Every book has co-authors. These co-authors are spouses, kids, parents, editors, friends, heroes, and even other authors of the same genre – all of whom play pivotal roles in creating the final reading experience. Every author stands on the shoulder of giants. And, as is often the case, the most important shoulder tends to be that of the spouse.

Of course, the book is just a metaphor for life and every project we have the privilege to work on.

It is easy to forget this and get caught up in the “self made” myth. It is also easy to over estimate our capabilities and the roles we play on the journey.

This is a thank you to the many co-authors of this blog – with a special nod to that most important shoulder. I am more grateful than I can possibly express.

I hope you find time to send your co-authors a thank you this weekend as well.

Living in the present – in moderation

At the end of his book on timing – “When,” Dan Pink shared a recommendation on living in the present. He points out that living in the present may not the best strategy at all times – despite the advice of spiritual gurus.

Instead, he suggests that we’re better off integrating the past, the present and the future as we live our lives.

I thought that was a profound insight. And, it is one I am beginning to stumble upon myself as part of my journey to engage with engagement/mindfulness. There is undoubtedly a place for living in the present. But, spending time reflecting on what happened is a source of great learning. And, identifying with our future selves helps us move forward with purpose.

I read once that zen masters believe that the essence of zen is doing one thing at a time. That’s increasingly where I find myself ending up. There’s a place for some reflection, some day dreaming about the future and getting things done in our lives. They co-exist and, in moderation, balance each other out.

The key, I find, is to make peace with the process of balancing and to be fully engaged with it – one thing at a time.

Who sends you email?

My Gmail account gets two kinds of emails – emails from brands and cold emails from people I don’t know.

This wasn’t the case when I first set up my Gmail account 12 years ago. A key part of the value proposition back then was to hear from friends and family without having to worry about storage. Now, that happens almost entirely on Whatsapp.

As a user, I can feel a difference in my connection with my gmail account. This is especially the case because I can contrast it to my [at] email account – the default “reply to” email account for this blog. I look forward to every email on that account and it fills me with nostalgia about what email used to be. It is a dying breed.

Of my two remaining use cases (brands, cold emails), I suspect brands is the dominant use cases for most people.

That, then, brings forth a few interesting questions – would email, the product, be different if it was designed for communication with brands? For example, is there value in the “promotions” tab? Is there a better way to display sequenced offers? Could subscriptions (the more personal version of emails from brands) be given a separate, more personal area? Could ads be redesigned to better suit this new medium?

Email still remains one of my favorite mediums for communication. But, the design of most personal email clients seems to reflect use cases from a decade ago. It may be time for a rethink.

How much of your job is sales?

How much of your job involves –

  1. Persuading executives to fund your projects?
  2. Inspiring cross functional team members (who don’t report to you) to help you achieve your goals?
  3. Evangelizing your projects and teams across the organization?
  4. Attracting external talent to come work on your projects?
  5. Gathering support for key priorities from other teams?

Of course, this list doesn’t even count time spent trying to get actual customers pay for your work.

In workplaces with lesser hierarchy and more network based work, more of us spend more of our time in sales than we realize. (This isn’t the aggressive “always be closing” type of selling we picture. It is a softer, subtler version built on attunement, buoyancy and clarity. More on that another day.)

And, yet, it is likely we don’t spend much time strengthening our selling muscle. Nor do we realize how strong this muscle actually needs to be.

The first step, then, is for us to appreciate the importance of selling to our success.

With this acceptance will come change..

User feedback and sophistication

“The least sophisticated users tell you what you need to simplify and clarify while the most sophisticated users tell you what features you need to add.” | Paul Graham, Hackers and Painters 

Most things we build for other people – whether it is a business or presentation or product – will have consumers at both ends of the sophistication spectrum. The first step in synthesizing user feedback is to be clear who you are building it for – eliminate feedback that isn’t from your target audience.

Second, assuming you’ll still have users on both sides of the sophistication spectrum, building products that enable both novice and power users is key. And, an important step toward making that happen is to listen carefully to feedback from both ends of the spectrum. Expect your novice users to push you to simplify and expect your power users to do the opposite.

Then, it is on you to strike a balance.

That’s, of course, how we get made.

Getting a degree versus getting an education

Too often, we focus conversations about learning plans around getting a degree. There is an implicit assumption in these conversations that getting a degree and getting an education go together.

But, that need not be the case.

You can get a degree without getting an education – there are plenty who do. And, conversely, thanks to books and the internet, you can get an education without getting a degree.

There are good reasons to get a degree. Moving geography, improving career prospects, learning from top Professors and a motivated peer group, taking a break, etc., could all, in combination, be good reasons. But, if the only reason to get a degree is – “I want to learn management” or “I want to learn machine learning” – I would reconsider.

We have more options to pursue learning in subjects we are interested in than ever before. We can buy books, subscribe to online courses, create a peer learning group around these materials, start a blog sharing insights or do all of these together.

We can choose to not get the business of getting a degree interfere with our desire to get an education.

Optimizing for synthesis and reflection over reading and listening

Our lives right now are built around consumption. Media companies have somehow convinced us that there are few things that matter more than staying up to date. So, we get free newsletters with stunning content and, generally, a link to subscribe to get more.

Media personalities (including venture capitalists and star entrepreneurs) all have podcasts and blogs for us to listen to. Many of this stuff is actually interesting.

There are more “summits” about various topics with lists of YouTube videos to watch than ever before.

So, naturally, we have more of us walking around wishing we had time to read, listen and watch all this content. And, aside from the fact that “catching up” is a fool’s errand (it is impossible), we are better served by doing less consumption and more creation. Creation contributes more to learning and happiness than consumption.

How do we that? Pick the best long article, podcast or video and, instead of moving to the next one, substitute that time with time for synthesis. Feel free to take notes during the process. However, these notes are only useful if we take the time to synthesize them afterward. Good synthesis, in turn, requires time to reflect.

And, if it is all too hard to resist the temptation of clicking on the next article or video, shut off the internet and get hold of a book on a topic you like. Then, repeat the above process.

We don’t learn effectively when we consume. We learn when we synthesize and reflect.

In the age of consumption, it is worth reminding ourselves that more is not better. Better is better.

Why we expect crypto to be a big deal

It is easy to look at all the frenzy around Bitcoin and cryptocurrencies (I prefer using crypto tokens or simply “crypto” instead) and wonder – why is this all a big deal? We are never far away from talk of a decentralized, government-less world. If that all seems far fetched, that’s understandable.

The crypto boom is not a function of idealist technologists chasing some fictional future. Instead, when you boil it down, it comes down to two reasons – databases and incentives. Let’s work through 2 questions.

First, what do Oracle, SAP, PeopleSoft and Salesforce have in common?

Aside from being worth billions of dollars ($300B in market cap), each of these companies are/were database companies. There’s a lot of money to be made in databases.

We also know there’s a lot more money to be made by having the right kind of data. Google, by virtue of its near monopoly on American and, to a large extent, global search data is worth $750+ Billion Dollars. Facebook is worth in excess of $500B thanks to the fact that it knows more about the world’s adult population than any institution in history.

Next, what do stock prices, bonuses and taxes have in common?

Each of these are economic incentive systems. They drive hundreds of millions of people to work every day and ensure we have the means to fund the infrastructure to do so.

This combination of the value of databases and the data they hold and the power of incentive systems to drive behavior are why we expect crypto to be a big deal.

The challenge with a decentralized database.
I like revisiting the technological innovation underpinning the blockchain.

Until the blockchain came along, it wasn’t possible to have a decentralized database. So, we’ve always had central database owners – typically large corporations or governments – who held tremendous power because of the value of the data in them. (In rare cases, these databases are owned by foundations, e.g. Wikipedia. The challenge is that there are very few foundations because such foundations need to constantly fight for financial survival. The allure of making lots of money with the data is too strong for most. Automatic hat tip to the founders of large open source projects!)

Financial incentives aside, it made sense to have centralized database owners because decentralization, on the face of it, would present a few challenging problems. What if the folks maintaining the database changed records?

Enter the “crypto” part of the blockchain. Satoshi Nakamoto’s famous white paper laid out the design for decentralized databases with cryptographic security. That, in turn, has 3 characteristics (H/T Alex Rampell from a16z) –

  • Records can’t be faked / No alchemy
  • Records are immutable / No alteration
  • Owner/signer is unique / No impersonation

Now that we’ve solved the security problem, there are two other issues with managing creating and valuable databases. First, maintaining a database costs a lot of money. Facebook pays massive infrastructure costs to hold all its data. (Of course, it turns out that the value of all data far exceeds the costs.)

And, second, how do you get the sort of data that Facebook has managed to accumulate anyway? Facebook’s strength comes from the network of users within Facebook and the current regulatory regime around user data.

Let’s talk about the latter for a second. We live in a regulatory regime where corporations own user data. If this changed to a regime where users own their data, users could, in theory, take all their data and port it to a new social network they wanted to participate in with their friends.

The bootstrap problem. In the absence of user focused regulation, Facebook’s network strength is nearly impregnable. And, every network that attempts to compete faces what is known as the bootstrap problem. The bootstrap problem illustrates the challenge of starting a new network. Networks become valuable when you have more users. But, how do you get to critical mass?

This is particularly critical where blockchains are concerned as it takes a lot of work (computing power, energy) to maintain these cryptographically secure databases. So, why would people do it?

This is where Chris Dixon’s excellent illustration comes in.

As Chris illustrates, crypto tokens (or “currencies” in popular language) provide financial utility to the early adopters of the network and help it get to critical mass.

Image you start Bitbook – the blockchain version of Facebook. You could imagine an incentive system that looks something like this –
There will only be a total of 100 BitTokens.
10 BitTokens will be given to early investors for a cash value of $10M to build the network. This, in turn, will be used to pay for servers and compensate employees.
10 BitTokens will be saved for employee incentives.
10 BitTokens will be kept aside for developers who add value to the system.
10 BitTokens will be owned by the founders.
Out of the remaining 60 BitTokens, 20 will be awarded to the first 2000 early adopters as an incentive to try the network.
The remaining 40 will be paid out over time to new users and users who bring value to the network.
What could you use the token for? Well, you could imagine a small entry fee, a small fee for the ability to send messages to people you don’t know and a small fee to buy and sell in the marketplace.
So, even if the token may not be worth much now, it could be worth a lot once the network has grown to a few million users.
Imagine executing a contract like the one above – you need a large group of lawyers and will need to sort through a multitude of contractual details. But, thanks to the blockchain, you can just trust the code.

We also know that these systems can work. Bitcoin is the proof-of-concept of this combination of an incentive system and decentralized database that has worked. Now, of course, there are multiple other blockchains that have followed suit.

Blockchains without a token/currency make little sense. Most big finance companies talking about the block chain are really talking about tamper proof databases. But, as you can probably tell from the above illustration, it makes no sense to have a blockchain without a token/currency. In the absence of this, there is no incentive for participants to maintain this cryptographically secure database.

(The reason “token” is more accurate than “currency” is because “currency” assumes general purpose use. But, a token in a blockchain tends to be constrained for use within that network.)

It feels good to contribute to the body of open source/creative commons work. But, we also want to be paid.

In a sense, the blockchain makes open source objects financially viable by converting networks into peer-to-peer marketplaces.

Tokens/currencies need good governance systems. Now that we understand how central tokens are to the blockchain, it is easy to understand why good governance systems matter. In a nutshell, this is what good ICOs /initial coin offerings are about – experimenting with governance systems to ensure the sustainable growth of their network.

2017 saw a crypto investment frenzy. While 95+% of the ICOs will end up having zero value, we will likely learn a ton about good governance systems from the 5% that do succeed.

It is also unclear to me whether the completely decentralized model will work broadly. Large open source projects still tend to have influential founders (Linux, Wikipedia, etc.). We’ll need more experimentation to find out.

A brief note about the experiment that is Bitcoin. Bitcoin is an example of one use case of the blockchain. It is the star of the crypto show right now. This may continue to be the case in the future – it is hard to say. But, it is worth noting that Bitcoin is also an experiment that was designed to test if we might be able to create a cryptographic currency.

However, that experiment seems to be failing. Instead, it is emerging as a potential “store of value” – to replace gold.

For people who find the it weird to attach value to a virtual concept, take a moment to consider that we picked a random shiny looking metal from the ground and assigned tremendous value to it. Then, there’s also the fact that this storage and transport of this arbitrary metal is hard. It is also hard to track.

Just like digital photos replaced their analog counterparts because they were easier to store, transport and track, what if Bitcoin was a digital upgrade?

I’m not positing that it is. But, it just might be. And, that option value is worth something to many people.

That said, it won’t matter a great deal if Bitcoin fails. For those who see the power of these decentralized database and incentive systems, Bitcoins rise has just spurred some much needed investment. There are numerous problems to be solved – chief among them are scalability and energy use. But, with the amount of venture capital funding the sector has attracted, it is only a matter of time before top engineering talent figures solutions that work. In the spirit of discussing incentives, money is a powerful motivator.

If Bitcoin doesn’t work, we’ll design the next cryptocurrency that works.

Or, as Nassim Taleb eloquently puts it

Bitcoin will go through hick-ups (hiccups). It may fail; but then it will be easily reinvented as we now know how it works. In its present state, it may not be convenient for transactions, not good enough to buy your decaffeinated expresso macchiato at your local virtue-signaling coffee chain. It may be too volatile to be a currency, for now. But it is the first organic currency.

But its mere existence is an insurance policy that will remind governments that the last object establishment could control, namely, the currency, is no longer their monopoly. This gives us, the crowd, an insurance policy against an Orwellian future.

Wrapping up. It is hard to discuss the potential of crypto without encountering ideas like the importance of decentralization, democratization and permissionless innovation. The believers will tell you that this is important – to make the world a better place and win back the internet.

But, solving climate change is important too. So is figuring out what happens to jobs in a post AI world.

But, as human beings, our behavior is driven by incentives. Currently, there isn’t a clear financial incentive to go work on climate change. So, there isn’t venture capital money pouring in and neither are undergrads hooking up computers in their dorm rooms to solve math problems to fix carbon emissions.

But, the world of crypto has that figured out.

And, when you combine powerful financial incentives with the inherent value in databases and the data they hold, you begin to understand why we expect crypto to be a big deal.

Links for additional reading

  • Beyond the Bitcoin Bubble by Stephen Johnson – on NYT (one the best long reads on crypto)
  • Chris Dixon’s post on a breakthrough in network design – on Medium
  • In code we trust – on NYT
  • The Blockchain man – on RibbonFarm (Fascinating)
  • Crypto boom funded by MIT – on Quartz
  • Trends in Cryptocurrency – on a16z
  • Alex Rampell on Cryptocurrencies at the a16z summit – on a16z (great overview)
  • Satoshi’s famous whitepaper – on
  • Nassim Taleb on Bitcoin – on Medium
  • A 3+ hour comprehensive podcast on how to think about crypto – on InvestorFieldGuide

Unbiased is overrated

We often seek unbiased advice or points of view. However, more often than not, unbiased is just a result of a lack of awareness of biases. Folks who are truly unbiased are few and far between.

Unbiased, as a result, is overrated.

I’d take biased and aware any day of the week.


Experiments and mis-steps

Waze suggested this an alternate route to work a few days back to avoid traffic on my usual route. In the spirit of experimentation, I thought I’d give it a try.

The route choice ended up taking doubling the amount of travel time. And, my instinct mid-way through the journey was to wonder what I did wrong.

Soon enough, it hit me that this mis-step was simply the cost of experimentation. If I’d reduced my travel time, I’m sure I would have congratulated myself for the intelligent risk. This result was just the flip side of that. The only logical action after an experiment like this is taking the time to reflect and learn. In this case, never try that route again was a good learning.

Constant experimentation – beginning with a hypothesis and ending with reflection – is a powerful approach to continuous learning. But, it also requires us to make peace with unexpected mis-steps.

Experiments and mis-steps go together. You cannot have one without having the other.