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The AI Researcher: From Information Overload to Active Knowledge Synthesis (Part 2)

In this episode, we continue our discussion of the AI-Powered Professional by returning to the AI Researcher persona. Picking up from the prior conversation (episode 149) on information overload and information toxicity, Ray, Augusto, and Francis explore how AI can help professionals move from traditional search toward more collaborative research, synthesis, comparison, and knowledge discovery. They discuss deep research tools, source verification, using multiple AI systems to challenge each other, Google NotebookLM as a grounded research workspace, AI-assisted book reading and writing, proactive information discovery, and the importance of treating AI research outputs as drafts or hypotheses that still require human judgment. (If you’re reading this in a podcast directory/app, please visit https://productivitycast.net/150 for clickable links and the full show notes and transcript of this cast.) Enjoy! Give us feedback! And, thanks for listening! If you'd like to continue discussing The AI Researcher: From Information Overload to Active Knowledge Synthesis (Part 2) from this episode, please click here to leave a comment down below (this jumps you to the bottom of the post). In this Cast | The AI Researcher: From Information Overload to Active Knowledge Synthesis (Part 2) Ray Sidney-Smith Augusto Pinaud Art Gelwicks Francis Wade Show Notes | The AI Researcher: From Information Overload to Active Knowledge Synthesis (Part 2) Resources we mention, including links to them, will be provided here. Please listen to the episode for context. ResearchGate Google Search Google Scholar Academia.edu ChatGPT Claude Google Gemini DeepSeek Google NotebookLM Google Alerts Feedly Feedly Pro Zapier Evernote Evernote AI Raw Text Transcript Raw, unedited and machine-produced text transcript so there may be substantial errors, but you can search for specific points in the episode to jump to, or to reference back to at a later date and time, by keywords or key phrases. The time coding is mm:ss (e.g., 0:04 starts at 4 seconds into the cast’s audio). Read More Voiceover Artist | 00:00 Are you ready to manage your work and personal world better to live a more fulfilling, productive life? Then you've come to the right place. Welcome to ProductivityCast, the weekly show about all things personal productivity. Here are your hosts, Ray Sidney Smith and Augusto Pinault with Frances Wade and Art Gelwix. Ray Sidney Smith | 00:19 Welcome back, everybody, to ProductivityCast, the weekly show about all things personal productivity. I'm Ray Sidney Smith. Augusto Pinaud | 00:25 I am Augusto Pinaud. Francis Wade | 00:26 And I'm Francis Wade. Ray Sidney Smith | 00:28 Welcome, gentlemen, and welcome to our listeners to this continuation of our discussion on the AI-powered professional. In our last conversation, we were really defining the problem around information overload and many of the issues that the modern professional or knowledge worker really deals with as it relates to all of the information. In our lives today. And what we wanted to do in this episode is continue that conversation. And talk through really how to take the sometimes overwhelming amount of information, but the treasure trove of information that we have every day coming into our world and really utilizing it in productive ways. I think that today, Thanks to AI, we no longer need to think about the concept of a search engine. We need to really think about this from the perspective of it being a collaborative engine and there is this kind of reality that it could be considered an answer engine, a research engine, all of these kinds of ways in which we can coin it. There are lots of different use cases today. We're particularly focusing in on the research And these more sophisticated AI tools can now perform tasks previously reserved for a research assistant or for you to take intensive manual effort to produce. And so let's talk through some of the ways in which you're utilizing AI for research purposes. And let's think through perhaps some of the pitfalls that people fall into as they're trying to use AI for research. Francis Wade | 02:12 I've been in a whole different world as a result of deep research in the last year. I remember before It was available. I used to do... Research via looking for documents like ResearchGate, I can search for a PDF using Google. I could search Google Scholar. You could go to academia.edu and What it would give back to me, these different sources, is Stuff that was close to what I was looking for, but not exactly what I was looking for. Matter of fact, it was often not close at all because I would have a specific question. And I'm trying to get a specific question answered. But I have to find somebody who actually answered that question in a document. Or maybe a book or in something. And usually I'd be looking for an academic source. And usually I wouldn't find anything.  So that's just, The game I would play was would be hunt and never find and that was 50%, 75% because I'd be looking for Esoteric stuff. Today, however, I have at my fingertips multiple A few different subscriptions to deep research and chat GPT does it for free up to a particular limit. And I can ask a very specific question. And to my shock, I can receive a plausible reply to my question Right. Pulls from credible sources for the most part. In the beginning, it When it first came out, they would pull from hallucinated sources, which was pain in the neck. But today... They've gotten to the point where They give credible... Specific answers to my very specific questions.  So my research has just multiplied by, it's hard to even compare what it was like No, Versal, what it was like before. Because I do so much of it now. It's really been a game changer.  So that's at the high level. The game is completely different for me right now. See you next year. Ray Sidney Smith | 04:15 And it will be different in a year from now even. More so. As the technology gets better. Francis Wade | 04:21 - I've told people that different parts of my work. Have undergone more change in the last year than in the last decade. 30 years before that, 20 years? And this is certainly one era that is completely different. Augusto Pinaud | 04:37 Sometimes digging and research in a topic and sometimes more than the papers, find the books. What is the book that, okay, I read this book. Now, What other... Go. Into this line and with books go on the opposite line.  Sometimes it's not only The papers, it's the one to give a more... Book rented? What books? Hey, I'm dealing into... And sometimes once I want to deal or work or research into this particular idea, Bye. Where can I find those books? Because you think, okay, I want to get, how do you get granular and now fast? But then now how do you find those book, those authors, who are the authors who I'm researching this, the same areas that I'm research, it doesn't matter if they're agreeing or disagreeing with you, but how you find them, that was a labor Of love. A lot of times, to find those books and to find those authors.  And then after that, then you needed to start Figure out which one was good, which one was bad. That job? One from weeks to hours. And you in hours can get a list that is better than what I was able to produce in months. This gets very interesting, the issue. Who's this? The expectations that now the people have. Because for what you're describing, similar to mine, it's not only get the information, now that just you were able to get to the sources pass through. But the other part of the process is still, you need to still read it, still download them, still digest them, still trying to connect those dots. That is still takes the same amount of time, but then First part, it's fantastic. The issue I see with this is I find a lot of people who think that find the sources is enough. And find the sources is just a step one of X number of steps to be able to get to the next conclusion. Ray Sidney Smith | 06:47 So I think about AI in a research context, when I say this is an AI researcher, Bye. That AI can still hallucinate. I know Francis is a little more, maybe more trusting than I am when it comes to these tools. But I've found ways to revalidate information even after it has pulled research And again, I Preface this always with everything I do with AI, I presume to be a first draft when it puts it out. And so I'm reviewing everything as though an intern handed it to me and it's an intern's work product.  So I need to make sure that it is correct. So we were all on the same page there. I think there are certain areas where AI is really good right now and where it will get better. I think that the deep research functions within all of the major tools that AI chat bots are pretty good right now.  So you have this deep research function in Claude Gemini, and ChatGPT. Personally, I've found that Gemini's does the best. I'm not sure why, but I just feel like it gets the most right when you prompt it correctly. And I don't like the verbosity around the deep research that Google puts out, but it's fine. It gets the data right, which is what I care about most. And that's one piece, which is you have this complex question and you need it to go out there and scour lots of sources and come back to you with an answer. And you don't know what the sources are. And I think in that sense, it can go ahead and find sources and then go ahead and do that analysis and synthesis that is really complex and therefore laborious and make it simpler.  Though Concern I always have with folks is that We're a little too trusting. So I'm going to, again, underscore the point that even after it does this research,...
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The AI Researcher: From Information Overload to Active Knowledge Synthesis (Part 1)

In this episode, we continue our series on the AI-Powered Professional by introducing the AI Researcher persona. Ray, Augusto, and Francis discuss how AI is reshaping research, learning, and knowledge work by moving us beyond simple retrieval toward active knowledge synthesis. Along the way, they explore the problems of information overload, low-quality information, over-trusting AI-generated answers, news and social media overwhelm, and what Ray calls “information toxicity.” The ProductivityCast team also discusses practical ways to curate inbound information, reduce cognitive friction, use AI-generated briefs and drafts responsibly, and stay in control of your attention while working with smarter tools.

(If you’re reading this in a podcast directory/app, please visit https://productivitycast.net/149 for clickable links and the full show notes and transcript of this cast.)

Enjoy! Give us feedback! And, thanks for listening!

If you’d like to continue discussing The AI Researcher: From Information Overload to Active Knowledge Synthesis (Part 1) from this episode, please click here to leave a comment down below (this jumps you to the bottom of the post).

In this Cast | The AI Researcher: From Information Overload to Active Knowledge Synthesis (Part 1)

Ray Sidney-Smith

Augusto Pinaud

Art Gelwicks

Francis Wade

Show Notes | The AI Researcher: From Information Overload to Active Knowledge Synthesis (Part 1)

Resources we mention, including links to them, will be provided here. Please listen to the episode for context.

ResearchGate

Academia.edu

ChatGPT

Google Gemini

Google Workspace

Microsoft Copilot

Feedly

Evernote

Social Fixer

The New York Times

The Onion

Raw Text Transcript

Raw, unedited and machine-produced text transcript so there may be substantial errors, but you can search for specific points in the episode to jump to, or to reference back to at a later date and time, by keywords or key phrases. The time coding is mm:ss (e.g., 0:04 starts at 4 seconds into the cast’s audio).

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Voiceover Artist | 00:00

Are you ready to manage your work and personal world better to live a more fulfilling, productive life? Then you’ve come to the right place. Welcome to ProductivityCast, the weekly show about all things personal productivity. Here are your hosts, Ray Sidney Smith and Augusto Pinault with Francis Wade and Art Gelwick.

Ray Sidney Smith | 00:18

Welcome back, everybody, to Productivity Cast, the weekly show about all things personal productivity. I’m Ray Sidney Smith.

Francis Wade | 00:24

And I’m Francis Wade.

Ray Sidney Smith | 00:25

Welcome, gentlemen, and welcome to our listeners to this episode of ProductivityCast. This week, we are going to be continuing our dive into the world of artificial intelligence, which I like to call smart software, with another episode in our series of the AI-powered professionals. 

So today we’re going to be focusing on research and what I’m coining here is the AI researcher persona and how these new tools are really transforming the process of learning and researching and knowledge work for us. We’re moving to a place where we can understand retrieval as basically active knowledge synthesis. And we’re going to be talking through some of the challenges that folks face with regard to information overload and otherwise. 

So let’s first talk through the problems with research today. What do you find are the good or the positives around research today? And what are some of the problems that we experience? One of them we’re going to talk about, which is information overload. But there are others that are out there. 

And then we can give that context. Color with regard to how we can use AI as a researcher to help us with that process or those problems. 

So what do you feel like are the primary problems today with research.

Francis Wade | 01:47

I think in the past, very much a hit or miss kind of proposition. Where if you could find someone who had done the research… Answer the research questions that you have. You were extremely lucky. And the game was, how can I increase odds of success how can I be luckier So that meant that dwelling in places like Research Gate. Maybe at academia.edu. 

Yeah. But ResearchGate was my goal, though. And For certain topics, especially the two that I specialize in, which are task management and strategic. Planning. I’ve pretty much got to the bottom of everything that I could find easily. It took a few years for each one, but I’ve sort of gotten to what I think is like the bottom. Where I read what they have to say. And I’ve noticed sort of where all the faults are why in neither field the research academics do is very useful in the real world? 

You know, it’s very esoteric and it’s meaningful. Academics tend to write for each other. And for journals. And for advancement in their field. They don’t like to go into areas that are cross bouldery that I like to mix and match different fields. They don’t go interdisciplinary. It makes a real mess of the nice, clean, lines that they like to follow. And I don’t like to go into areas that, you know, If you become an expert in an area where there’s no conferences and no journals, no chairs and no departments anywhere in the world. If you go into an area like that, you know, you’re sort of dooming yourself to obsolescence. 

So with those problems, It means that for the two areas that I’m interested in, there’s a, Not a lot of useful research. There is to find. 

So finding something useful used to be a lucky proposition. And I would have to basically find someone who has enough experience in both areas to be able to do research in both areas so that they would have the questions. And finding that was like a needle in a haystack. 

So it’s always been difficult in the two areas that I Try to find research written on. It’s always been an uphill struggle.

Augusto Pinaud | 04:02

I think it’s important to make an distinction between professional researching practices and the non-professional one. I agree in the professional researching the impact of AI has been incredible because now these people who Say. Knows better when they’re trying to search and look into information. Cinta was not available. When you go to the noun informal research. It’s interesting because I feel that we used to have Three levels of research, bad research, middle ground research, and good research. And now with the AI, we have gone and disappeared that middle because people think that they can find the answer that they believe is legit. Doesn’t matter if it’s true or it’s fake information or what it is. They can go bump into any of these agents. Get an answer. And because of that, people stopped digging. Into is this really legit? But when you think in the world of productivity, When the first book of David Allen came out, we were talking about 2001, It was hard to find the information. It was hard to find the principles behind unless you have access to them. 25 years later, you can find A ton of information. The question now is, How did you know that information is legit or not? And that’s why I think that middle ground has disappeared. You have the people who goes and do a prompt, and get an answer and assume Dad. The answer they’re getting is the truth. And because of that, that’s the stop of the research. 

So what was part of the issues 20 years ago is, okay, I want to research this topic and now I have 20 books. No, they just go, ask two questions, get what they think is a truth answer, and take that That’s a fact. Then you have the other level that is the people who are going to get that and try to figure it out. Is this a fact? They’re going to try to dig out or it’s not a fact. And what is the fact? What is interesting for me with AI is That middle ground, that guy who will have get that fact and tried to see why. I don’t look legit or not legit. That disappeared. What I have seen is people getting the output that AI is giving them I’m taking them. It’s a truth. It’s an absolute truth that is even more scarier. And I have seen this In academic settings, I have seen this in professional settings, okay, where people go What is the obsolescence of this? Okay. Can you repeat that? I didn’t get an answer. 

So when that is, they never really dig. Hold on, did you want to do the vendor? Did you, did the chat GPT was floating you know, That, I mean, how been… Wonderfully. Last week. My son is a baseball fan, so he was watching the baseball and he wanted to see the score, so he asked, Madame Eyre. And But I may say, the game has not started. It was time for the game to start. That’s true. The radio. Fuck. And you know, like, You’ve got me in the life. Damn, man. Give us whatever is for them. I’ve nothing to do. With the reality. And it was a great moment of, teach an opportunity because of that. If we will have the initial answer, what most people do, This other game has no authority. Okay, and you move on. But the reality is minimal. The game had started. We were in the middle of the game and there was a different score than what she was giving us on the third answer. And that is what Most people don’t notice when they go into this research. AI will give you an answer. The question is if that answer is actually the answer or.

Ray Sidney Smith | 08:11

Not. When it really matters, right? Learning that the game is not trivial, maybe not to your son, but to the rest of the world, you know, when it’s… I will.

Augusto Pinaud | 08:19

Make sure to tell him that right thing, that when the game is on, it’s not trivial. You are going down in that scale of people he likes. You’re going down, my friend.

Ray Sidney Smith | 08:27

The unfortunate part is if you say, hey, I just swallowed this thing mineral….

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Ep 35 – Your Strategic Stagnation Isn’t a Framework Problem—It’s a Story Problem

You’re in a strategy retreat. You see an opening to shift the conversation—a strategic insight you know could change the trajectory. You speak up with confidence. And then… blank looks. Awkward silence. The room moves on as if you hadn’t spoken.

It doesn’t matter if you’re the CEO, the board chair, or an ambitious director. The frustration is identical: you have strategic clarity, you know the frameworks, yet your interventions land with a thud while others command the room effortlessly. Most executives diagnose this as needing sharper frameworks or better presentation skills. Wrong problem.

This episode exposes what elite strategists do differently: they’ve built pattern libraries from accumulated case exposure that allow them to deploy diagnostic stories, pattern stories, and origin stories in the moment—not in PowerPoint decks afterward. You’ll discover why Julius Yego’s YouTube-driven Olympic medal validates cognitive science research on tacit knowledge, how Samuel Berger’s “intellectual dark matter” explains the gap between knowing frameworks and commanding strategic conversations, and why the three-season development model transforms in-the-room impact when executive programs don’t.

For global executives who’ve exhausted conventional development paths, this reveals the hidden capability that separates persuasive pattern recognition from forgettable framework recitation—and the deliberate practice method that builds it.

Enjoy the full video of this episode below for all subscribers.

This is a public episode. If you’d like to discuss this with other subscribers or get access to bonus episodes, visit longtermstrategy.substack.com/subscribe

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The AI Assistant: Automating Administrative Friction and “Shadow Work”, Part 2

In this episode, we continue our conversation on The AI Assistant as part of The AI-Powered Professional series. Picking up from Episode 147, the ProductivityCast team shifts from using AI merely to offload administrative friction and shadow work to thinking about AI as a true collaborative assistant. Ray, Augusto, and Francis discuss how to define roles for AI assistants, train them with useful context, manage multiple AI tools and personas, review AI-generated work as drafts, and build prompt workflows that help professionals get better results while staying firmly in control. (If you’re reading this in a podcast directory/app, please visit https://productivitycast.net/148 for clickable links and the full show notes and transcript of this cast.) Enjoy! Give us feedback! And, thanks for listening! If you'd like to continue discussing The AI Assistant: Automating Administrative Friction and “Shadow Work”, Part 2 from this episode, please click here to leave a comment down below (this jumps you to the bottom of the post). In this Cast | The AI Assistant: Automating Administrative Friction and “Shadow Work”, Part 2 Ray Sidney-Smith Augusto Pinaud Francis Wade Show Notes | The AI Assistant: Automating Administrative Friction and “Shadow Work”, Part 2 Resources we mention, including links to them, will be provided here. Please listen to the episode for context. Microsoft Copilot Google Gemini Google NotebookLM ChatGPT Claude Evernote Zapier Raw Text Transcript Raw, unedited and machine-produced text transcript so there may be substantial errors, but you can search for specific points in the episode to jump to, or to reference back to at a later date and time, by keywords or key phrases. The time coding is mm:ss (e.g., 0:04 starts at 4 seconds into the cast’s audio). Read More [00:00:00] Are you ready to manage your work and personal world better to live a more fulfilling, productive life? Then you've come to the right place. Welcome to ProductivityCast, the weekly show about all things personal productivity. Here are your hosts, Ray Sidney-Smith and Augusto Pinaud, with Francis Wade and Art Gelwicks. [00:00:18] Welcome back, everybody, to ProductivityCast, the weekly show about all things personal productivity. I'm Ray Sidney-Smith. Marco is jumping out. And I'm Francis Wade. Welcome, gentlemen, and welcome to our listeners to today's episode, where we're gonna continue our discussion on AI, and this is our series on the AI-powered professional. [00:00:44] in our first episode, we started the discussion about the concept of utilizing generative AI. in this episode, we also started the process of talking about what an AI assistant is really [00:01:00] like, talking about some of those administrative frictions, being able to get rid of, and automate that out of, your world to some extent, and dealing with shadow work as well, defining shadow work and so on and so forth. [00:01:13] We're gonna continue this topic into discussing today about really how to partner with your AI in a lot of ways, what the collaboration process really looks like. And so I'd like for us to discuss shifting using AI tools as a mechanism of just kind of offloading something, which it can do, but then becoming a more collaborative partner with that particular AI tool in order for it to become a true AI assistant. [00:01:45] And so I'm thinking of things like how do we ensure that AI is taking over the right kind of work and that it's not taking over the work that we should be doing, and how do we maintain control and accuracy? And of [00:02:00] course, there are a bunch of boundaries and ethical considerations that we should be thinking about and some thoughts about the future. [00:02:05] So let's start with what are some of those first principles, for us to be able to create a true collaboration partnership with our AI assistant? [00:02:19] Sure. I'm thinking about this from the perspective that If I want to work with my AI assistant, I need to choose particular categories of work in which it can actually collaborate. So for example, I want it to be able to help me take a rough sketch that I've made on either my iPad or on paper, and then to have the AI turn that into a full-fledged drawing, a full-fledged cartoon perhaps. [00:02:49] So the AI assistant is acting as my cartoonist, and so that's a role that I want the AI assistant to do. And while I can draw my [00:03:00] own cartoons, 'cause I've taken this drawing class, I feel competent to draw, you know, one part of a cartoon, but then it can fill in the rest by creating the other panels of the cartoon. [00:03:13] And this is really helpful to me because now I can make the first drawing. It can be roughish, you know, to give it the idea of what I want, and now I can help it help me, quickly generate more panels and get the cartoon done by virtue of that. But the idea is that it's now a role that I want it to continually be helping me with, and so that is the cartoonist role. [00:03:38] That's just one. I mean, like that, it doesn't, it doesn't have to be just role. It could be any number of things. But it's just like, that's the kind of thing that I'm thinking about. well, in the last episode, we sort of established the notion that, an AI assistant is like an intern who remembers everything, but doesn't have a whole lot of judgment. [00:03:56] isn't, a really good judge of, you know, the [00:04:00] things, whatever it is that we happen to be expert at. It, it's too much to ask the AI to rise to our level of, insight and understanding. Having said that, there's a whole bunch of stuff that now looks to me that, it looks different to me because I can now see it as automatable. [00:04:23] Like the example that you gave of, doing repetitive drawings or repetitive, animation. There's a bunch of things that I, and the list keeps growing, which is why I don't have a fixed answer. but it does start with this notion that I have an untrained intern that has infinite memory and infinite patience and doesn't have an attitude and works at all hours. [00:04:48] And if I train that intern, then there's more and more things that the intern can do, and there's gonna be a new app tomorrow that- allows the intern to [00:05:00] do even more. So it's hard to say what specific role because the roles keep changing, and they keep being added to. if anything, I would say there's maybe a rule, which is that, try to give the intern as much as possible, but always be the person of last kind of decision. [00:05:20] Be the one who's at the end checking to make sure the intern didn't make some, you know, gross error. So if there's any rule, that's the rule that I'm applying right now. Try to find more and more to give and then be the person at the end to do the checking. and then don't try to stress the intern out with judgment calls. [00:05:42] and even the limit-- even the line on what I call a judgment call is changing with AI because it's getting better, You know, the AIs that I use, I use memory, so it understands me and what my judgment calls are, better and better each day. So it's a tough question to answer.[00:06:00]  [00:06:00] So just stepping up a level, I would say that just the concept of establishing roles for the AI is the first principle. It's not necessarily that you're going to ever be exhaustive in terms of creating the roles, because sometimes the role you need for a specific chat is defined in only that chat, and then there will be ones where you're gonna need that as an ongoing kind of recurring thing. [00:06:29] It depends. You know, last episode I was talking about that wine help. You know, help me identify wine that I may enjoy based on my profile and educated that profile. But same thing on, on the professional side. I have a client who we, because of what they do, they, it's a report that is run every morning, and that report gets to them. [00:06:53] And the problem is it's impossible to, to analyze it long enough. You know, you can see the report daily. You can maybe go a [00:07:00] couple days back. But human, it's hard to really create trends and things from that specific report. Where it's been very cool is a play on the role we create a chat for that neural network, okay? [00:07:15] And now that report is dumped, for lack of a better word, into this chat. But this has now allowed us to identify trends not in three months, not in 90 days. Hey, this server last time this failed, okay, it was seven months ago. And it failed for three days. That information no human can provide for me. Okay? [00:07:38] But allows you to start seeing that, and that make it very, very specific. Okay? Same thing, when you write. After you train, yeah, it required to train the intern, but after you train, say, "Okay, this sound like me. This doesn't sound like me." You know, one of the things that I love to do is when I get an [00:08:00] idea, okay, let me discuss this idea with the content of, okay, or the ideas or the understanding that AI has of X person. [00:08:08] And you can say, "Hey, I want to look what will be the perspective of this text if Einstein read it." assuming you, you know what, physics and stuff. But that give you... Is the perspective you're going to get accurate? Well, it may be, it may not. But it will give you a counter that is very interesting. [00:08:30] One thing that I do very often is find the arguments in favor and against this i- this concept, this idea that I'm working on. And it now get... You know, I think the definition, part of the definition or the issue is this, for a lot of people, is the first time they get access to an assistant, to an administrative assistant,  [00:08:53] For most people, that is a concept that they heard, that they, you know,...
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The Two Meetings That Turn Long-Term Strategy Into Motion

Most top executives can generate urgency around a quarterly target. The mechanisms are familiar: dashboards, deadlines, compensation levers. People move.

But ask those same executives to build genuine momentum toward a grand aspiration which needs a fifteen-year horizon, and something strange happens. They show up. They nod. They wait for the pressure to pass.

This isn’t insubordination. It’s a rational response to a broken process. And if you’ve ever led a strategic planning cycle that produced a polished document nobody touched again, you already know the symptom. The question is whether you’ve correctly diagnosed the cause.

The Real Problem Is Sequence, Not Ambition

CEOs who struggle to activate major aspirations or breakthrough results typically frame it as a people problem — their teams aren’t bold enough, disciplined enough, or strategically literate enough. Frequently, they apply pressure to fix the problem and become too directive. They hope their personal energy fills the void.

Perhaps just as often, they do the opposite and become too passive. In this mode they back off, hoping organic energy fills the void. It rarely does.

Neither framing is quite right. In the end, CEO’s migrate towards short-term goals because they don’t have a reliable way to maintain both short-, mid-, and long-term momentum.

The deeper issue is that most organizations try to do too much in a single planning meeting.

Effective accomplishment of all three phases at the same time requires two distinct meetings, held weeks apart, each demanding a different posture from the leader. Getting the sequence right changes what the plan is, who owns it, and how fast it can move.

Clarifying Misconceptions About Long Horizons

Before the two meetings make sense, two widespread beliefs need to be addressed:

the first is that long-range planning is inherently vague, and therefore not worth taking seriously.

Mistake 1) This is a problem for CEOs who truly have big aspirations, because long-range planning calls for the decades needed to make breakthrough goals realistic and credible to stakeholders. Without adequate time, executives play the game mentioned before. They show up, nod, and wait for the pressure to disappear.

This view of long-range planning being vague is understandable but technically wrong.

The planning tools appropriate for year one of a strategy are genuinely different from those suited to year twenty-five — but that doesn’t mean the far end of the horizon is a guess. It just needs to be equipped in the right way.

For example, the Rolling Wave Technique leads to the use of different methods, mindsets and discussions for short- and long-term phases. It provides operational details in the short term, and higher-altitude targets and milestones in the long term.

Neither end is more rigorous than the other. They are rigorous in different ways. The confusion exists because precious few use the technique. It’s just not taught in most business schools as a component of corporate strategy.

Mistake 2) The second faulty belief is that long-term aspirations don’t matter. To explain why this is so wrong, consider a historical example.

Medieval cathedral builders routinely committed to projects spanning two to three centuries. No individual craftsman who broke ground would see the finished nave. Yet construction continued across generations, through plagues and political upheaval, because the aspiration was large enough to give the work meaning — and specific enough to give it credible direction. Floor plans existed. Proportions were specified. Progress was measurable even when the endpoint was a lifetime away.

This points to a counterintuitive truth: the grander the ambition, the more likely it is to unlock discretionary effort — the creativity and energy people typically reserve for pursuits they actually care about.

Modest, short-term goals produce compliance. In corporate life, these tend to be overwhelmingly financial.

Transformative goals, properly constructed, produce ownership. The audacity of a well-chosen endpoint is itself a management tool, one that most corporations never pick up.

With these misconceptions cleared up, here are the details of both meetings and how they are conducted.

Meeting One: The CEO Goes Quiet

The first meeting has one non-negotiable design principle: the CEO sponsors but does not lead. Or facilitate.

This is harder than it sounds. Most executives who have reached the top of an organization have done so partly through the force of their vision. They arrive at planning sessions having already formed views about where the company should go. The instinct is to share those views early — to inspire the team with a compelling picture of the future and let the session fill in the details.

Resist it. Completely.

The goals of this first meeting are for the executive team to construct the long-range aspiration themselves and define the means to accomplish it. That means choosing a target year — somewhere between fifteen and thirty years out — and then building the assumptions, scenarios, and numbers required to define what success looks like at that point.

It’s followed by the use of the Rolling Wave Technique to lay out a plan for the entire horizon, with more details in closer than later years.

Facilitators can guide the process. The CEO’s role is to hold the space while that process unfolds, tolerating the discomfort of an outcome they did not pre-select and cannot entirely predict.

What makes this worthwhile is what it produces: genuine co-ownership. Every figure the team debated, they will later defend. Every scenario they stress-tested, they trust because they built it. A strategic target and plan defined by the CEO and handed to the team is a document. A strategy the team constructed is a commitment — and the difference shows up in execution, not in the planning room.

For example, one team member assumes a technology shift in five years. Another assumes fifteen. Both assumptions are driving their instincts about investment and timing, silently, in every meeting they attend. Naming those beliefs, debating them, and converting them into dated claims is one of the most underrated outputs of a well-run long-range planning session. It also reveals where the team’s consensus is genuine and where it is merely polite.

Meeting Two: The CEO Becomes an Instigator

Several weeks after the first meeting — long enough for the plan to feel real, not so long that momentum fades — the CEO calls a second session. It has a single agenda item, framed as a question:

“Using the same logic we built together, how much faster could we realistically get there?”

The phrasing matters more than it might appear. This is not a demand for “twice the output in half the time” — the kind of arbitrary stretch target that produces creative accounting and quiet cynicism. It is an invitation to apply the team’s own reasoning to a compression problem. They set the destination and the pathway. Now they are being asked whether the chosen route is as efficient as it could be.

And because the team built the original logic, they are the only people positioned to answer the question credibly. They know which assumptions were conservative. They know where interdependencies between units create natural leverage — and where they create drag. They know which technologies on the industry’s horizon could compress a transition the plan assumed would take a decade. They know where the plan padded timelines because of organizational inertia rather than genuine constraint.

That collective intelligence almost never gets activated, because the question that unlocks it is almost never asked. Unfortunately, leaders tend to apply pressure before the team has built the logic, which means compression becomes a negotiation rather than an analysis. The two-meeting sequence reverses that order — and the difference in what the team produces is striking.

The best version of this second meeting doesn’t only produce a revised plan. It produces a set of credible acceleration options: specific conditions under which the timeline compresses, specific investments or decisions that could trigger those conditions, and an honest accounting of what would have to be true for the faster scenario to hold. The team leaves not just aligned, but strategically fluent in a way that one-off retreats almost never achieve.

Case in point: Before 2017, one of my clients in the Jamaican financial sector had never put a date to an assumption: “the average local customer is not ready for online services.”

When I challenged them to place a date on the moment when 50% of the population would reach that threshold, they predicted: 2028. They wove that date into their plan.

Three years later when the COVID-19 pandemic arrived, that plan was simply accelerated (i.e. compressed) to be implemented within months rather than a decade. They were lucky.

The Resilience Dividend

There is a benefit to this process that rarely appears in planning frameworks: the organization becomes significantly harder to surprise.

An executive team that has jointly built a long-range plan, surfaced its embedded assumptions, dated them, stress-tested scenarios, and explored acceleration options has essentially pre-thought a wide range of futures.

When the external environment forces their hand — a market disruption, a technology shift, a crisis that compresses years into months — they are not improvising. They are activating a version of something they already worked through. The decisions feel fast because they had already built the internal logic needed to respond.

This is not a theoretical benefit. Organizations routinely discover, under pressure, that their plans contained a faster path they simply hadn’t chosen to pursue yet. The companies best positioned to accelerate in a crisis are the ones that already knew, in principle, how acceleration was possible — because they had asked themselves exactly that question before one was forced on them.

The slow work of building shared logic, it turns out, is what makes rapid response possible. Resilience isn’t built in the crisis. It’s built in the room, in the meeting before the meeting, when the CEO is quiet enough to let the team think.

Why This Rarely Happens — and What to Do About It

The reason most aspirations which require long-term strategies end up stalling is that the people accountable for executing them never felt genuinely accountable for creating them. The CEO’s vision, however compelling, remains the CEO’s vision. Rollout becomes performance. Compliance replaces conviction. And when conditions change, there is no one in the room who feels responsible for updating the logic — because the logic was never theirs.

The two-meeting structure addresses this not through a motivational technique but through a structural one. Ownership is built in at the design stage. The compression question in the second meeting then activates that ownership, rather than challenging it.

The process asks something genuinely difficult of the CEO: to be quiet and patient at the moment when they most want to speak, and to ask a question — rather than issue an instruction — at the moment when they most want to apply pressure. Both moves feel counterintuitive. Both, consistently, work.

Begin with the meeting where you say less than you ever have before. What comes next will surprise you.

Use These LLM Prompts to Apply This Framework

Copy any of the following into an AI assistant to put the ideas in this article to work for your organization.

  1. Pressure-test your current strategy “Here is our current strategic plan: [paste or summarize]. Using the Rolling Wave principle from the article I just read, identify where our plan conflates short-, mid-, and long-term planning into a single approach. What assumptions are we treating as facts? Which ones should have a specific date attached to them?”
  2. Prepare for Meeting One “I am a CEO preparing to run a long-range planning session where my role is to facilitate, not lead. Our industry is [X]. Help me design a 3-hour agenda that guides my executive team to construct a 20-year aspiration themselves, without me imposing a conclusion. Include the questions I should ask — and the ones I should resist asking.”
  3. Surface your team’s hidden assumptions “Here are the key assumptions embedded in our strategy: [list them]. For each one, challenge me to convert it from an open-ended belief into a dated, falsifiable claim. Then identify which assumptions, if wrong, would most significantly change our direction or timeline.”
  4. Run the compression question “Here is a summary of our long-range plan: [paste summary]. Assume the logic is sound. Now help me identify: which parts of this plan are paced by genuine external constraints, and which are paced by internal inertia or conservative thinking? Where could the timeline realistically compress — and what would have to be true for that to happen?”
  5. Build your resilience map “Based on the strategic plan below [paste], identify the three to five external disruptions — technology shifts, market changes, regulatory moves — most likely to force an acceleration of our timeline. For each, describe what an already-prepared organization would do in the first 90 days, versus one that had never considered the scenario.”
Posted on

The Two Meetings That Turn Long-Term Strategy Into Motion

Most top executives can generate urgency around a quarterly target. The mechanisms are familiar: dashboards, deadlines, compensation levers. People move.

But ask those same executives to build genuine momentum toward a grand aspiration which needs a fifteen-year horizon, and something strange happens. They show up. They nod. They wait for the pressure to pass.

This isn’t insubordination. It’s a rational response to a broken process. And if you’ve ever led a strategic planning cycle that produced a polished document nobody touched again, you already know the symptom. The question is whether you’ve correctly diagnosed the cause.

The Real Problem Is Sequence, Not Ambition

CEOs who struggle to activate major aspirations or breakthrough results typically frame it as a people problem — their teams aren’t bold enough, disciplined enough, or strategically literate enough. Frequently, they apply pressure to fix the problem and become too directive. They hope their personal energy fills the void.

Perhaps just as often, they do the opposite and become too passive. In this mode they back off, hoping organic energy fills the void. It rarely does.

Neither framing is quite right. In the end, CEO’s migrate towards short-term goals because they don’t have a reliable way to maintain both short-, mid-, and long-term momentum.

The deeper issue is that most organizations try to do too much in a single planning meeting.

Effective accomplishment of all three phases at the same time requires two distinct meetings, held weeks apart, each demanding a different posture from the leader. Getting the sequence right changes what the plan is, who owns it, and how fast it can move.

Clarifying Misconceptions About Long Horizons

Before the two meetings make sense, two widespread beliefs need to be addressed:

the first is that long-range planning is inherently vague, and therefore not worth taking seriously.

Mistake 1) This is a problem for CEOs who truly have big aspirations, because long-range planning calls for the decades needed to make breakthrough goals realistic and credible to stakeholders. Without adequate time, executives play the game mentioned before. They show up, nod, and wait for the pressure to disappear.

This view of long-range planning being vague is understandable but technically wrong.

The planning tools appropriate for year one of a strategy are genuinely different from those suited to year twenty-five — but that doesn’t mean the far end of the horizon is a guess. It just needs to be equipped in the right way.

For example, the Rolling Wave Technique leads to the use of different methods, mindsets and discussions for short- and long-term phases. It provides operational details in the short term, and higher-altitude targets and milestones in the long term.

Neither end is more rigorous than the other. They are rigorous in different ways. The confusion exists because precious few use the technique. It’s just not taught in most business schools as a component of corporate strategy.

Mistake 2) The second faulty belief is that long-term aspirations don’t matter. To explain why this is so wrong, consider a historical example.

Medieval cathedral builders routinely committed to projects spanning two to three centuries. No individual craftsman who broke ground would see the finished nave. Yet construction continued across generations, through plagues and political upheaval, because the aspiration was large enough to give the work meaning — and specific enough to give it credible direction. Floor plans existed. Proportions were specified. Progress was measurable even when the endpoint was a lifetime away.

This points to a counterintuitive truth: the grander the ambition, the more likely it is to unlock discretionary effort — the creativity and energy people typically reserve for pursuits they actually care about.

Modest, short-term goals produce compliance. In corporate life, these tend to be overwhelmingly financial.

Transformative goals, properly constructed, produce ownership. The audacity of a well-chosen endpoint is itself a management tool, one that most corporations never pick up.

With these misconceptions cleared up, here are the details of both meetings and how they are conducted.

Meeting One: The CEO Goes Quiet

The first meeting has one non-negotiable design principle: the CEO sponsors but does not lead. Or facilitate.

This is harder than it sounds. Most executives who have reached the top of an organization have done so partly through the force of their vision. They arrive at planning sessions having already formed views about where the company should go. The instinct is to share those views early — to inspire the team with a compelling picture of the future and let the session fill in the details.

Resist it. Completely.

The goals of this first meeting are for the executive team to construct the long-range aspiration themselves and define the means to accomplish it. That means choosing a target year — somewhere between fifteen and thirty years out — and then building the assumptions, scenarios, and numbers required to define what success looks like at that point.

It’s followed by the use of the Rolling Wave Technique to lay out a plan for the entire horizon, with more details in closer than later years.

Facilitators can guide the process. The CEO’s role is to hold the space while that process unfolds, tolerating the discomfort of an outcome they did not pre-select and cannot entirely predict.

What makes this worthwhile is what it produces: genuine co-ownership. Every figure the team debated, they will later defend. Every scenario they stress-tested, they trust because they built it. A strategic target and plan defined by the CEO and handed to the team is a document. A strategy the team constructed is a commitment — and the difference shows up in execution, not in the planning room.

For example, one team member assumes a technology shift in five years. Another assumes fifteen. Both assumptions are driving their instincts about investment and timing, silently, in every meeting they attend. Naming those beliefs, debating them, and converting them into dated claims is one of the most underrated outputs of a well-run long-range planning session. It also reveals where the team’s consensus is genuine and where it is merely polite.

Meeting Two: The CEO Becomes an Instigator

Several weeks after the first meeting — long enough for the plan to feel real, not so long that momentum fades — the CEO calls a second session. It has a single agenda item, framed as a question:

“Using the same logic we built together, how much faster could we realistically get there?”

The phrasing matters more than it might appear. This is not a demand for “twice the output in half the time” — the kind of arbitrary stretch target that produces creative accounting and quiet cynicism. It is an invitation to apply the team’s own reasoning to a compression problem. They set the destination and the pathway. Now they are being asked whether the chosen route is as efficient as it could be.

And because the team built the original logic, they are the only people positioned to answer the question credibly. They know which assumptions were conservative. They know where interdependencies between units create natural leverage — and where they create drag. They know which technologies on the industry’s horizon could compress a transition the plan assumed would take a decade. They know where the plan padded timelines because of organizational inertia rather than genuine constraint.

That collective intelligence almost never gets activated, because the question that unlocks it is almost never asked. Unfortunately, leaders tend to apply pressure before the team has built the logic, which means compression becomes a negotiation rather than an analysis. The two-meeting sequence reverses that order — and the difference in what the team produces is striking.

The best version of this second meeting doesn’t only produce a revised plan. It produces a set of credible acceleration options: specific conditions under which the timeline compresses, specific investments or decisions that could trigger those conditions, and an honest accounting of what would have to be true for the faster scenario to hold. The team leaves not just aligned, but strategically fluent in a way that one-off retreats almost never achieve.

Case in point: Before 2017, one of my clients in the Jamaican financial sector had never put a date to an assumption: “the average local customer is not ready for online services.”

When I challenged them to place a date on the moment when 50% of the population would reach that threshold, they predicted: 2028. They wove that date into their plan.

Three years later when the COVID-19 pandemic arrived, that plan was simply accelerated (i.e. compressed) to be implemented within months rather than a decade. They were lucky.

The Resilience Dividend

There is a benefit to this process that rarely appears in planning frameworks: the organization becomes significantly harder to surprise.

An executive team that has jointly built a long-range plan, surfaced its embedded assumptions, dated them, stress-tested scenarios, and explored acceleration options has essentially pre-thought a wide range of futures.

When the external environment forces their hand — a market disruption, a technology shift, a crisis that compresses years into months — they are not improvising. They are activating a version of something they already worked through. The decisions feel fast because they had already built the internal logic needed to respond.

This is not a theoretical benefit. Organizations routinely discover, under pressure, that their plans contained a faster path they simply hadn’t chosen to pursue yet. The companies best positioned to accelerate in a crisis are the ones that already knew, in principle, how acceleration was possible — because they had asked themselves exactly that question before one was forced on them.

The slow work of building shared logic, it turns out, is what makes rapid response possible. Resilience isn’t built in the crisis. It’s built in the room, in the meeting before the meeting, when the CEO is quiet enough to let the team think.

Why This Rarely Happens — and What to Do About It

The reason most aspirations which require long-term strategies end up stalling is that the people accountable for executing them never felt genuinely accountable for creating them. The CEO’s vision, however compelling, remains the CEO’s vision. Rollout becomes performance. Compliance replaces conviction. And when conditions change, there is no one in the room who feels responsible for updating the logic — because the logic was never theirs.

The two-meeting structure addresses this not through a motivational technique but through a structural one. Ownership is built in at the design stage. The compression question in the second meeting then activates that ownership, rather than challenging it.

The process asks something genuinely difficult of the CEO: to be quiet and patient at the moment when they most want to speak, and to ask a question — rather than issue an instruction — at the moment when they most want to apply pressure. Both moves feel counterintuitive. Both, consistently, work.

Begin with the meeting where you say less than you ever have before. What comes next will surprise you.

Use These LLM Prompts to Apply This Framework

Copy any of the following into an AI assistant to put the ideas in this article to work for your organization.

  1. Pressure-test your current strategy “Here is our current strategic plan: [paste or summarize]. Using the Rolling Wave principle from the article I just read, identify where our plan conflates short-, mid-, and long-term planning into a single approach. What assumptions are we treating as facts? Which ones should have a specific date attached to them?”
  2. Prepare for Meeting One “I am a CEO preparing to run a long-range planning session where my role is to facilitate, not lead. Our industry is [X]. Help me design a 3-hour agenda that guides my executive team to construct a 20-year aspiration themselves, without me imposing a conclusion. Include the questions I should ask — and the ones I should resist asking.”
  3. Surface your team’s hidden assumptions “Here are the key assumptions embedded in our strategy: [list them]. For each one, challenge me to convert it from an open-ended belief into a dated, falsifiable claim. Then identify which assumptions, if wrong, would most significantly change our direction or timeline.”
  4. Run the compression question “Here is a summary of our long-range plan: [paste summary]. Assume the logic is sound. Now help me identify: which parts of this plan are paced by genuine external constraints, and which are paced by internal inertia or conservative thinking? Where could the timeline realistically compress — and what would have to be true for that to happen?”
  5. Build your resilience map “Based on the strategic plan below [paste], identify the three to five external disruptions — technology shifts, market changes, regulatory moves — most likely to force an acceleration of our timeline. For each, describe what an already-prepared organization would do in the first 90 days, versus one that had never considered the scenario.”
Posted on

The Two Meetings That Turn Long-Term Strategy Into Motion

Most top executives can generate urgency around a quarterly target. The mechanisms are familiar: dashboards, deadlines, compensation levers. People move.

But ask those same executives to build genuine momentum toward a grand aspiration which needs a fifteen-year horizon, and something strange happens. They show up. They nod. They wait for the pressure to pass.

This isn’t insubordination. It’s a rational response to a broken process. And if you’ve ever led a strategic planning cycle that produced a polished document nobody touched again, you already know the symptom. The question is whether you’ve correctly diagnosed the cause.

The Real Problem Is Sequence, Not Ambition

CEOs who struggle to activate major aspirations or breakthrough results typically frame it as a people problem — their teams aren’t bold enough, disciplined enough, or strategically literate enough. Frequently, they apply pressure to fix the problem and become too directive. They hope their personal energy fills the void.

Perhaps just as often, they do the opposite and become too passive. In this mode they back off, hoping organic energy fills the void. It rarely does.

Neither framing is quite right. In the end, CEO’s migrate towards short-term goals because they don’t have a reliable way to maintain both short-, mid-, and long-term momentum.

The deeper issue is that most organizations try to do too much in a single planning meeting.

Effective accomplishment of all three phases at the same time requires two distinct meetings, held weeks apart, each demanding a different posture from the leader. Getting the sequence right changes what the plan is, who owns it, and how fast it can move.

Clarifying Misconceptions About Long Horizons

Before the two meetings make sense, two widespread beliefs need to be addressed:

the first is that long-range planning is inherently vague, and therefore not worth taking seriously.

Mistake 1) This is a problem for CEOs who truly have big aspirations, because long-range planning calls for the decades needed to make breakthrough goals realistic and credible to stakeholders. Without adequate time, executives play the game mentioned before. They show up, nod, and wait for the pressure to disappear.

This view of long-range planning being vague is understandable but technically wrong.

The planning tools appropriate for year one of a strategy are genuinely different from those suited to year twenty-five — but that doesn’t mean the far end of the horizon is a guess. It just needs to be equipped in the right way.

For example, the Rolling Wave Technique leads to the use of different methods, mindsets and discussions for short- and long-term phases. It provides operational details in the short term, and higher-altitude targets and milestones in the long term.

Neither end is more rigorous than the other. They are rigorous in different ways. The confusion exists because precious few use the technique. It’s just not taught in most business schools as a component of corporate strategy.

Mistake 2) The second faulty belief is that long-term aspirations don’t matter. To explain why this is so wrong, consider a historical example.

Medieval cathedral builders routinely committed to projects spanning two to three centuries. No individual craftsman who broke ground would see the finished nave. Yet construction continued across generations, through plagues and political upheaval, because the aspiration was large enough to give the work meaning — and specific enough to give it credible direction. Floor plans existed. Proportions were specified. Progress was measurable even when the endpoint was a lifetime away.

This points to a counterintuitive truth: the grander the ambition, the more likely it is to unlock discretionary effort — the creativity and energy people typically reserve for pursuits they actually care about.

Modest, short-term goals produce compliance. In corporate life, these tend to be overwhelmingly financial.

Transformative goals, properly constructed, produce ownership. The audacity of a well-chosen endpoint is itself a management tool, one that most corporations never pick up.

With these misconceptions cleared up, here are the details of both meetings and how they are conducted.

Meeting One: The CEO Goes Quiet

The first meeting has one non-negotiable design principle: the CEO sponsors but does not lead. Or facilitate.

This is harder than it sounds. Most executives who have reached the top of an organization have done so partly through the force of their vision. They arrive at planning sessions having already formed views about where the company should go. The instinct is to share those views early — to inspire the team with a compelling picture of the future and let the session fill in the details.

Resist it. Completely.

The goals of this first meeting are for the executive team to construct the long-range aspiration themselves and define the means to accomplish it. That means choosing a target year — somewhere between fifteen and thirty years out — and then building the assumptions, scenarios, and numbers required to define what success looks like at that point.

It’s followed by the use of the Rolling Wave Technique to lay out a plan for the entire horizon, with more details in closer than later years.

Facilitators can guide the process. The CEO’s role is to hold the space while that process unfolds, tolerating the discomfort of an outcome they did not pre-select and cannot entirely predict.

What makes this worthwhile is what it produces: genuine co-ownership. Every figure the team debated, they will later defend. Every scenario they stress-tested, they trust because they built it. A strategic target and plan defined by the CEO and handed to the team is a document. A strategy the team constructed is a commitment — and the difference shows up in execution, not in the planning room.

For example, one team member assumes a technology shift in five years. Another assumes fifteen. Both assumptions are driving their instincts about investment and timing, silently, in every meeting they attend. Naming those beliefs, debating them, and converting them into dated claims is one of the most underrated outputs of a well-run long-range planning session. It also reveals where the team’s consensus is genuine and where it is merely polite.

Meeting Two: The CEO Becomes an Instigator

Several weeks after the first meeting — long enough for the plan to feel real, not so long that momentum fades — the CEO calls a second session. It has a single agenda item, framed as a question:

“Using the same logic we built together, how much faster could we realistically get there?”

The phrasing matters more than it might appear. This is not a demand for “twice the output in half the time” — the kind of arbitrary stretch target that produces creative accounting and quiet cynicism. It is an invitation to apply the team’s own reasoning to a compression problem. They set the destination and the pathway. Now they are being asked whether the chosen route is as efficient as it could be.

And because the team built the original logic, they are the only people positioned to answer the question credibly. They know which assumptions were conservative. They know where interdependencies between units create natural leverage — and where they create drag. They know which technologies on the industry’s horizon could compress a transition the plan assumed would take a decade. They know where the plan padded timelines because of organizational inertia rather than genuine constraint.

That collective intelligence almost never gets activated, because the question that unlocks it is almost never asked. Unfortunately, leaders tend to apply pressure before the team has built the logic, which means compression becomes a negotiation rather than an analysis. The two-meeting sequence reverses that order — and the difference in what the team produces is striking.

The best version of this second meeting doesn’t only produce a revised plan. It produces a set of credible acceleration options: specific conditions under which the timeline compresses, specific investments or decisions that could trigger those conditions, and an honest accounting of what would have to be true for the faster scenario to hold. The team leaves not just aligned, but strategically fluent in a way that one-off retreats almost never achieve.

Case in point: Before 2017, one of my clients in the Jamaican financial sector had never put a date to an assumption: “the average local customer is not ready for online services.”

When I challenged them to place a date on the moment when 50% of the population would reach that threshold, they predicted: 2028. They wove that date into their plan.

Three years later when the COVID-19 pandemic arrived, that plan was simply accelerated (i.e. compressed) to be implemented within months rather than a decade. They were lucky.

The Resilience Dividend

There is a benefit to this process that rarely appears in planning frameworks: the organization becomes significantly harder to surprise.

An executive team that has jointly built a long-range plan, surfaced its embedded assumptions, dated them, stress-tested scenarios, and explored acceleration options has essentially pre-thought a wide range of futures.

When the external environment forces their hand — a market disruption, a technology shift, a crisis that compresses years into months — they are not improvising. They are activating a version of something they already worked through. The decisions feel fast because they had already built the internal logic needed to respond.

This is not a theoretical benefit. Organizations routinely discover, under pressure, that their plans contained a faster path they simply hadn’t chosen to pursue yet. The companies best positioned to accelerate in a crisis are the ones that already knew, in principle, how acceleration was possible — because they had asked themselves exactly that question before one was forced on them.

The slow work of building shared logic, it turns out, is what makes rapid response possible. Resilience isn’t built in the crisis. It’s built in the room, in the meeting before the meeting, when the CEO is quiet enough to let the team think.

Why This Rarely Happens — and What to Do About It

The reason most aspirations which require long-term strategies end up stalling is that the people accountable for executing them never felt genuinely accountable for creating them. The CEO’s vision, however compelling, remains the CEO’s vision. Rollout becomes performance. Compliance replaces conviction. And when conditions change, there is no one in the room who feels responsible for updating the logic — because the logic was never theirs.

The two-meeting structure addresses this not through a motivational technique but through a structural one. Ownership is built in at the design stage. The compression question in the second meeting then activates that ownership, rather than challenging it.

The process asks something genuinely difficult of the CEO: to be quiet and patient at the moment when they most want to speak, and to ask a question — rather than issue an instruction — at the moment when they most want to apply pressure. Both moves feel counterintuitive. Both, consistently, work.

Begin with the meeting where you say less than you ever have before. What comes next will surprise you.

Use These LLM Prompts to Apply This Framework

Copy any of the following into an AI assistant to put the ideas in this article to work for your organization.

  1. Pressure-test your current strategy “Here is our current strategic plan: [paste or summarize]. Using the Rolling Wave principle from the article I just read, identify where our plan conflates short-, mid-, and long-term planning into a single approach. What assumptions are we treating as facts? Which ones should have a specific date attached to them?”
  2. Prepare for Meeting One “I am a CEO preparing to run a long-range planning session where my role is to facilitate, not lead. Our industry is [X]. Help me design a 3-hour agenda that guides my executive team to construct a 20-year aspiration themselves, without me imposing a conclusion. Include the questions I should ask — and the ones I should resist asking.”
  3. Surface your team’s hidden assumptions “Here are the key assumptions embedded in our strategy: [list them]. For each one, challenge me to convert it from an open-ended belief into a dated, falsifiable claim. Then identify which assumptions, if wrong, would most significantly change our direction or timeline.”
  4. Run the compression question “Here is a summary of our long-range plan: [paste summary]. Assume the logic is sound. Now help me identify: which parts of this plan are paced by genuine external constraints, and which are paced by internal inertia or conservative thinking? Where could the timeline realistically compress — and what would have to be true for that to happen?”
  5. Build your resilience map “Based on the strategic plan below [paste], identify the three to five external disruptions — technology shifts, market changes, regulatory moves — most likely to force an acceleration of our timeline. For each, describe what an already-prepared organization would do in the first 90 days, versus one that had never considered the scenario.”
Posted on

The AI Assistant: Automating Administrative Friction and “Shadow Work”

In this episode, we’re discussing how to use AI to automate "shadow work", the boring, repetitive tasks like data entry and invoicing that drain our energy. By viewing AI as a "million interns" that need clear instructions and human supervision, the hosts share how to streamline everything from professional billing to personal life choices like cooking and movies. While AI can sometimes make mistakes or "hallucinate," the episode explains that investing time in training your AI assistant can remove administrative friction and help you focus on the work that actually matters. (If you’re reading this in a podcast directory/app, please visit https://productivitycast.net/147 for clickable links and the full show notes and transcript of this cast.) Enjoy! Give us feedback! And, thanks for listening! If you'd like to continue discussing The AI Assistant: Automating Administrative Friction and "Shadow Work" from this episode, please click here to leave a comment down below (this jumps you to the bottom of the post). In this Cast | The AI Assistant: Automating Administrative Friction and "Shadow Work" Ray Sidney-Smith Augusto Pinaud Art Gelwicks Francis Wade Show Notes | The AI Assistant: Automating Administrative Friction and "Shadow Work" Resources we mention, including links to them, will be provided here. Please listen to the episode for context. "Deep Work" and "Shallow Work" by Cal Newport Flow Theory by Dr. Mihaly Csikszentmihalyi Personal Productivity Club Raw Text Transcript Raw, unedited and machine-produced text transcript so there may be substantial errors, but you can search for specific points in the episode to jump to, or to reference back to at a later date and time, by keywords or key phrases. The time coding is mm:ss (e.g., 0:04 starts at 4 seconds into the cast’s audio). Read More Voiceover Artist | 00:00 Are you ready to manage your work and personal world better to live a more fulfilling, productive life? Then you've come to the right place. Welcome to ProductivityCast, the weekly show about all things personal productivity. Here are your hosts, Ray Sidney Smith and Augusto Pinault with Frances Wade and Art Gelwix. Raymond Sidney-Smith | 00:18 Welcome everybody to productivity cast the weekly show about all things personal productivity. I'm Ray Sidney Smith. Francis Wade | 00:25 And I'm Francis Wade. Raymond Sidney-Smith | 00:28 Welcome, gentlemen, and welcome, everyone. To ProductivityCast this week. We're diving into the world of artificial intelligence and its growing role in our personal productivity. This is going to be a part of an ongoing series we're calling the AI-powered professional. And in today's episode, we'll be exploring how AI tools are moving beyond simple task management to tackle tedious shadow work, things like administrative friction, small repetitive tasks, and context switching overhead that drains our time and energy. And so we're going to talk about how to approach shadow work with AI, how to overcome the problem, and we can talk about some of the solutions that we have utilized throughout the So let's get into this. Raymond Sidney-Smith | 01:13 Episode. Raymond Sidney-Smith | 01:16 And first, let's spend a little bit of time talking about what exactly is administrative friction and shadow work. Does anybody want to kind how they... Raymond Sidney-Smith | 01:26 Of tackle. Raymond Sidney-Smith | 01:28 Perceive what shadow work or administrative friction is. Francis Wade | 01:32 Sure, it's the stuff that I have to do to Execute the day. So it tends to be repetitive stuff. I don't have a choice. I must do it. No one else can do it. Typically, or I could train someone to do some of it, but most of it It's not worth training someone else to do it because there's probably some nuance that only I know. I see these things as a bit of a tax in the sense that In order to achieve your overall objectives, you have to do them. And yes, if you can get them automated, "Polite you, but point is that they're mandatory, they're required, and you don't have a choice.  So I know how I feel when I'm doing them because my heart sinks and my energy drops and I go through a whole metamorphosis into someone who wishes he were doing something else. So that's an emotional Sugar for me. Or a Marco. Augusto Pinaud | 02:34 You know, for me, the shadow work is all that work that is required to do to really be able to focus on being productive. And I'm dead. And the reason is, as Francis was saying, it's normally it's not the fun work. Okay. But it's the fun, it's the work that you need to do. To be able to get to that fun work to get to that. Work in which you can really focus and you can shine. And Us bored. As tedious That's it is. It's critical to be able to get a good session of productivity. Raymond Sidney-Smith | 03:13 Yeah. Cal Newport defines his concept of Shallow work. As I think what we think of as what we call shadow work. And so there's this concept of often performed while you're doing other things and doesn't create a lot of value. And I've always had a problem with the concept of shallow work and deep work. I think that those definitions, deep work being high value, items that you're highly focused on just really sounds like flow work to me. And so, but I define flow work, of course, the way that Dr. Mihaly Csikszentmihalyi talks about it. And The goal here is to really look at this from a lens of if we're doing all of this administrative work, I think that there is some great value to some of it. As I typically use the example that you could have a five minute phone call and have a client say, let's sign the million dollar contract. Right. Was the five minute phone call worth it? Absolutely. And some people would consider that an administrative issue. Burden, right? That would be administrative friction having to take and have that five minute phone call.  So we have to kind of parse apart those things that are high value and don't take a lot of time. Those things that are low value and take little bits of time or lots of time, each of which are kind of problematic in their own way.  And then being able to overcome those through various mechanisms. Artificial intelligence is just one of them.  So we have to be mindful that what we're talking about here today is just one of the ways in which you can overcome this. But I don't think that AI ultimately becomes the panacea. It is just one option that you have among many for being able to overcome these kinds of issues. Couple things that I wanted to kind of talk about here is that I think that Data entry generally is administrative friction and is a classic type of shadow work that you can think of. And Honestly, data entry is what computers were built for.  You know, the whole concept of being able to take data and run calculations or structure it in a way I think is the archetypal form of shallow, shadow work. Francis Wade | 05:50 The data entry I have an intern that works with me or an associate who works with me and She was doing an entry job And I thought about it for a minute, because she was not enjoying it. And I said, It's one of those, again, it's one of those taxes that at some point you've got to pay because We all have to enter data at some point. And we'll try all our best to not have to do it. But again, it's one of those sinking feelings that after you thought of everything and you realize that at the end of all your thinking, you still have to enter the data. There's no shortcut available. You got to do it. And I entered I remember. , entering data early in There's a way to it. Into data and I was trying to share this with her That's more skillful. Because you're paying attention to what you're doing. You're not checking out to the point where you're making mistakes. And at the same time, you're taking care of your well-being.  So you're not engaging in conversations that are dragging you downhill and getting you depressed. That there's a way you have to manage your mind. And manage your attention. To do good data entry so that you don't do nonsense.  So it's actually, I tried to paint this picture for her. It's actually a skill. That Once you have it, you can always Do it. Use it. But it's not a skill to... Resist in the sense that you wish it weren't there. It actually has so much, sometimes the data has so much value, that you need to bring your best skills to your data entry.  So that you don't end up resisting it. You don't end up resenting it. And you don't end up making mistakes so it's a skill in and of itself. And funnily enough, after I gave her this, very inspirational explanation. I ended up spending It must have been at least six hours entering data. There was no way. I was yeah. And I actually did some automation. I did a little lab coding to kind of speed it up. But that could only get me so far. But not go any further. And I thought, I'm eating my own dog food, taking my own medicine. But I agree. Raymond Sidney-Smith | 08:19 Yeah, I'll say this. There are so many ways to ease the burden of data entry. Again, it's about the ways in which input and output in computer communication in human-computer interaction that we just don't think about.  So, you know, Our input options for a device are typically in an input perspective. There's audio, right? You can put audio through a microphone into it, which is what we're doing right now, recording the podcast.  And then there's video, having the device take in video. Or images and then of course mouse and keyboard and if you have a touch screen or a touchpad like a Wacom board, you're capable of putting in some kind of handwriting or hand drawing some kind of, you know, stylus type input or touch inputs into the device....
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What Does Perspective Mean in GTD?

In this episode, we're discussing the concept of perspective as a contrast to the GTD concept of control. We explore the "Horizons of Focus" and the different altitudes of self-management, ranging from the "runway" of daily actions to the "50,000-foot" level of life purpose. We debate whether perspective is a tactical relationship or a pseudonym for context while contrasting top-down visioning with bottom-up execution. From discussing the "elasticity" needed in planning to identifying incongruencies between our values and our careers, we explore how these various layers of focus can transform mundane tasks into meaningful progress toward a fulfilling life. (If you’re reading this in a podcast directory/app, please visit https://productivitycast.net/146 for clickable links and the full show notes and transcript of this cast.) Enjoy! Give us feedback! And, thanks for listening! If you'd like to continue discussing what perspective means in the context of GTD from this episode, please click here to leave a comment down below (this jumps you to the bottom of the post). In this Cast | What Does Perspective Mean in GTD? Ray Sidney-Smith Augusto Pinaud Art Gelwicks Francis Wade Show Notes | What Does Perspective Mean in GTD? Resources we mention, including links to them, will be provided here. Please listen to the episode for context. Getting Things Done by David Allen The 8th Habit by Dr. Stephen Covey Unlimited Power by Tony Robbins Tony Robbins Audio Programs GTD "Horizons of Focus" Model Personal Productivity Club Raw Text Transcript | What Does Perspective Mean in GTD? Raw, unedited and machine-produced text transcript so there may be substantial errors, but you can search for specific points in the episode to jump to, or to reference back to at a later date and time, by keywords or key phrases. The time coding is mm:ss (e.g., 0:04 starts at 4 seconds into the cast’s audio). Read More Voiceover Artist | 00:00 Are you ready to manage your work and personal world better to live a more fulfilling, productive life? Then you've come to the right place. Welcome to ProductivityCast, the weekly show about all things personal productivity. Here are your hosts, Ray Sidney Smith and Augusto Pinot with Francis Wade and Art Gelwix. Raymond Sidney-Smith | 00:18 Welcome back, everybody, to Productivity Cast, the weekly show about all things personal productivity. I'm Ray Sidney Smith. Augusto Pinaud | 00:24 And I'm Augusto Pinaud. Francis Wade | 00:26 I'm Francis Wade. Art Gelwicks | 00:28 And I'm Art Gelwicks. Raymond Sidney-Smith | 00:29 Welcome, gentlemen, and welcome to our listeners to this week's episode. Today, we are going to be talking about perspectives as a contrast to last week's episode on the GTD concept of control.  So in order to start off the conversation, I want to lay the groundwork with perspectives. The Getting Things Done March 2015 edition appendixes. Glossary of terms definition given for perspective. And it says, one of the two key elements of self and organizational management, along with control, and it refers to point of view, focus, altitude of horizon. We have this concept of horizons of focus in getting things done. And what I'm hearing from the definition is that David Allen is saying that each one of those horizons of focus is a perspective. That's what the terminology is talking about. And so with that in mind, I wanted to ask, Is. Perspective the right term? And what does perspective mean to you in your own. Francis Wade | 01:33 My mind perspective is a pseudonym for context. And as someone smart said, context is decisive. The background story from which you take your actions is all important. And it's malleable. And most of us just wake up into the context that human beings wake up into every day, which is something close to survival. Survival, desperation, fear, you know, how can I make it through the day kind of, point of view. I think that's the default.  And then to Create a new context, tics. Or any perspective takes. Conscious act for the most part conscious action it takes deliberate effort. I think this is all important. I think the book GT is really about that. And perspectives is one way of seeing it. I think this idea that... The context of your life is decisive is an idea that's been around probably since the Greeks. And that's something worth paying attention to.  So yes, it's vitally important. Art Gelwicks | 02:41 What I think is interesting about this looking at perspective and how it breaks down is that often perspective is not related to ourselves. If you look at the GTD structure you've got, and I'll work from the bottom up, Actions, Projects, Goals, Vision, Life The first four of those categories are often... Stolen for lack of a better term by corporate and work environments. To set the messaging. For everything that you're supposed to be doing and that becomes the context, for lack of a better term, that those get applied in. It's difficult for us to translate goals, vision and life into actual real life things, because every time we think about it, we think about, you know, the next five year plan at work.  So... If we think about it from the perspective of how they relate to each other, perspectives in my book, are pretty much whatever you're dealing with and the thing above and the thing below it.  So projects is a good example. If you're working on projects, The projects need to align to the strategic goals that you have. If it's business, obviously you have business strategic goals. If it's personal goals, The things that you're doing should align to those. You have to determine what those are, but they should be tied to it. And below that, the actions necessary to execute those projects.  So the perspective is less... What the term would lend me to believe, which is a view on things and more of a relationship. Raymond Sidney-Smith | 04:27 I certainly see perspectives for me. As a vertical planning tool. And so each of the additional perspectives above the actions level or the ground level in at least GTD lingo, you are seeing a different and therefore you were planning at a different time. "layer of time" So it's for me, I always think of time horizons is that, you know, projects are within our time bound within about a year and then you keep stepping up to further and further distances of time. Accepting the horizon too, which is areas of focus and accountability, which ends up being something that is it's a maintenance level.  So, While each of the time horizons keep going up in that sense, Horizon 2 is the exception there because it's maintenance. It's ongoing maintenance. And if you're like me and you've created other horizons, other perspectives, then you may have other time horizons in that sense as well. They're not going away. And so that has an infinite horizon in essence.  So I'm looking at it on a regular basis purely because it's perennial. It's always going to be there. The interesting thing about perspectives for me is that I think that there is a clear... I don't know if I want to say contrast or argument between other systems, other methodologies, other thought processes on this and perspectives. I'll give you one example, which is Dr. Stephen Covey's The Eighth Habit, where he talks about the concept of the four intelligences. And if... Control and perspective are really the only two vectors of a productivity system, then Where does something like the four intelligences fit. And I would say that Dr. Covey would say that this is perhaps a completely different dimension.  You know, the four intelligences being mental intelligence or IQ, physical intelligence, PQ, emotional intelligence, EQ, and spiritual intelligence, SQ. And so he has this perspective on the four intelligences and how they map to all of the rest of how you would develop in his language, you know, finding your voice and helping others find theirs. And so I'm always... I don't know if I'm conflicted because I have myself learned to deal with where these things fit in my own system. But I can see that there can be a difficulty for folks to think about how Picking. IQ, PQ, EQ, SQ, and turning that into vision, discipline, passion, and conscience in the eighth habit world, and then seeing the somewhat limited I wouldn't say limited, but more simplistic view of the perspective concept. And I'm curious from all of you, Do you see a conflict or do you see... Perspective is just basically holding other I. Art Gelwicks | 07:38 Think perspectives are a more tactical term. Approach. They're more tangible. We associate them with things and activities that we have going on. Stephen Covey's concepts are more to understand people. I want to say spheres of influence. I don't know that they necessarily relate directly to each other. There is no dotted line. It is difficult at best. To translate. For example, projects into mental intelligence, you're not going to be able to make that connection easily without it stopping. Significant amount of work. Raymond Sidney-Smith | 08:18 Yeah, but to interject right there, like, so if we step up a few horizons and we get to vision and purpose and principles, then we're really starting to connect. The concepts of what he's talking about there at the very top levels of the system.  So it's not really closer to the tactical level, but more when he starts talking about, you know, creating vision, right, which he defines kind of as applied imagination. And then he we keep stepping down to these other, not stepping down, but going around the four quadrants, right? To figure out passion and discipline and conscious and otherwise.  So it's, At those upper horizons, it starts to bleed over one another. I.
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What Does in Control Mean in GTD?

In this episode we’re discussing the concept at the core of personal management: control. Specifically, we’ll be philosophizing about what control truly means within the context of the Getting Things Done (GTD) methodology. We’ll start with David Allen’s definition, which ties control to the workflow stages of capturing, clarifying, organizing, reflecting, and engaging. But does that definition fully capture the complex, often psychological, reality of feeling “in control”? Then, we explore how to build tangible systems and “guardrails” that move us from simply feeling overwhelmed to being confidently in command of our work and personal lives.

(If you’re reading this in a podcast directory/app, please visit https://productivitycast.net/145 for clickable links and the full show notes and transcript of this cast.)

Enjoy! Give us feedback! And, thanks for listening!

If you’d like to continue discussing what control means in the context of GTD from this episode, please click here to leave a comment down below (this jumps you to the bottom of the post).

In this Cast | What Does Control Mean in GTD?

Ray Sidney-Smith

Augusto Pinaud

Art Gelwicks

Francis Wade

Show Notes | What Does Control Mean in GTD?

Resources we mention, including links to them, will be provided here. Please listen to the episode for context.

Getting Things Done (GTD) by David Allen

How to Get Control of Your Time in Your Life by Alan Lakein

Freedom.to (A Focus application used to block digital distractions)

Fitbit watch (Used to track sleep)

Byron Katie’s process (A methodology for managing unwanted thoughts or feelings)

Raw Text Transcript

Raw, unedited and machine-produced text transcript so there may be substantial errors, but you can search for specific points in the episode to jump to, or to reference back to at a later date and time, by keywords or key phrases. The time coding is mm:ss (e.g., 0:04 starts at 4 seconds into the cast’s audio).

Read More

Voiceover Artist | 00:00

Are you ready to manage your work and personal world better to live a more fulfilling, productive life? Then you’ve come to the right place. Welcome to ProductivityCast, the weekly show about all things personal productivity. Here are your hosts, Ray Sidney-Smith and Augusto Pinaud with Francis Wade and Art Gelwicks.

Raymond Sidney-Smith | 00:19

Welcome back, everybody, to ProductivityCast, the weekly show about all things personal productivity. I’m Ray Sidney-Smith.

Augusto Pinaud | 00:25

And I’m Augusto Pinaud.

Francis Wade | 00:26

I’m Francis Wade.

Art Gelwicks | 00:28

And I’m Art Gelwicks.

Raymond Sidney-Smith | 00:29

Welcome, gentlemen, and welcome to our listeners to this episode. Today, we are going to do some philosophizing, I suppose, and hopefully bringing ourselves from that level down to the practical. We’re going to be talking about control. And what I wanted to do was to preface this with The concept of control and perspective in the Getting Things Done or GTD methodology perspective, which is that that’s where came up to me in the first place. And over the years, it has changed. And so I want to talk about what does control mean to each of us and how do we actually make the concept of control practical even tangible in our own worlds. I’m going to define what David Allen says of control in Getting Things Done in the March 2015 edition, in the appendix, in the glossary of Getting Things Done terms, he actually gives a definition for control And then we’re going to talk a little bit about what, the concept of GTD control is so that we can then define what We think of it as in contrasting terms. 

So he says of control, one of the two key elements of self and organizational management along with perspective. And so that’s what he calls control in the most basic terms. And if we think about it from the concept of control and perspective, control are the steps of the or stages of the workflow going from capturing to clarifying to organizing, reflecting and engaging on the action level of the horizons of focus. That is what he considers control. 

And then as we go up the horizons on the y-axis, we then have projects and so on and so forth going up the horizons. And that’s what he considers perspective. 

So control are the actions that we take on the lowest level of the horizons of focus and everything above that becomes perspective. So kind of thinking of it as looking down at the actionability of the thing above itself. 

So when you’re at the highest level, Horizon 5 purpose and principle You are looking down at the other’s vision, goals, areas of focus and accountability, projects, and actions. So that is the GTD definition. And… We have all probably thought of it as being insufficient in some way, shape or form in our own worlds. And now what I’d like to do is to ask you all, gentlemen. How do you define control? And what is… If I think Art gave a really great example before we started recording, if someone came to you and said, I’m feeling out of control, how do you help them get in control or under control in their life?

Francis Wade | 03:10

So I think David Allen’s definition is basically a process definition. So he’s saying, here are the steps. Or managing tasks. And the ones that really start with capturing and so forth are basically the steps for managing tasks. And I suppose that I’m guessing that what he means by control is that the… Process of managing tasks is in control. Now, that has a very specific meaning in my world. I was trained in part as an industrial engineer. And we love For those of you who know the Leningrad-Stewart charts and control charts, we love the idea of measuring processes so that they stay in control. That’s not practical for most people to be able to use these kind of diagnostic tools. But the way I would advise to answer your question, Reem, someone who tells me that they’re out of control… Is to ask them What do you mean? Because the word control is a psychological object The definition has changed and it varies and there’s no uniform. Understanding of what it means. 

So you have to go to the next step and say, When you say control, the question I would ask is when you say control, What specifically? Symptoms are the ones that you notice and I would imply in real life. Not just in your emotional life, but in The Hard Tensible Life where are those symptoms occurring? Such that you’re led to conclude that you’re feeling out of control. 

So I would immediately go to and I would focus and start to break down their response. Between I’ve mentioned psychological objects like I’m feeling stressed, I’m feeling unhappy, I’m feeling unworthy, I’m feeling lazy. As opposed to I arrive at half of my appointments at least ten minutes late. Okay, there we go. That’s one. That’s a tangible object. We can work with that. What else do you have? Well… I wake up in the middle of the night three times out of the week. With something that I forgot to do. That’s two. All right, that’s another tangible activity. 

So I would look for the tangible symptoms. The things that you can put your finger on, you can touch, you can see. 

And then accumulate those so that we move the conversation from and feeling out of control. Towards And again, in the lingo of industrial engineers is defects. We’re looking for defects. And we’re looking to put them together so that we can say, okay, with these five defects, the root cause of them are Because the truth is, control is a lag indicator. Peely Walter Control is a lag indicator. Comes a lot after. The things that you Did or didn’t do. 

So we’re trying to go all the way back so that When we start to… Figure out what they should do, We’re actually looking at things that they did do or need to do or didn’t do. In tangible reality. 

So that’s how I would tackle it. Said that to me.

Art Gelwicks | 06:21

Control to me is a very… Unlike the industrial… Definition of it. I look at it from the almost the psychological side of it. Control is a perceived state of comfort It’s a lack of stress. It’s a… Point of awareness. Of activity And I think when someone says they are out of control, my first reaction is to ask the question, When do you feel things went out of control. Because I need to know contextually Is this something that is a recurring feeling, which means that it is probably systemic. To a process failure Or is it something that has recently happened, which may be triggered by an environmental response or some external factor that has pushed things off the rails? But control itself like a, can be an extremely negative impact. On work and process and quality of work. Having a sense of control. I don’t know is necessarily an extremely positive thing. It’s basically neutral. You feel like, okay, if I’m in control, I can do… What I need to do. If I’m out of control, I can’t do what I need to do. But at no point are we saying that if I’m in control, I can do better things. I’m just saying that I can do things. 

So to me, I always look at it from the mental aspect of it more than the process one, because The process one I can chase. I mean, I can look at the measures. I can look at the metrics involved and say, OK, this is working. This isn’t this. But that doesn’t necessarily, again, translate to a lack of control. And we’ve all seen it. We’ve had people who have processes that work somewhat. But they feel like they are in control, but we know looking at it, it’s like, no, you’re not. As much as you think you are, you’re careening wildly down the highway. 

So… The subjectivity of that term and the amorphousness of that term makes it difficult to have that initial conversation.

Raymond Sidney-Smith | 08:49