For one thing, even though we have big heads, we can’t hold enough in our minds all at once to make sense of the world, not even close. When we think things through, we have to slowly chunk up our concerns into categories, and then higher categories, and higher ones, until we end up with few enough chunks that they all fit in our minds at once. It turns out that our simplification is a dangerous activity if you are really trying to do the right thing.

In the real world, our decisions impact our lives according to our unique situations – specifics matter, yet simplification glosses over specifics. Plus, the thoughts and feelings that guide our decisions are highly interconnected by their nature. At the most basic level, if you spend time on one thing, you have less time for another. One level up, if you attend to one aspect of your life, the others fade from your attention. Some levels up from there, if you hold one area of your life as the most important, than the others are less important. And so on. Those interconnected relationships are enough to boggle our minds, and if we put our unique and changing life situations on top of it all, we quickly look for an easy way out, a generic checklist, an automatic reminder, a rule of thumb, a trusted bit of conventional wisdom. Also as a result of those simplifications, we end up with enough biases in our thinking and intuition to inspire a Nobel Prize, and to give us pause.

The news rings with scientists who are chipping away at the problem. However, as the Nobel laureate Daniel Kahneman pointed out in a recent appearance at the Singularity Summit in San Francisco, despite forty years of study he still cannot avoid the biases in thinking and intuition that he has studied all his life. Isolated lab experiments and tidy stories are true and make sense but still leave us without a clear map we can apply to our unique situations. For better or worse, our world and our minds are so interconnected that even Nobel Prize winners find that it is still hard to figure out the right thing to do.

I’m a geek, so I tried to figure out how big the gap is between choosing a single ‘most right’ path and the decisions we face in our real lives. To do this, I ran the numbers on the prototype Wahanegi algorithm. At the moment, it takes into consideration only some of most prominent scientifically proven aspects of happiness and our cognitive biases. To do that, it looks at ten areas of our lives across fourteen rankings of priorities and motivations. Each unique set of priorities and motivations represents a story, a path our lives can take. It includes more aspects than we consider in our day-to-day lives, but not so much to boggle the mind, right?

Unfortunately, no. Even such a simple view into our lives is incredibly complicated. In fact, Wahanegi’s relatively simple algorithm considers at least hundred times more possible stories than particles in the universe, or 1 followed by 89 zeros. If you are a visual person, that looks something like this:

100, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000

No wonder it is so hard to figure out what to do.

And that calculation is just one example of the general impossibility of picking the “most right” path. Here are a few more:

• Every time we decide, we cut off many life directions on purpose, and by accident we also slash huge swaths of life that we never even considered. Without knowing what else might have happened, we can’t know if we did the right thing.
• We are scientifically proven to be terrible at estimating the chances and results of our decisions, and at the same time we are overconfident in our ability to get what we want and overly afraid of risking what we have. So in this sense, the more carefully we consider the decision, the more likely we will confuse ourselves and end up heading in a certifiably wrong direction.
• Even if we had magically perfect knowledge of the chances and results of our decisions, statistics are not about you, they are about a theoretical version of you who can make decisions a zillion times to see what happens X% of the time. Not even Einstein could use statistics to predict what will happen to you as a real person. Remember – lies, damn lies, and statistics.

Obviously there are examples where statistics are useful, and we should make use of them to help guide us. I saw my fraternity brothers do well bringing down the house by counting cards in Vegas, and we watched an incredible team of scientists and engineers made a bunch of good decisions that just landed a robot named Curiosity on Mars ‘against the odds.’

But as difficult as those challenges were, it is still easier to figure out the count at a blackjack table, or the tensile strength of a titanium wire, than it is to figure out how much happier you will be if you quit your job, or get married, or move to a new city.

So instead of worrying so much about the right thing to do, we should shift our focus to doing what is wise and being compassionate while we’re at it.

My first attempt at describing the happiness algorithm starts with an equation, which feels just right as I briefly revel in uber-geek mode before the imperatives of more broadly accessible marketing copy take over:

Happiness Balance = Positive Motivations – Negative Motivations – Tension

Positive motivations move us towards things. They regulate our lives to seek things we want, appreciate what we have, prioritize what we need, give what we can. They benefit us by pulling us towards something in particular. Confusingly, they do this mostly by reducing our motivation to do other things that conflict. This can make them a painful source of unintended consequences – by motivating ourselves to move in poorly considered directions we can wreak havoc by accidentally demotivating ourselves in other areas of our lives. However, this also makes them relatively easy to change, since we can find where they point and decide to point them somewhere else.

Negative motivations move us away from things. They regulate our lives to avoid what we don’t want, fear loss of what we have and what we need, give nothing away. They benefit us by pushing us away from something in particular. Confusingly, they do this mostly by increasing our motivation to do other things, and in that capacity scientists have measured them as perhaps two to five times stronger than positive motivations. They are rather hard to manage, especially since it is tricky to get our hands around something that can be found almost anywhere but where it came from. As a result, they can do things like use the fear of a tiny harmless spider to run us smack into a big brick wall. However, this also makes them a clear sign of danger – they always drive us forcefully away from something worth avoiding, and they never help us figure out where to go instead.

Tension happens when conflicting priorities arise in our lives. It is not a conflict when one thing is more important than another, or when one thing is more meaningful than another…such decisions are easily made. Confusingly, conflicting priorities happen when one part of our lives is more important and another part is more meaningful, or when we think more about one area and spend more time and energy on another, and so forth. Strange as they may seem, those situations happen often. Something that was once time-consuming and important loses its importance but keeps consuming our time. Old automatic behaviors distract our minds from necessary dreams of what comes next.  Something ignored suddenly becomes meaningful. Tension means we have a difficult but significant decision to make, and the longer we wait, the more small related decisions rise up and entangle us. But just as ongoing changes in our lives cause tension to arise, we can make decisions that cut through the tension and clear a path.

The happiness equation is a balance between these three elements. Looked at over our lifetimes, it says happiness is about moving purposefully towards things without being pushed forcefully away from things nor being entangled by tension.

If happiness were just an equation, then we need know nothing else. To increase our balance of happiness, we just increase our positive motivations, decrease our negative motivations, and reduce the tension in our lives. It tells a good story. It sounds so easy. It feels like a book. Be grateful and our positive motivations will increase. Exercise and our negative motivations will decrease. Believe in religion and we will reduce the tension in our lives. Scientists have proven that all of those things do, in fact, work to some extent. All we need is a generic checklist and a series of reminders and we will be happy, or at least happier.

Unfortunately, even though the happiness equation helps compare our situations and measure our progress, just like the printed pages of a book, it struggles to tell us each what to do in a useful and personal way, estimate what impact our decisions will have on each of us over time, and figure out how to make good decisions we can commit to.

That is why the happiness algorithm has three other important elements:

• Our priorities and motivations are an interconnected network unique to each of us.
• Our motivations and tensions are not equal – some have greater impact on our happiness.
• Our decisions are much stronger and last longer when we contemplate and make them in the company of others.

Combine those elements with the happiness equation, build the resulting algorithm into a modern app, and you have Wahanegi.

They also give meaty, geeky subjects for several more blog posts.

A few months ago I realized I was designing a happiness algorithm. I suppose that should have been obvious, considering the mission of this company is to use technology to help people be authentically happy. But the creative process didn’t work that way this time – first I filled my head with a thicket of ideas that obscured the path, then I cut them away until the path was clear.*

Maybe I shouldn’t say I am designing an algorithm. It’s more like I am renovating one, bringing some ideas up-to-date, treating others in new ways and leaving the rest alone. That feels natural to me. I’ve always been someone more likely to see the possibilities in what lies around me, and less likely to create something from scratch. I am too optimistic to get distracted by the flaws in what already exists, and too impatient and practical to take on the risk and cost of the truly new, if such a thing even exists.

What is a happiness algorithm? It is a way to look at your life and decide on a direction to take, a story to tell, that increases your happiness long enough to be well worth the effort.

Some start-ups are trying to make the happiness math work by decreasing the effort required. They don’t need a happiness algorithm for that – in theory, if they can make one good idea easy, then we will come and be happy. That also jibes with the time-honored and well proved idea that happiness is based on simple principles. However, if being happy really were so simple, then we wouldn’t keep hearing about how simple it is all the time. The problem would be solved, and we’d all be talking about something else.

Rather than trying to reduce the effort required to obtain small things, Wahanegi aims at dramatically increasing our happiness payoff, and making the experience enjoyable even though it takes real effort up front. Being authentically happy is not easy, but we can do it. And if we do it right, the payoff for all of us is valuable beyond measure. Doing it right requires a special sort of algorithm.

I’ve been iterating the algorithm intensively and testing it with people, and the results are giving me goosebumps more and more frequently. That is exciting, and also frustrating, since it will take a while to build something real that lots of people can experience. Despite this blog posting and others to come, you can’t really describe what it is like to experience an algorithm in words and stories. Understanding how and why Google works doesn’t describe what it feels like to find just the information you were looking for. Similarly, describing how and why Wahanegi works is not the same as seeing your life in a new way and feeling a path open for you.

But it is pretty good blog fodder nonetheless. For instance, the next blog post about the happiness equation is already up.

*Once the path became clear, I stopped blogging, I left Facebook alone, I began making things and showing them to people. Just like that, my motivations had a clear run, and I started doing what obviously needs to be done. I knew that’s how it happens, the happiness algorithm is based upon that aspect of human nature, but it still felt like a discovery.

Two months later, I have questions and tasks that are well beyond what I can handle on my own, and so I’m finally writing the pitch and business plan to raise money and attract more people to help. I knew that would happen too, the happiness algorithm relies on other people. I’ve been part of new businesses many times before; nevertheless it feels scary and confusing and embarrassing and awesome every time, even this time – doing something you care about is like that. That’s probably why I like it so much.

In part, that process of scaling up the business is also why I am blogging again, so new people can learn more about what we are up to. I also want to bury the Facebook stuff under more information about Wahanegi to cut the distraction. I would drop those posts, but a couple hundred people still read them each week, so I’m leaving them up until Facebook comes clean.

Are you a small company that is planning to advertise on Facebook? Do you already advertise on Facebook but want to get more out of your money? Then I have some free advice that could save you thousands of dollars.

Before you read this, you should understand I am making two assumptions:

• You have already done some reading and got advice about Facebook advertising in general, and it makes sense for your company.
• You know what customer segments you are going to target with your advertising, especially Geography, Age, Gender, Education and any key interests.
• You are planning to use Facebook advertising to drive people to ‘like’ your Facebook page and engage with your company on Facebook.

Hopefully the first and second points make sense. As far as the third point, in my opinion you should not use Facebook to drive people to your website. For one thing, there are far more effective ways of doing that, like search advertising and even regular display advertising. In addition, there are real reasons to be suspicious about the effectiveness of Facebook advertising when used to drive people to external sites.

So, you already know you want to use Facebook to drive customer engagement in important customer segments for your small business, and now you want to know how to do it as efficiently as possible. To do that, you need to understand that there are two types of people on Facebook: people who regularly click on lots of ads without a lot of true interest in the ads, and people who rarely notice or interact with any ads except when they are really interested. Most of the people you want to reach are in the second group, which means it takes time and effort to get to them. Even worse, the eager people in the first group will flood in at the beginning of your campaigns and use up all your advertising budget before you have a chance to get to the folks you really want.

Dealing with those two groups separately is how you save money. You first have to ‘flush out’ the eager folks as cheaply as you can, and then you make the most of the incredible reach of Facebook by spending more money on clicks from folks that you are confident are really interested. Here is how to do it:

1. Create ads targeted however you want and pay the CPC bid that Facebook recommends. It seems you have to do this for Facebook to give you inventory in the first place.
2. Once the ads are approved and have collected a few clicks, drop your bid by 50% or so. Wait until you get a few more clicks and watch as your click-thru rate rises.
3. After your click-through rate either doubles or goes above 0.1% (whichever is higher), then drop your bid to 90 to 95% of your original bid.
4. Watch as the clicks keep coming in for a few days, and your click-thru rate climbs perhaps as high as 2% or more.
5. Over time, your impressions will decrease. When the number of impressions per day drops below 10% of the rate you saw in Step 2, then raise your bid again to the recommended range to get more impressions.
6. Repeat Steps 2-5 a few times. If you create variations of your ad that use the same copy and image but slightly different targeting rules you can get even better results. This may take a couple of weeks.
7. Once the ads seem “burned out,” then put your bid back to the normal range and let the campaign run as long as you like.

I validated this by proving we could generate about 5,000 likes for our Facebook page for a little less than $200, or about $0.02 a click. The people we collected were essentially the same as the people we collected when paying $0.20 per click. Since I was just experimenting on a shoestring budget, the fans we collected mostly folks from the Philippines, India, Pakistan and Bangladesh. However, some later tests show this method also seems to work in the US and the UK, though at higher CPCs.

I call it the ‘Facebook Flush’ because if you follow these steps, you will have flushed out all the eager clickers in your segments for a low price, and then your ads will be running against normal people who don’t click on ads very often. That second stage will feel a bit depressing after your awesomely high click-thru rates and cheap prices early on, but that’s reality.

I am publishing this because I believe that Facebook misled me and is misleading other advertisers, and I don’t want you to fall into the same trap.

———————————————————

If you found this helpful, then you can help us by trying the Wahanegi Beta.

Wahanegi helps people like you make wise life decisions.

“I feel happy. It made me realize the answer was already inside me. Wahanegi is extremely helpful, and I strongly recommend it. I like it.”

Are you facing a big life decision? Try the beta today, it’s anonymous, free, easy and effective!

Unfortunately, I felt the need to write one more posting about Facebook advertising. It is unfortunate because our business is about apps to help people change their lives for the better, not about advertising, and I hate wasting time. However…

When I read Rory Cellan-Jones’ partially correct and rightfully surprised BBC article about Facebook advertising last night and then Mike Butcher’s more pithy but somewhat less thoughtful insider TechCrunch dismissal of his findings, I decided I had to follow up.

The short summary of the problem is that some people who use Facebook ‘like’ huge numbers of things with relatively little discrimination. It is because they use Facebook more like most of us use Twitter (or like teenagers used to use MySpace before the fall), and the new Facebook interface encourages them to do it. I call them ‘booklicants‘ because at first I thought they were fake profiles, just like the BBC did. But Rory Cellan-Jones is wrong, and so is Mike Butcher, just like I was.

I have previously written about how to avoid the problem the BBC found, how this problem may represent a material financial risk for Facebook, and how Facebook knows about the problem and even exacerbated it with their new user interface and yet has a policy of placing the onus and blame on their advertiser customers.

So far there aren’t very many of these booklicant people in the scheme of Facebook’s sea of hundreds of millions. From what I can tell, they tend to exist in countries where the new Facebook interface has been in place the longest, so I suppose we should expect to see more of them in the US, UK and so forth over time. However, they already represent a VASTLY disproportionate percentage of the clicks paid for by advertisers compared to their population.

Facebook knows they exist because 1) I told them, 2) they recently thwarted a class-action lawsuit on behalf of advertisers that is now under appeal and 3) they seem to have an algorithm that invalidates clicks after a booklicant likes a truly huge number of things, but doesn’t retroactively invalidate all the clicks by that user. If my analysis on that last point is right, then it means they are knowingly taking money from advertisers for clicks that their own internal algorithms show are almost certainly invalid.

This problem does not hit most advertisers very hard on a percentage basis, but unfortunately it hits smaller advertisers hardest. That is not only because they may be less sophisticated and do a poorer job targeting ads like the BBC did – Mike Butcher is right about that, even if he is wrong about the nature of the underlying problem. It is also because they spend less money.

If you only have $1000 to spend, even if you target it carefully, many of the first ‘likes’ you will get are from people who like a lot of things not because they actually like the ads or the company but because 1) they like to collect badges and 2) they believe it will change the stream of content they receive. Both are reasonable reasons to click from a user perspective, but very low value from a small advertiser perspective. Unfortunately, the small advertiser has to pay the same price for those low-value clicks as they do for the more meaningful clicks that will come later as the campaign progresses. And even worse, the small advertiser will see their click-thru rate drop very rapidly after the first couple days as those click-happy ‘booklicants’ exhaust themselves. That encourages the advertiser to refresh the ads or refine their targeting, which gives Facebook a chance to bring in a new set of users who include some ‘booklicants’ who will like the ads quickly as well. The result is that if you spend less than $1000 on Facebook advertising in most any demographic but especially in countries where the new interface has been around for a while, you will be wasting a meaningful percentage of your budget on people who don’t really like you the way you think they do.

Big advertisers pay ‘too much’ for those early booklicant clicks as well, but their campaigns are so large that it isn’t a big deal for them. Plus, like Mike Butcher, they are jaded and already “know” there is a lot of click-fraud in the world…they’ve seen it all before with Google and SEO scams and such.

However, this is different, and folks like Mike Butcher don’t really “know” as much as they think. In this case, Facebook has nearly perfect information, since these users have to log in, and most of their clicks are tracked. That means Facebook knows full well that there is a class of real users who click a lot, and their algorithms do seem to attempt to trim some of those clicks, even though they don’t invalidate clicks retroactively. It doesn’t seem to constitute fraud, since all these clicks are from real people. However, it is certainly misleading to advertisers to charge the same price for clicks from people whose behavior is dramatically and consistently different from other users in a way that their own algorithms are designed around. That is especially true when your algorithm only invalidates some clicks from these people. And it is even worse if it is a practice that has gone on for a long time and is getting worse, as it appears to be.

I validated most of this by proving I could generate about 5,000 likes for our Facebook page for a little less than $200, or about $0.02 a click. The population of people I collected was essentially the same as the people I collected when paying $0.20 per click. The method below also seems to work in the US and the UK, though at higher CPCs. Here is how I did it:

1. Create an ad targeted however you want and pay the CPC bid that Facebook recommends. It seems you have to do this for Facebook to give you inventory in the first place.
2. Once it is approved and has collected a few clicks, drop your bid by 50% or so, wait until you get a few more clicks and watch as your click-thru rate rises.
3. After your click-through rate either doubles or goes above 0.1% (whichever is higher), then drop your bid to 90 to 95% of your original bid.
4. Watch as the clicks keep coming in for a few days, and your click-thru rate climbs perhaps as high as 2% or more.
5. Over time, your impressions will decrease. When the number of impressions per day drops below 10% of the rate you saw in Step 2, then raise your bid again to the recommended range to get more impressions.
6. Repeat Steps 2-5 a few times. If you create variations of your ad that use the same copy and image but slightly different targeting rules you can get even better results. This may take a couple of weeks.
7. Once the ads seem “burned out,” then put your bid back to the normal range and let the campaign run as long as you like.

I call it the ‘Facebook Flush’ because if you follow these steps, you will have flushed out all the booklicants in your segments for a low price, and then your ads will be running against normal people who don’t click on ads very often. It will feel a bit depressing after your awesomely high click-thru rates and cheap prices early on, but that’s reality.

I think Facebook should do this automatically, so let me end by sharing the last customer support email I received from Facebook about all this after my earlier blog posting:

From: The Facebook Ads Team
Date: Tue, Jun 12, 2012 at 9:06 AM
Subject: Re: Help with Your Ads Manager

Hi Erik,

I hope you’re doing well. I reached out to an appropriate team to look into.

I understand your concern regarding your Facebook Ads. However, we aren’t able to pursue this any further without detailed click logs from you. Please contact your web hosting company directly if you have questions about how to obtain these server logs.

Our records show that you’ve only been billed for valid clicks. Your server logs will show us what you’re seeing on your end, which, when compared to the traffic we’re sending to your site, will help us identify whether any invalid activity is occurring, and help us clarify for you why you may be seeing discrepancies if not. Without this data, we simply aren’t able to give you any more information about the clicks you’re concerned about.

Please note that these investigations take a significant amount of time so it could be weeks until we have any updates after you send us the server logs.

Plus, it actually make sense that people who already like a lot of pages will continue to like more pages. Kind of like some users tend to click on ads more than others.

Thanks,
Neil
Global Marketing Solutions
Facebook

Yep, you are right, Neil, and so are the MBAs and/or lawyers who wrote and/or reviewed this response before you sent it.

The fact that they again asked for my logs when the entire problem is on their servers in their app is completely unforgivable in my mind – if I didn’t know better, I might have wasted time trying to comply with their request, or more likely just given up. When I look back to my experience running Acrobat.com as we rapidly grew to millions of users, we would never have treated a customer that way. So, instead of just giving up or giving in, I came up with the Facebook Flush and shared it with y’all.

But Rory and Mike, you guys don’t have it right. So please do a little more investigating, perhaps in partnership since Rory started the investigative work and Mike has the industry expertise. Facebook will probably tell you they can’t share their algorithms because they are theoretically sensitive for security reasons. They may also claim they can share them because of an ongoing legal case. Don’t give up, keep asking questions.

For instance, Rory, how many ‘likes’ did all of your fans generate for other advertisers, what is the likely price paid for all those clicks, and thus what is the total money that Facebook collected based on the unusual behavior of those folks? How many of these people exist in the world? I made my own guesses here – I am probably wrong, but the number is big either way.

And Mike, figuring out that number would be a real story no matter what you think of the BBC .

How do you answer a 5-year-old who asks “How much longer until we get there?”

As I was working on the beta version of our long-term decision assessment today, I realized that part of the algorithm can be applied to a question I’ve thought about most of my life: How does our perception of time change as we get older? And if nothing else, the answer to that question helps shed light on the summer road trip conundrum.

I think the answer is related to another common question around our house: ”Daddy, how old is Ruby?” Since Ruby is a puppy, the answer is always in explicit units of human years or dog years. For simplicity around the house, we use the 7:1 ratio as a rule of thumb, meaning 1 human year equals 7 dog years. But anyone who lives around humans and dogs knows that ratio is not quite right, especially when comparing puppies and little kids, and so vets put together a handy chart to provide a more accurate translation. Thus Ruby is ten-months-old in human years and twelve-years-old in dog years. That seems about right.

Everyone understands what it means to translate age between dogs and humans, and because dogs and humans empathize with each other the translation is a strangely interesting topic of conversation.

Why not do the same for people?

Back in college I made up a rule of thumb that our perception of time depends on the doubling of our experience after age 4, meaning that the time periods between ages 4, 8, 16, 32 and 64 all feel roughly the same. I came up with it because I wanted to know how long my life would feel if I lived as long as my Grandpa Lee, a robust man who died in his late-90s. By my calculations, living from birth to my mid-20s would feel roughly the same as living from my mid-20s to late-90s. At the time that prediction had the ring of truth, some of which still echoes around my head, though it seems less important now.

My recent explorations of the current state of cognitive neuroscience and behavioral psychology give me some new data and perspective to generate my own chart. This one is for parents, with the hope that at a minimum it will spark interesting car-trip conversations with impatient 5-year-olds, and perhaps provide a framework for empathy between parents and progeny, or more generally people young and old.

So, if you are a forty-year-old parent, teacher or manager of young employees, one hour for you feels like:

12 hours for a three-year-old
7 hours for a five-year-old
4 hours for a nine-year-old
3 hours for a thirteen-year-old
2 hours for a nineteen-year-old
1.5 hours for a twenty-five-year-old

You can also extend this into the future if you are a forty-year-old child of elderly parents or a caregiver of some sort. Thus, an hour for you feels like 30 minutes to a 70-year-old and 20 minutes for a 90-year-old.

The algorithm I used is based on how learning, development and sleep patterns change over time, so I think it models reality in some sense. However, to keep things on the level, I do not believe is reasonable to translate literally between the perceptions of children and adults any more than it is reasonable to expect a ten-month-old puppy to act like a twelve-year-old child. And the fact that time flies when you are having fun and a watched pot never boils also throws a wrench in the works when you driving a beautiful mountain road with a couple of kids in the back seat. Perception is a tricky thing.

Nonetheless, the next time you are asked “How much longer?” maybe asking “Do you mean in parent minutes or kid minutes?” will put things in perspective and buy you some time.

If you set out to build a breakthrough product that makes people authentically happy, you need to know what happiness is and what it isn’t, and how people tend to get there or not. If you are serious about it, you also need to know something new, not so easy considering that the pursuit of happiness has been a major human activity for a few thousand years at least. And business being what it is, you also need to know what people will pay for.

In other words, to build a happiness product, you need to know:

1. What it is…and what it isn’t.
2. How people get it…and why they fail.
3. Something new in the form of an innovation or two.
4. What people will pay for.

The past six months of intensive thought, research and conversation has turned my original gut feel for happiness into a framework that is simple and comprehensive enough that it smells of truth and usefulness, at least for my purposes. And I think I have a good enough sense of the product and business. Fun stuff. Let’s go.

What Happiness Is

The framework says that for most people in most times and places:

• Happiness is a combination of Fun and Wisdom.
• Unhappiness is a combination of Enslavement and Foolishness.

I can imagine spending a lifetime illuminating those two sentences, perhaps changing the words a bit along the way. For instance, my wife and some friends didn’t like the word ‘slavery,’ hence Enslavement. I’m quite open to other suggestions if you have them, in the interests of continued marital bliss and phenomenological accuracy. In addition to ‘slavery’ I eliminated drudgery and hunger, bondage and subjugation along the way…I bet there is a perfect German or Hebrew or Sanskrit word for ‘the feeling of being forcefully beholden.’ Any takers? How about a word for what you get when you combine Enslavement with Wisdom? Or Foolishness with Fun? The tentative candidates are Tyranny/Duty and Nonsense/Luck.

I feel a bit odd declaring such sentences since many people before me have thought about the topic long and hard. On the other hand, very few of them benefitted from the crystallizing motivation to create a cloud-mobile-social app to make people happy, unfettered access to the world’s knowledge via Google, and an incredible network of friends and acquaintances from educational institutions, organizations and innovative regions the likes of which the world has never seen. Said another way, I got here by combining the best of Eastern and Western philosophy with the latest in neuroscience and psychology, throwing in a little poetry, MIT rocket science, HBS strategy and Silicon Valley chutzpah for good measure. And in the end I’m trying to create a product that works, not a theory of everything.

How to Get It

This simplified framework gets people from Unhappiness to Happiness three ways:

• Path 1 – They take foolish risks that pan out, and then seek purpose in their lives.
• Path 2 – They practice wise habits successfully, and then seek play in their lives.
• Path 3 – They decide to be happy, believe they can do it, and succeed no matter how hot or cold it gets.

I can imagine spending another lifetime illuminating those three sentences. But for now I’ll just make three lame jokes.

• For many Americans, Path 1 leads to Las Vegas, Path 2 to Des Moines, and Path 3 to Jerusalem.
• For many geeks, Path 1 leads to Sand Hill Road, Path 2 to the East Bay, and Path 3 to San Francisco.
• Paths 1 and 2 are paved with good intentions, and if you make the wrong decision then Path 3 ain’t all wine and roses either.

Said another way, when it comes to happiness, the joke is too often on us.

An Innovation or Two

Fortunately, our world has lots of resources and we do a pretty good job using them to learn and create good new things. In terms of innovation, it seems likely that the biggest cloud-mobile-social changes in our lives are yet to come, and in parallel it seems that scientists are on the verge of a revolutionary new understanding of the mind. I believe there is something new here to play with.

Of course believing in newness doesn’t make it clear what to do, but it does motivate me to persist. On top of that, I have a lot of experience building good and bad products, and these past six months feel exactly how the first step in building an excellent product should feel. Now I hope Wahanegi’s innovations and product success will help give proof of the human capacity for progress.

As product people know, you have to show to tell. It takes time even to build mock-ups and prototypes, so I ask for a little patience. However, it will come in stages, so you won’t have to wait forever.

What People Will Pay For

After six months, a dozen major iterations and four pivots including this one, here is the refinement of Wahanegi:

Wahanegi helps people make long-term decisions that will increase their happiness and change their lives for the better. Our free Assessment tool helps people categorize their life situation and find which long-term decisions will be easiest to make and which will have the greatest impact. Our premium subscription service provides a website and mobile app to help people Frame, Make and Monitor their long-term decisions in a way that will increase the likelihood of success and positive impact. The initial service provides community-based feedback and guidance through the process, and over time we will also develop a group of mentors who can give a sort of ‘advice from the future’ since they will be very similar to our customers only 20 years older.

Those four sentences will probably take four years of work to come to fruition, but now we can finally start building something. On to the Assessment!

If you’d like to be a beta tester for the Assessment, please…