.
• 25:10
  Philip Pape: There's lots of ways depending on what you're using.
• 25:11
  Philip Pape: Like if you use Fitness Lab, you can go into the chat and you could do audio or what you could do video or files or text or whatever.
• 25:19
  Philip Pape: And you say, okay, here are my constraints.
• 25:22
  Philip Pape: I train three days a week.
• 25:23
  Philip Pape: I only have dumbbells.
• 25:24
  Philip Pape: I don't have any micro plates, my knees are cranky.
• 25:27
  Philip Pape: Like, what's the weak link here?
• 25:29
  Philip Pape: That's a great way to question, ask it.
• 25:30
  Philip Pape: Like, what are the blocks?
• 25:31
  Philip Pape: What am I missing here in my plan?
• 25:33
  Philip Pape: I mean, you could say, hey, just give me a better plan, but I love to start from finding the weak spots.
• 25:39
  Philip Pape: Right.
• 25:40
  Philip Pape: So now that helps you learn where the plan doesn't stack up and improve what you're following for the things you just told it are your constraints.
• 25:49
  Philip Pape: And that's super powerful.
• 25:50
  Philip Pape: And you could have all sorts of constraints, right?
• 25:53
  Philip Pape: The days of the week that you can do it, like anything, you know, you hate doing this exercise, whatever.
• 25:57
  Philip Pape: So, do you see the difference between those two?
• 25:59
  Philip Pape: In the first one, you get a generic answer based on information, but the second one is diagnosing you and giving you the blind spots and how to improve.
• 26:08
  Philip Pape: And by the way, you're gonna learn in the process as a human.
• 26:10
  Philip Pape: You're not hopefully not just blindly following it and moving on, but it's like, okay, now I understand why it's working.
• 26:16
  Philip Pape: And again, my app, Fitness Lab, is is kind of cool because it it talks to you like I would, if you will, for better or worse.
• 26:22
  Philip Pape: And it kind of tries to explain it in an accessible way.
• 26:25
  Philip Pape: Here's another, here's another bad example, right?
• 26:27
  Philip Pape: Or bad versus good.
• 26:28
  Philip Pape: You say, is creatine good for women in menopause?
• 26:31
  Philip Pape: I don't know why I keep hammering on the women in menopause, but it's probably because I hear a million questions in about that.
• 26:36
  Philip Pape: So is creatine good, right?
• 26:38
  Philip Pape: And and honestly, that's a question I get, I get that question over Instagram or people had just found the podcast.
• 26:44
  Philip Pape: Hey, is creatine, should I take creatine?
• 26:45
  Philip Pape: I'm like, really?
• 26:46
  Philip Pape: That like that's your question.
• 26:47
  Philip Pape: Sorry, I don't mean to judge people, but like we need to, we need to put more effort into our questions, but I get it, I get it, because maybe you've never heard of creatine you just heard about, you're like, what is this creatine thing?
• 26:57
  Philip Pape: Is it good to do?
• 26:58
  Philip Pape: I would say a good use of AI or asking a question would be, hey, I'm I'm thinking of starting taking creatine.
• 27:05
  Philip Pape: Here's my goal, here's my routine, here's my other supplements, how much do I take, or how do I remember to take it every day, or how do I know it's working?
• 27:14
  Philip Pape: Like there's a lot of ways.
• 27:15
  Philip Pape: I'm not telling you that there's one right way to ask the question, but almost pretend like it's a coach in front of you that you're picking their brain.
• 27:22
  Philip Pape: That's really what you're trying to do.
• 27:23
  Philip Pape: All right.
• 27:24
  Philip Pape: You're not just trying to get a generic fact, you're trying to find out how it's gonna work for you.
• 27:27
  Philip Pape: And again, the more data you give it, the better.
• 27:29
  Philip Pape: I hope this episode isn't going too long, but I do have one more.
• 27:32
  Philip Pape: This is this is for all of us here.
• 27:34
  Philip Pape: Why am I not losing weight?
• 27:36
  Philip Pape: Okay, well, it's an interesting question, right?
• 27:38
  Philip Pape: Because some people say, Why is my metabolism too low?
• 27:40
  Philip Pape: Why am I not losing weight?
• 27:42
  Philip Pape: One of the most common questions.
• 27:43
  Philip Pape: And as a coach, I would say, Well, I need to learn a lot about you right now, based on that.
• 27:47
  Philip Pape: In fact, people sign up for coaching calls with me just to dig in and kind of figure the heck out of this stuff.
• 27:53
  Philip Pape: Because last I counted, there are at least 13 specific reasons for a plateau.
• 27:58
  Philip Pape: And I've built them into like the tools that I create to help people understand where your plateau is coming from.
• 28:03
  Philip Pape: But then even to get to one of those 13 answers, you need like 1300 pieces of information.
• 28:09
  Philip Pape: I'm I'm I'm exaggerating, but you know, you need data indicate data out.
• 28:13
  Philip Pape: So if you just ask the question generically on Google or AI, you're gonna get all a list of all the things.
• 28:18
  Philip Pape: Now you have to go figure out, okay, which of those lists apply to me?
• 28:21
  Philip Pape: Calories, sleep, stress, right?
• 28:22
  Philip Pape: The usual suspects.
• 28:23
  Philip Pape: Or you're gonna get fear-mongering, like, oh, it's your hormones, it's cortisol, right?
• 28:27
  Philip Pape: It menobellies called by cortisol caused by cortisol or something like that.
• 28:30
  Philip Pape: So it's generic, it's useless.
• 28:32
  Philip Pape: And look, you already know a lot of those, don't you?
• 28:35
  Philip Pape: Yeah, I think you do.
• 28:36
  Philip Pape: Or if you listen to the show, you do.
• 28:37
  Philip Pape: Maybe maybe you don't.
• 28:38
  Philip Pape: That's fine.
• 28:38
  Philip Pape: Basic information's cool, it's good education, but it's not gonna help you.
• 28:43
  Philip Pape: A good use of AI for this, if you're not losing weight, is take three weeks in a row of your data.
• 28:50
  Philip Pape: Now you're like, oh crap, I don't actually have data.
• 28:52
  Philip Pape: Well, listen to my podcast for a while, folks, because you're gonna learn how much I love tracking.
• 28:55
  Philip Pape: And if you feel like tracking is a chore, there are easy ways to do it that are low friction.
• 28:59
  Philip Pape: It's a problem we deal with all the time.
• 29:01
  Philip Pape: Okay, but if you don't track, how the heck can you tell what's going on?
• 29:04
  Philip Pape: You've got to track something, right?
• 29:06
  Philip Pape: You've got to track something.
• 29:07
  Philip Pape: So, and maybe this will motivate you to do it.
• 29:09
  Philip Pape: Knowing that you can get an answer may motivate you to do it.
• 29:12
  Philip Pape: So take three weeks of your food log, your training, your weight trend, your biofeedback, like your sleep, and then you paste it all in.
• 29:18
  Philip Pape: Maybe you have lab work too, but I would keep lab work to the side initially unless you really suspect something.
• 29:23
  Philip Pape: And then ask the AI, hey, what patterns do you see?
• 29:27
  Philip Pape: And what would you change first if my goal right now is to lose weight or to lose fat?
• 29:32
  Philip Pape: Okay, and if if you're using Fitness Lab and you ask it, it might even push back and say, hey, we're not trying to lose weight, actually, we're trying to lose body fat.
• 29:38
  Philip Pape: It's gonna, it's gonna mansplain to you, but actually in a general uh gender neutral way, I guess.
• 29:43
  Philip Pape: But I'm joking, kind of.
• 29:45
  Philip Pape: It will then help you understand.
• 29:47
  Philip Pape: Ah, okay, here's the thing that's the most important for you right now.
• 29:50
  Philip Pape: That's pretty cool.
• 29:51
  Philip Pape: That's pretty amazing.
• 29:53
  Philip Pape: Like if you all you have to do is have data, and I get it takes work and effort to track data, but really not that much, guys.
• 29:59
  Philip Pape: Not that much.
• 30:00
  Philip Pape: Okay, just a few things can be very powerful.
• 30:03
  Philip Pape: So the through line on all of these, I've heard the word through line lately.
• 30:06
  Philip Pape: It's like jargon buzzword I hear everywhere.
• 30:09
  Philip Pape: Maybe it's because of AI.
• 30:10
  Philip Pape: I don't know.
• 30:10
  Philip Pape: The through line on all of this is that every good use of AI or a human coach, but we're talking about AI today, starts with you giving it some good data.
• 30:21
  Philip Pape: Your plan, your goals, your data, your constraints, all of that fun stuff.
• 30:25
  Philip Pape: The the incorrect use of AI is without that.
• 30:29
  Philip Pape: It's just asking questions, but not, and it's lazy.
• 30:32
  Philip Pape: It's a lazy use of AI that's gonna give you a lazy answer that's gonna result in you not getting any progress.
• 30:38
  Philip Pape: Okay.
• 30:39
  Philip Pape: So I am I am not saying that AI is useless for fitness.
• 30:43
  Philip Pape: I clearly don't believe that.
• 30:45
  Philip Pape: I built an entire tool around it, Fitness Lab.
• 30:47
  Philip Pape: We talked about it.
• 30:48
  Philip Pape: I'm not saying information doesn't matter.
• 30:50
  Philip Pape: It doesn't, it does.
• 30:51
  Philip Pape: If you are genuinely like at a zero out of 10, you got to learn stuff.
• 30:55
  Philip Pape: You gotta learn the principles.
• 30:56
  Philip Pape: Go ahead and use AI to learn them.
• 30:57
  Philip Pape: That's fine.
• 30:58
  Philip Pape: Be a little bit cautious and careful on where the data is coming from, right?
• 31:01
  Philip Pape: Again, that's where if you had Fitness Lab, you can learn as part of the process.
• 31:05
  Philip Pape: In fact, in Fitness Lab, every day there's a briefing that teaches you something.
• 31:09
  Philip Pape: That's pretty cool.
• 31:10
  Philip Pape: So that helps you level up on your knowledge.
• 31:12
  Philip Pape: I'm not saying you should trust AI blindly.
• 31:14
  Philip Pape: That absolutely you shouldn't, because the tools tend to want to agree with you and like give you a pat on the back and say, like, hey, great thinking there, even when it's terrible thinking, I'm sorry to say.
• 31:26
  Philip Pape: And there is good research showing that they still have a strong tendency to just go along with what you say, even when you're wrong, because they're built to be that way.
• 31:36
  Philip Pape: So they're not a substitute for an actual human coach who's gonna give you, I'll say, tough love, something that you don't want to hear.
• 31:42
  Philip Pape: Now, caveat on that, we're gonna get back to at the end of the episode.
• 31:45
  Philip Pape: Can you train your AI to give you some tough love?
• 31:47
  Philip Pape: Yes, you can.
• 31:48
  Philip Pape: So hold on.
• 31:49
  Philip Pape: I'm also not saying AI replaces a human.
• 31:52
  Philip Pape: I mentioned that 74% improved results when you had the human with the AI.
• 31:56
  Philip Pape: And I get we can't all afford a human or whatnot.
• 32:00
  Philip Pape: So pick the best combination of tools for the job that you could afford that fits within your life.
• 32:04
  Philip Pape: That's what I'm saying, right?
• 32:05
  Philip Pape: The bottleneck for almost everyone is not the information, especially who listens to this podcast.
• 32:10
  Philip Pape: You got the information.
• 32:11
  Philip Pape: It's applying it and doing it consistently.
• 32:14
  Philip Pape: And AI is a phenomenal application tool, but it's like a mediocre information toy.
• 32:21
  Philip Pape: I mean, it's great for information, but what I mean is it's not going to do anything for you just by having the information.
• 32:28
  Philip Pape: All right, before we wrap up, I did promise you a one-line prompt that can train your AI and turn it from a yes man into something that will help you more.
• 32:36
  Philip Pape: I'm gonna give you that in a second.
• 32:38
  Philip Pape: But if if this episode has surfaced all the things you've been thinking about and wondering about AI, and you're like, yeah, now it makes sense that, you know, I've got all this information, I follow so many people, but I don't have the results.
• 32:52
  Philip Pape: That is the gap Fitness Lab was built to close for you.
• 32:56
  Philip Pape: I am so passionate and supportive of what we did here.
• 33:00
  Philip Pape: I think it's a fantastic tool.
• 33:01
  Philip Pape: People are using it, love it, and they keep renewing because it's helping them.
• 33:05
  Philip Pape: Those who actually use it, it's helping them.
• 33:07
  Philip Pape: It is that layer that looks at your data and it coaches you on those patterns and it helps you keep consistent instead of just handing you more information.
• 33:16
  Philip Pape: And again, we have a summer special right now.
• 33:18
  Philip Pape: Go to wits and weights.com slash app, 20% off.
• 33:21
  Philip Pape: When you go to that link, you take a very short two-minute quiz and it gives you what your plan would look like if you decide to use the app and you don't have to then use the app if it's not right for you.
• 33:31
  Philip Pape: So it's a really great zero risk way to check it out.
• 33:33
  Philip Pape: Go to witsandweights.com slash app.
• 33:37
  Philip Pape: Link will be in the show notes.
• 33:39
  Philip Pape: Okay, here's the one-line trick that changes how AI will talk to you.
• 33:44
  Philip Pape: So if you ask AI, hey, is my plan good?
• 33:47
  Philip Pape: Or what do you think of my plan or spot check my plan, it's basically gonna agree with you.
• 33:52
  Philip Pape: It's kind of the default setting.
• 33:54
  Philip Pape: Depending on how you ask it, it might go a little bit deeper than that, but you have to force it out of that.
• 33:58
  Philip Pape: And this is where prompting is very important.
• 34:00
  Philip Pape: Now, in some tools, depending on your account, what you have access to, like Claude or Chap GP or whatever, you can go into your profile, into your settings, and you can give it instructions that it always looks at.
• 34:12
  Philip Pape: In other words, it's like global instructions all the time.
• 34:15
  Philip Pape: And I actually have some of those.
• 34:17
  Philip Pape: But even if you don't use that and you just want to type it right into the chat, what I would do is, you know, paste your data in and then you add, put your question and then put the following act as a skeptical coach.
• 34:30
  Philip Pape: Argue against this plan.
• 34:32
  Philip Pape: Tell me the three things most likely to fail and why.
• 34:37
  Philip Pape: That's it.
• 34:37
  Philip Pape: Now, if you guys want to know what I use in my instructions, I have a very detailed uh set of instructions on like, hey, don't sugarcoat it, don't tell me what I want to hear.
• 34:46
  Philip Pape: I want you to push back.
• 34:47
  Philip Pape: Like, I have all this stuff because I've learned over time how to make it more and more tough on me so it's a more realistic.
• 34:54
  Philip Pape: But just in the chat, do what I just said, go back and listen.
• 34:57
  Philip Pape: I'll repeat it right now, actually.
• 34:59
  Philip Pape: Act as a skeptical coach, argue against this plan, tell me the three things most likely to fail and why.
• 35:05
  Philip Pape: That's it.
• 35:06
  Philip Pape: That instruction turns it from this sycophant, this cheerleader, into a critic, like in a good way.
• 35:14
  Philip Pape: It's gonna give you helpful critique, and that's where the gold is, right?
• 35:18
  Philip Pape: That's where the gold is.
• 35:18
  Philip Pape: That's what you need to hear.
• 35:20
  Philip Pape: Okay.
• 35:20
  Philip Pape: So I hope that was helpful.
• 35:21
  Philip Pape: I hope this whole episode was helpful.
• 35:23
  Philip Pape: I know I pitched my app in there a lot because I truly believe in it and I think it does what we are talking about.
• 35:28
  Philip Pape: It's why I made it.
• 35:30
  Philip Pape: I hope this tool, this episode helped you in even just day-to-day use of AI.
• 35:36
  Philip Pape: And just go forward and conquer and get those results, please.
• 35:39
  Philip Pape: I'm rooting for you.
• 35:40
  Philip Pape: Until next time, keep using your wits, lifting those weights.
• 35:43
  Philip Pape: And remember the answer was never the thing you were missing.
• 35:46
  Philip Pape: The doing is.
• 35:47
  Philip Pape: I'm Philip Pate, and I will talk to you next time here on the Wits and Weights podcast.