Get Everything Done

I liked the topic in and of itself (being a computer scientist), so I'm going to read through the book and see what they have to say! I'm sure I'll have some comments to bring back after that.

Alright, I finished reading the first part of the book, and I have not yet finished the case studies.

This book resonates deeply with me. I have to say that I don't think Alan's expectations of the interpretation of the book are quite accurate.

Focusing specifically on what implications the book makes for individual action, I'd say that it's making the following claims:

1. There are two types of objectives or goals: mundane and ambitious. Mundane goals are fully, completely, totally understood, with no uncertainty, and can be achieved directly. They represent the space of known quantities and competencies. These sorts of objectives not only can be achieved, but the use of them can help facilitate effective and efficient achievement.

2. Ambitious objectives/goals are such that they represent some level of unknowns. They are such that we don't really know how to achieve them or how to make them happen. An important insight claimed in the book is that *many* more goals in our lives are ambitious than we might think at first.

3. By their nature, ambitious goals are almost certain to be highly deceptive. This fundamentally means that how close you currently seem to be towards achieving a given goal is a fundamentally *bad* indicator/false compass of whether or not you actually are to reaching the goal.

4. Because of inherent deceptiveness, attempting to achieve an ambitious goal by pursuing that goal (that is, trying to get closer to the goal), ironically and systematically tends to lead to a high likelihood of *not* achieving the goal.

5. Even worse, the pursuit of any ambitious goal cannot even reliably predict the achievement of *other* ambitious goals. That is, "aim for the moon and at least you'll land among the stars" is a fundamental falsehood.

6. Even worse than this, the pursuit of objectives/goals of this sort can be not only correlated with, but shown to actually *cause*, low achievement and mediocrity.

7. The only successfully replicated search strategies that are able to achieve high outcomes reliably and consistently are "non-objective" search strategies. Translating this to personal living, this would imply that only by living according to constraint-driven/principle-driven action rather than goal-driven action, can we increase the likelihood of "success". That is, your heuristic decision function is a constraint function rather than an objective function (in more technical terms).

8. But even more radically, such strategies are not able to guarantee any outcome; there's no secret recipe to success. Instead, they provide the highest likelihood of achievement, but they also *require* you to give up the achievement of any *specific* outcome. In other words, they aren't just another way of achieving an objective. You have to give up on the specific pursuit of ambitious objectives.

9. Instead of the pursuit of ambitious objectives, the recommended constraints/principles are instead to pursue what is interesting (which is highly connected to what is novel). They claim that, indeed, pursuit based on interestingness may be the most principled and mathematically sound method of high achievement.

10. Moreover, this all implies fundamentally that one pursues what is reachable/attainable from here, rather than be driven by a future that is distant. Put their way, you can move the present into the future, but you can't bring the future to the present.

They sum this up, essentially, by saying, "to achieve our highest goals, we must be willing to abandon them."

I have to admit that this whole approach is deeply appealing and intuitively meaningful to me. It also serves as a sort of Unified Theory of action that ties together many of the various types of advice that I always found useful, but maybe one-dimensional. Consider:

* First things first
* Do one thing at a time
* Gardeners vs architects (writing style)
* Agile methods and incremental development
* Ivy Lee
* Eisenhower Matrix
* Flow states
* Jorden Peterson's claim that meaning is found on the boundary between chaos and order
* Kaizen and Continuous Improvement models

IMO, this book provides a compelling method of unifying all of these various ideas into a unified model that connects them all and reveals an underlying and overlapping interpretation that would adequately explain their effectiveness, as well as illustrate why they might not work for some people.

It also provides a mechanism by which we can evaluate Mark Forster's long list systems and other TM systems and provides a more grounded theory underpinning Mark's previous discussions about how some people explore through a seedbed of possibilities and others pursue a focused goal.

If you even want to get into the religious elements, I think there are deep connections with life philosophy that is found inside many faiths, but especially some of the ways in which you can interpret the Christian faith and some Eastern beliefs. There are deep structural similarities between the above points and things like the Dao De Jing, Christ's comments on present mindedness and "seek the kingdom of God first", Zen meditation and focus, as well as more apparently "goal driven" comments like Proverbs' and Ecclesiastes' on work, effort, and so forth.

I especially appreciate their willingness to slaughter some sacred cows here in the US's overall approach to life and living.

IMO, the most powerful element of the book is the clear and methodical approach that they give to delineating between when an objective is useful and when you should discard objectives. It makes the resolution of useful goals very small, and something that puts a huge perspective on things. It also provides a framework by which you can introduce non-objective search strategies in your own work, and I can already point out areas where I've been arguing in my own field for certain patterns that I've found successful which mirror exactly what the book espouses. Since objectives only make sense in the face of "perfect knowledge", then you can create a constrained system around lack of clarity and then have confidence that a non-objective exploration of that space is likely to be more successful than an objective-driven search. You may *still* not succeed, but you've increased your chances. This provides a very useful tool for not only general time management, but also for solving specific problems. It enhances the "break down the problem into smaller bits" idea into something much more rich and powerful, IMO.

Given that I'm a computer scientist myself, I'm probably biased by their arguments, as I'm familiar with the overall issues that they address and also can intuitively understand the points that they are making, which might make me a little more likely to agree with them.

To me, it's also very powerful that they not only discuss the fundamental theory, but they also provide a specific, actionable, practical plan for putting that theory into practice. They don't just say "stop living by objectives." Instead, they give you the alternative, which is to live by interestingness, with the use of objectives helping to efficiently execute within spaces that are well known and clear of unpredictable obstacles.

I think this might also provide a successful and missing component that might allow me to use Mark's systems with more confidence.

Overall, it's such a short and easy to read book, and it's so well argued, IMO, that I think this should be required reading. :-)

Alan:

Regarding gradient search, I'd have to do a little examination into whether gradient search would be considered this strategy or not. The authors actually bring up gradient search in opposition to this idea, because traditional gradient search, at least in my mind, tends to focus on evaluation of an absolute measure via an objective function, which is the interpretation that work off as well. They are specifically emphasizing non-objective search and use their own research in novelty search specifically as a springboard for this sort of thinking.

One thing they highlight is that traditional gradient search tends to find local optima. This is because it has a specific objective. They distinguish something like novelty search from objective search because in objective search, any two given points in the search space tend to be absolutely evaluated as either good or bad relative to the objective. Their point is that such evaluations are deceptive. Instead, novelty search creates a set of constrains that embeds the concept of prior knowledge in judgments of what to pursue next, without any judgment against a fixed objective. In the case of novelty, doing something novel is at first good, because it is novel, but over time, repeating that same action is no longer novel, and as such, that same action becomes less desirable over time. This dynamic, contextualized reinterpretation of the heuristic function is part of what they are emphasizing. Another way they frame this is that something like novelty search doesn't depend on knowledge of or vision into the future, but rather is dependent on knowledge of the past, which is much more reliable. An objective function as they define it depends on comparing the present against the future, while the novelty search depends on examining a present action against the past.


I also decided to see what people might be saying against the writing in the book, to see if there were some other things to consider. However, most of the arguments that I've seen were responses not to the book but to the video presentations that the authors have made in relation to the book. Generally, people made arguments that were already adequately addressed in the book, such as whether a hybrid approach would be better than one or the other.

However, there was one point that the authors readily concede that other people have pointed out, and that is that as dimensionality increases and the search space explodes, non-objective search can get just as lost in the search space as anything else. In fact, if there are no obstacles anywhere, and no walls, then non-objective search can just lose itself entirely without any markers. Of course, the reality is that pretty much all other methods also struggle to some degree with this. Part of the question is how well our real world maps to any given one of these various systems.

I think the answer to fitment in the real world is interesting because I don't think it is fixed. We get to, in some sense, control our search space. We are not unintelligent creatures who don't have any control over our search space. The authors make this very point, that humans are much better at novelty and interesting search than pretty much anything else, and in fact, we seem to be partially built specifically for this "interestingness" search. It's a theme that has run through a huge number of traditions, and it is encoded everywhere in humanity. This means that we're already likely in a better place. But more than that, when we are looking to pursue something, we can often put many more constraints on the space than some might. We're not search blindly. One of the reasons that interestingness is so valuable is that pursuit of such things generally results in the efficient accumulation of new knowledge, and that new knowledge opens up more "steppingstones." The authors themselves make the point that a steppingstone that doesn't hold the potential to open up more steppingstones shouldn't be considered as interesting as one that opens up new possibilities.

Given this, we can tackle the issue of getting lost and wondering for all time simply by allowing ourselves to embrace more constraints and principles rather than more goals. Rather than falling back into objective thinking, we can fall into principles that create more desirable constraints on our search. This is one of the most reliable and powerful ways to improve the ability to find something within a given unknown space, provided that the constraints don't constrict your search space so as to miss the things that matter, but again, you can't reliably find any specific thing anyways.

If I were to criticize the work for anything in particular, it would be that the authors don't do enough to articulate the appropriate interplay between mundane objectives and non-objective search. They make references to it, and talk about how mundane objectives (such as coding software that meets a specification) will always be valuable and useful, but they leave the details of how that might interact with search a little less well-defined.

My interpretation is that the existing objective driven techniques still work whenever you have established a specific and clear next thing that represents a clear outcome/objective in which all the steps to get from here to there are not only known, but fully actionable along the entire space without concern for obstacles. Where I think more thought should be spent is right on the border, where we need to, for instance, decide how many interesting things we can do at once, or how to really know whether something is mundane, and so forth. Is it okay to leave the pursuit of a steppingstone halfway?

My current interpretation at that intermediate level is that the steppingstone metaphor is a good one. We probably can't really go to more than one steppingstone at a time (one thing at a time), so it's mostly a matter of choosing one. The challenge I have is regarding the *finishing* of things.

Implicit in the authors work is a mandate for communication of the results of your pursuits to the outside world (production), in some form or another. This implies, to some extent some level of "finishing". But one potential concern for interestingness is that it might change too rapidly, and we might go after a bunch of interesting things, but with zero finished things to show for it. That would undermine the concept of achievement, in which the intent is to at least go *somewhere*. My gut feeling is that this requires at least some commitment to achieving some specific steppingstone that is visible before changing course, but it might also be the case that as long as you can take a sufficiently useful step in information enhancement and somehow communicate that to the outside world in some useful (valuable) way, that might be enough to justify shifting gears.

And that is where outcome thinking might come right into focus. By establishing a fundamentally clear outcome for something and making sure that it is an actionable thing that is a mundane outcome (connected to SMART goals), then maybe it is best to doggedly pursue that thing until the outcome is achieved, the results summarized and reviewed, and the next interesting thing chosen. In this sense, we are always at least producing something, enhancing our knowledge, but also expanding our search space by choosing to pursue the interesting.

The authors have this to say on the matter, I think:

"Contrary to popular belief, great inventors don’t peer into the distant future. A false visionary might try to look past the horizon, but a true innovator looks nearby for the next stepping stone. The successful inventor asks where we can get from here rather than how we can get there. It’s a subtle yet profound difference. Instead of wasting effort on far-off grandiose visions, they concentrate on the edge of what’s possible today."
-- Stanley, Kenneth O.; Lehman, Joel. Why Greatness Cannot Be Planned (p. 97). Springer International Publishing. Kindle Edition.

If we scale that down, this might just make for an adequate heuristic for daily work.

I've been trying to figure out how exactly this book should impact my personal TM systems and methods of productivity, and it was surprisingly hard for me to tease it all out. However, it all finally came together. This neatly ties in with Mark's ideas about priorities and at what point you should prioritize.

In short, this book helps to provide an alternative for choosing WHAT you do, that is, what you COMMIT to. However, the book completely avoids any discussion about HOW you do what you commit to doing.

The book basically provides an alternative to planning and what many would describe as Vision-oriented thinking (where visions are long term objectives and outcomes) or outcome-oriented thinking, which is to instead focus on interesting things that are at the edge of the space of possible things in the present (today).

Once you have committed to something in such a framework, you then need to apply proper time management and productivity systems to actually do the work, though.

Alan:

<<Why: We want to make you happy. How: By providing a better way to connect with people you love. What: This device or service or instruction. ... And if Greatness is not best reached by laying down a concrete Objective, maybe these hows might best be resolved in an incremental fashion.>>

I think the above highlights one of the main messages in their book that is the hardest to stomach: the idea that having an outcome in mind is the worst way to achieve it, incremental or no. That's really probably the central main point they are making.

They are not just saying that you have to approach big goals incrementally. I think implicit in your last two paragraphs above is a sort of guided objective function, even if it is partly implied. I think the point the authors make is that you can't just give up directly pursuing the goal, you have to give up *having* the goal at all. It doesn't matter how you try to reach a specific goal, if you're trying to reach it, then you're probably not going to.

Importantly, the more valuable (that is, the more overall impact it makes), the more likely this goal is to be grandiose or ambitious, thus making it more likely that it is deceptive (almost certain), and thus falling under the admonition that it must be discarded.

Thus, when you say, "But in producing your outcome, you need to think ahead...," this is actually exactly the line of reasoning that the authors argue isn't the correct approach. The problem is that you're trying to produce an outcome, and that outcome is one which is complex enough that requires fuzzy thinking ahead.

The whole idea here is that you *cannot* guarantee any outcome past a certain very small and often overestimated threshold of possible. Moreover, trying to achieve any such outcome is almost certain to lead you astray from actually achieving it.

I think the idea of "making people happy" is a great example. The authors argue against not only objectives, but also metrics designed to facilitate optimization towards a given objective. I think "Make people happy" could easily fall into one of these two camps. A lot of people have the idea of making people happy as a goal in the form of "world peace" or "end suffering" or any other number of such things. A less global, but still overly ambitious one that wasn't mentioned in the book but that I think is worth considering is something like "end hunger." In all of these cases, having these as objectives or goals that you pursue is almost certainly the worst way to achieve them, and I think a lot of social evidence exists for this. In particular, I think a lot of evidence exists to show that all attempts that had "end hunger" in mind at a large scale were in fact the least successful at their aim, whereas the situation today with massive overall reduction in world hunger actually came about mostly because of entirely separate pursuits that did not have that goal in mind.

In the case of a Why that you mention, you could interpret "make people happy" in a local, rather than a global sense, and turn it into a principle. I'd argue that maybe it's a bad principle, but provided that it was something that was an always achievable thing in the local space that was independent of any future outcome and thus could be continually in the state of being true, I think it could represent a sort of constraint. One problem with this is that many people don't have this in mind. They implicitly want to think globally, or they start to use it as an optimization function, where they start trying to ask, "how many people does this make happy?" They then optimize for maximum happiness instead of just asking, "does this make anyone happy?" At that point, you're likely in the space of perverse optimization problems with a bad hidden objective function.

Ironically, what they don't have a problem with is the "concrete objectives" as you put it, if they are indeed concrete enough to be fully actionable and without uncertainty. Those are good, at least in terms of objectives, because they can be shown to contain no deception. It's the more fuzzy visions and objectives that become a problem.

Translating this into David Allen's GTD model, you have the planning model, which has Principles as 1, then Vision, Brainstorming, Organization, and Action. The authors would say that if your vision is anything other than downright boringly concrete without uncertainty, then you're probably doing it wrong.

What's interesting here is that a lot of things that people take for granted as good goals are probably deceptive ones, like "being successful" or "making money" or "being financially stable", especially in terms of how most people interpret those. On the other hand, releasing the iPhone or putting a man on the moon are, counter-intuitively, *not* deceptive goals.

For the authors, there are obviously mundane goals, and obviously deceptive goals, but then there is the class in between. These are the hidden mundane goals. These are the goals that are in fact fully realizable, but which used to be unreachable or ambitious. In these cases, most people fail to recognize that conditions are right for their implementation, but this is where, in the authors' views, the visionary plays his role. The visionary isn't about seeing past the horizon, but instead, the visionary sees exactly within the realm of possibility a configuration of action that was previously unreachable that no one else sees.

So, putting a man on the moon might have appeared to be a deceptive goal, but a good visionary would have seen that in fact, all the parts were in place to know that this was a fully achievable goal and that in fact, all of the uncertainty had been taken out of the equation. Instead, all that was left was to actually *do* it. But things like improving education, or being successful, or even a lot of ambitious software projects, are in fact *more* ambitious than putting a man on the moon in terms of the book's use of the word, meaning that they have more deception in them.

Thus, the authors don't just go to the point of saying that we need to explore in order to reach hard/deceptive outcomes. They say that we need to literally give up the intentional pursuit of any specific hard outcome if we want to achieve any "Great" outcome. This is the part that I think is hardest for people, and why they wrote the book, because the very idea runs counter to every single approach that people currently embrace for doing great things. It's *not* about exploration, but about rejecting the desire to know where you're going or what the intent is.

I think I can finally put together a lot of these threads that are in these discussions and try to highlight what new things this book is saying relatives to "common knowledge".

First, the book *is* controversial. There's no getting around that their particular recommendations are controversial and suggest a way of pursuing a future that is *very* different than what we are currently doing. However, I think their arguments (which they go into at length) are compelling. I don't want to rehash all of their arguments here, though. However, I can go so far as to say that I do buy their arguments that suggest that the current obsession with "ambitious" objectives and trying to drive everything on the basis of objectives is flawed.

There are a few things that are being connected with the book which are common strategies, but they are not, IMO, what the book's main point is, many of which they discuss in the book:

* Pursuing concrete goals
* Being ready to change the goal if things change
* Exploration being important (people pay lip service to this)
* You *have* to have a goal!
* You have to be incremental in how you tackle something

None of these are really what the book's primary focus is on. I also will say that I think objective functions and objectives very much are able to be connected.

Fundamentally, the book is asking the question, "What is the best way we know to figure out what to do next?" The book itself is operating on fairly "large" timescales, so they don't specifically focus on daily productivity and time management. I did exchange some correspondence with one of the authors about this point, and they found the idea interesting, but the book itself wasn't primarily targeting the question of time management in the micro, but direction and vision in the macro.

A lot of the confusion comes from not staying to the strict definitions of what an objective is vs what a constraint or principle is. As Mark points out, our minds are able to be primed to see what we are looking for. This is what makes this research so compelling, because this is such a powerful psychological phenomenon in humans that it really does tend to behave like the smaller scale models that we explore in computer science. Importantly, it's not that the mind is so much primed to see what it is looking for, but that in so doing, it is also primed to *ignore* what doesn't look like a good match. That's the fundamental point the book is making.

Objective-driven execution means that you are specifically evaluating your choice of direction or motion or whatever on the basis of how readily a given action appears likely to achieve a given objective. In particular, objectives are outcomes that can be considered "achieved" or not "achieved". That is, they represent what we generally call goals. These must be distinguished from principles or constraints. Principles and constraints are things that are always expected to be in force. That is, we expect that as we progress, we should always be able to answer "yes" to whether we are currently, at this moment, following a constraint or principle. This is different than an objective, where we are usually saying that we are getting "closer" or "farther away" from an objective, but until the objective has been accomplished, we cannot say to have achieved it. This is the fundamental distinction.

The first, foundational point the book is making is that when you are driving your action on the basis of ambitious objectives (any objective whose fulfillment exists on a "deceptive" path), of which a *huge* proportion of what we pursue usually qualifies as, basing action by priming your mind or your priorities on the basis of how well they seem to get your closer to achieving the objective is in fact a very sub-optimal way to actually achieve that objective. The reason for this is that when you are searching for ways towards the objective, you are not only priming yourself to be aware of those things, but your valuation structure inherently will have a tendency towards convergence, not divergence. The tendency of objectives to encourage convergence is a key point. Over time, as you pursue a goal, you converge towards it, which will inherently tend to encourage the reduction of other paths and options by design.

Thus, the book is trying to understand how to achieve interesting and "great" solutions when you know that trying to achieve something specific is almost guaranteed to be a sub-optimal strategy. The key insight is that divergence search strategies are non-objective. In particular, if you choose to instead enforce constraints and principles on decisions, and then encourage a valuation of decisions that focuses on the principle of interestingness, if you create the appropriate domain (constraints on exploration), then your path will tend to be more successful at finding great solutions. But the key point here is that while it will find *something*, you can't say what it will find, so you *can't* try to just subvert the divergent search as a means to doing a convergent search (non-objective vs. objective).

The reason that this tends to work is that something like interestingness generally requires that you *increase* exposure, novelty, and knowledge/experience. You can't stay in that space of interesting without growth and expanding along that "proximal zone of development". But, as it turns out, handling more ambitious objectives tends to be a matter of ensuring that sufficiently complex and sophisticated concepts and ideas are sufficiently internalized so as to reach a high level of competent accessibility. Put another way, in order to get at objectives that are beyond our reach right now, we have to become more sophisticated in some way (maybe it's figuring out how to simplify a process so that we can scale it or whatever), but with the caveat that we cannot know in advance *which* increases in sophisticated/knowledge/competency will actually lead to the capacity we need to solve any given objective. Since we must expand our range, but we can't know exactly the best way to do that in advance, a search strategy (that is, a way of choosing what to work on) that optimizes for interestingness is also extremely effective at rapidly and efficiently expanding that competency.

The difference then, between pursuing objectives and doing something like pursuing interestingness is that you can constantly be always pursuing interestingness, with all the while the actual things you are pursuing constantly changing. Indeed, they must change in order for you to be continuing to retain some level of interestingness. Objectives are achieved and then you move on to the next one, interestingness is a constraint, not an objective. It leads inherently to divergent exploration.

A particular point the authors make is that many people talk about favoring exploration, but they don't actually do exploration, because that exploration is constrained by the need to satisfy an ambitious objective, which just creates convergent exploration, which is exactly *not* exploration. We see this a *lot* in the sciences (I happen to be in exactly this situation in my own field, and the authors experienced it in their field as well as a regular occurrence), despite the claim that science should be about exploration.

We might think that this is the same thing as just pursuing a goal and then changing it over time as we learn more things. But the point the book is making is that by pursuing the goal, you're already reducing your divergence and exploration, and thus you are actually making it *harder* on yourself to see the path forward and make the appropriate course corrections. That's true while pursuing any ambitious objective. You're inherently reducing your opportunities to find better paths.

To speak to Alan's point about it seeming as if we're saying that you can't achieve anything, actually, at some level, this book *is* radically suggesting that we stop trying to intentionally achieve any specific grandiose/ambitious thing. This flies directly in the face of a lot of popular advice right now to "find your passion" or to find a mission and pursue it or any number of other ways to frame having big, grandiose "meaning in life" sorts of goals. These are all the rage right now, but the authors make the compelling argument that this sort of thing is probably a recipe for burn-out and frustration. However, their argument *does* agree with some other competing research suggesting that simply focusing on competency and building skills and developing and cultivating near term excellence can be a much better direction.

But, does this mean that we can't ever achieve anything? No! That's the point of the book. The book is saying that you'll make it harder to achieve things by trying to specifically pursue something to achieve. Instead, if you put the parameters and constraints on the area of achievement you want, such that it properly constrains the search space, while not being objective driven, then you will in fact achieve more, just without being able to say what exactly you're going to achieve ahead of time. In other words, not having a goal doesn't mean that you never *do* anything because "what's the point?", but instead, it means that the reason you pursue something isn't because it will satisfy some sort of specific objective goal you're chasing, but because it is "interesting" to a sufficient degree in accordance with the set of values and constraints that you are working with in your life.

Of course, again, if you try to "game the system' by, say, trying to find a cure for cancer by doing "divergent" search on all things that seem to be related to cancer, that's just an objective function, not an "interestingness" function. There is obviously still art and nuance in this, and you have to understand the distinction being made. That's because it's very likely that the cure to cancer depends on a lot of things that have nothing apparently to do with cancer.

Regarding Mark's comments about "showing up" I think that this begins to get at it, but the book is suggesting a very specific way of showing up. It's also suggesting that the overall rate of success may not be due as much to luck as people think. That is, if you look at the way that objective search tends to work in deceptive environments, then success very much does seem to be a lot like luck. However, if you look at this from a different perspective, then a lot of luck might be more a matter of that pattern of growth and exploration created by interestingness search. Certainly, Steve Jobs credits much of his success to this sort of "serendipity". It's easy to think of this as "luck", but it's not really raw, uncontrolled luck, because we have influence over those things. That's not to say that everything is a guarantee or that luck doesn't play a part, but that the current methods most people are using probably put them at a disadvantage.

This sort of interestingness I can map directly to most of the successes in my own life, so I'm quite willing to buy into this idea. In fact, a significant number of advantages that I end up having in a number of my own pursuits can often be directly attributed to lots of things that I did "just because" they were interesting and I remained curious. But if I were more objective driven in those times and cases, then it's very likely that I would not have had the successes that I have had.

A key refinement that the authors make on their decision function that they recommend for choosing what to pursue is the idea of what has "promise". What they mean by this specifically is what next thing can you do which is clearly not ambitious (in other words, you can see how to do it) that is also interesting that also suggests to you that it will lead to *other* interesting things. That is, an interesting thing that leads to no other interesting things isn't particularly valuable, but an interesting thing that promises to lead to lots of other interesting things is very valuable.

Finally, while I've tried to summarize conclusions here, the book goes into more detail on actually arguing the case, and most of the points brought up in this discussion are discussed in the book, so I think it's worth reading the book if you want to see the arguments justifying this line of reasoning.

One of these days I'll figure out how to write a *short* response. I promise!

I think I'm more on board with their ideas, obviously, than most of you are, but there is one area I was thinking about recently that I think the authors haven't covered, and that is the potential galvanizing effect that a goal can have.

I think it's true that people who keep striving towards a goal but constantly suffer a sense of futility around the pursuit can suffer things like burnout and other forms of morale loss or depression. At the same time, people often seem to find it difficult to "live in the moment" and focus on principles instead of goals, and those same people, when given a goal, whether or not it is strictly better for them or not, can sometimes be inspired and compelled forward into actions that they would not have otherwise undertaken without the goal (either a negative or positive goal, or sometimes both). Having that singular focusing objective can help to pull people into action.

Of course, the potential cost of such unified sense of action and direction can literally be maladaptive behaviors, and there's a question of whether a bad action is better or worse than no action in any given context, but there's nuance there that I think makes something, though I'm not sure what.

Remember that the book itself is largely focused on systemic/institutional level thinking in terms of long term direction; it isn't written directly as a type of "self-help" resource on individual time management at smaller time scales. The book pretty much already assumes that you're involved and doing something, it focuses only on the target of that work and how you choose to explore (or not) through the space of possibilities and directions. I happen to think there are applications to more low-level aspects of time management, but that's not something directly addressed in the book.

Moreover, I think "Stay open to possibilities" isn't quite the right phrasing, because that suggests that you're doing something and then just keeping an eye open for something interesting that might come along. I think the book is really saying, "Choose to expand possibilities," or something like this. I think the book is recommending that you don't just watch for opportunity, but actively drive your direction through the lens of opportunity/possibility. Put another way, that's probably like saying, "Hunt for the opportunities." It's an active, rather than a passive thing, and it's meant to replace the use of longer term/ambitious goals, though *not* shorter term, mundane goals.

To hop a little on the questions that Christopher brings up, there are lots of places in life where you may be in a job you want to be in, with responsibilities you want to have, but where those with influence over how you do those things are introducing things which are hampering what would be the best way to do the work. Some really common examples of this are obsessively unrealistic or unconsidered goals driven by metrics which are introducing perverse emergent effects within the organization. In such cases, it's often a good thing to have some strong reasons to push back against such things in a form that you can externalize from yourself and your own "opinions."

Likewise, we may have an inkling as to some direction or approach we might like to take, but finding a way to externally discuss and, in particular, put those intuitions into some external framework can be very valuable in allowing us to move from a lack of definition and precision into one of intention and clarity.