How to Make Espresso

Now that you have your lovely espresso machine (see our earlier post on some tipps about this), let me write down some lessons learned about the science of making excellent espresso (as it is a science, not an art).

First things first: Water.

Do yourself a huge favor and only use filtered or bottled water — it not only tastes better but also makes sure your machine doesn’t clog up. Espresso machines are delicate beasts operating at high temperatures and pressures. Using tap water with it’s usually high(er) level of calcium and other minerals can lead to build-up of scale which in turn will clog up your machine (and is a pain to get rid off). Personally I use a BWT Vida filter system — it’s specific filter tech makes water not only free of anything which leads to scale but also makes it taste much better.

Second: Measure.

Espresso is all about dissolving the solubles from your ground beans into water. It’s science — thus measure what you can. Start with measuring the amount of ground beans you put into your portafilter basket. Usual basket sizes are measured for about 18 grams — what you want to get, is a basket which is so full (after tampering the grounds down) that it barely touches the screen inside of your machine. The golden rule is that you want about as much space between your prepped puck and the screen that you can put a coin inbetween. I would experiment a bit to find the right amount of ground beans for your specific setup and the make a mental note of it. From then on fill each basked with the exact same amount of ground beans (as measured in grams).

Next you measure the amount of espresso you pull from your shots. The golden ratio is between 1:1.5 and 1:2. The former is typical for dark roasted beans (more of the Italian style), the latter for, what is called, Third Wave Coffee (i.e. the newer lighter roasts you find in most SF coffee shops these days). Put your espresso cup on a scale while you pull your shot and stop the shot when you hit the right amount. In my case I put 18.5 gram of ground beans into my portafilter and extract 37 grams of espresso.

Measure the time it takes you to get to that extraction — the golden rule is to aim for about 30 sec for the full extraction (i.e. the moment you start your shot until you reached your desired weight). If it’s shorter, adjust your grind and make it a little finer, if it’s longer make your grind a little coarser.

All of this is called “dialing in” — every barista does this at the beginning of her shift. It will take you a bit to find the right settings — the good news is that after you found the right settings, the needed adjustments from there on are minimal (but constant; I tweak my settings more or less daily to stay within those parameters).

Third: Puck Prep

Preparing your puck properly is important. Grind your beans into the portafilter or a transfer vessel (e.g. a small cup). Measure the right amount by weight (see above). As I am using a Niche grinder, which is a single dose grinder, I measure the weight of the beans I put into the grinder and grind a single portion. I am not sure if that works with your grinder but generally speaking I would not leave beans in the hopper – beans get stale within hours of taking them out of an airtight container (which means that you should store your beans in an airtight container once you took them out of the sealed bag). I would always only put as many beans into my hopper as I need for the espressos I am making. Leave the filled hopper to baristas running a busy café.

Distribute the beans using the Weissman Distribution Technique (WDT) — it is easiest with a portafilter funnel (something like this). It makes sure you don’t have clumps which inhibit flow as well as distributes the grinds more evenly.

Some people like to polish off the grinds with a tool like this — I, for one, do this. It creates a more even top surface. The actual usefulness is debated but I like the tidiness.

Once you have your puck prepped you tamp. If you don’t use a calibrated tamper (such as the Force Tamp), try to a) push down vertically without any wiggling and b) about the same force each time.

Fourth: Milk Steaming

It will take you bit of practice to make great microfoam. There is no way around it. But you can significantly shorten your learning curve — watch a couple of videos on YouTube (here are two good ones: https://www.youtube.com/watch?v=6YMgB61WyvE and https://www.youtube.com/watch?v=HIuHvciUS9g — both these channels are great channels to follow).

Use water with a drop of dishwashing liquid for practice – it foams nearly like milk and you don’t waste actual milk in your practice runs.

One pro-tip: Always do a quick purge puff of steam after steaming your milk. Milk likes to gunk up in your steam wand and has a nasty tendency to creep into the steam wand — a quick puff at the end of your steaming will prevent this from happening.

Have fun! It’s a bit of steep learning curve; you will get to good coffee pretty fast if you practice a bit and from there it is the eternal quest to get to the fabled “god shot”.


Let's talk about Making Espresso

You might know that I obsess over good coffee — specifically espresso. A dear friend recently asked about my recommendations on a home barista setup. I emailed him the following:

This is the best machine you can buy for less than $2k: Breville Espresso Dual Boiler

It is not cheap but easily outperforms anything in that price bracket on the market — superb temperature and pressure stability, commercial build quality (this thing stays with you for decades) and overall easy to operate (i.e. you will get great shots out of it). Plus it is a dual boiler which means that you have two boilers — one for pulling espresso shots and another one for steaming, with both boilers operate and heat at the same time, i.e. you can go from pulling shots to steaming without waiting for the boiler to heat up to steam temperature.

I am nuts, thus I bought a Decent DE1PRO — hands down the best machine you can buy for less than $10k (which is Slayer territory).

Equally as important as the machine is your grinder. Do yourself a favor and buy something great and don’t skimp on this — you will regret it and end up buying the high(er) end grinder anyway.

Not all that expensive and hands-down one of the best grinders you can buy is the Sette 270.

Quite frankly the only negative is the plastic look (which is only looks – the grind mechanism is solid as rock) and the noise (it is quite noisy when you grind – but then: You only grind for a few sec at a time).

If you want to spend a little more, get a Niche Zero — this is what I have. It beats the crap out of $3k+ grinders and is a lovely appliance. All the pro-baristas I know, have this thing at home now.

Lastly you will need a few accessories. Get a good steam pitcher for making milk – buy a Motta and call it a day. Splurge on your tamper and buy the Force Tamper – it creates insane consistency from shot to shot. Get a simple frothing thermometer to get consistency for your milk steaming. And get yourself a small, precise kitchen scale to weigh your shots (one of the best things you can do to get to great, repeatable results – you weigh the beans going into your shot and the shot itself; depending on the bean you aim for a 1:1.5 or 1:2 ratio at an extraction time of about 30-50 sec; depending on the bean again).

Good places to buy all this stuff:

And if you want to read up on all of this – this is the barista bible and a lot of amazing folks hang out on this forum (which also has great reviews, etc).


Alexa - or: The Importance of Voice

Ten thousand employees. That is the number of people working on Amazon’s speech assistant Alexa. Add to this all the people working on Google’s, Apple’s, Samsung’s and Microsoft’s speech assistants and you get a sense for how important these companies take “the next frontier in user interfaces”. And speech is not just convenient – it also fundamentally changes the way interactions between users and products and services will work.

Take batteries. We all remember the Energizer bunny. The little, fluffy pink bunny which never ran out of steam as he was powered by the world’s leading battery brand “Energizer”. When you run out of batteries next, do you believe you will say to your voice assistant “Alexa – order a pack of Energizer MAX AAA Alkaline Battery” or will it be “Alexa – order batteries”?

If you do this on the web today, the world is pretty much in order: Amazon dutifully shows you the number one battery brand on the planet high up in its product listings. But the moment you ask Alexa – which batteries will Alexa ship you? Of course Amazon ships you Amazon Basic batteries. In the US Amazon’s online marketshare for all batteries being sold is 97%! And it is not just batteries – it is category after category which is dominated by Amazon. From skin care (91% marketshare) to home improvement (93%) or cleaning supplies (88%) and many more.

And it is not just (online) sales. Coming back to our beloved furry friend, the Energizer bunny: Where we spent significant amounts of money on marketing and brand building – from the creative team which dreamed up the bunny to the TV network which aired the ads. All of this will not matter anymore as you don’t see nor care about product brands all that much anymore when Alexa and Co. does the shopping for you.

Alexa and its ecosystem is growing at an exponential rate. In the US Amazon nearly doubled its installed base of Alexa-enabled smart devices from 25 million in the fourth quarter of 2017 to 46 million in the same quarter just one year later. Today Alexa cannot just order batteries for you, it does 99.999 other things as well. And learns 168 new skills every single day.

The important lesson is this: You don’t need to care about batteries to understand that voice will shift the decision from the mouse click of a consumer to the data-fed intelligence of the voice assistant. And this will be an as fundamental shift as there can be. We will do more and more things on and with our smart speakers. And they soon will be everywhere: In our home, our phones (and thus always with us), our car, our televisions. Voice, as a medium is much more versatile than computer or mobile phone screens – and it is much easier to integrate into many more devices and interactions.

And yet, you might look at voice as a curious oddity. As much as they are science fiction which has become real (remember the communicator from StarTrek?), they still have many flaws to overcome. They struggle with dialects, uncommon terms or complex commands. Given the huge investments being made into their further development combined with the continued exponential growth of the underlying technology platforms such as compute power and artificial intelligence as well as big data, it will only be a question of time until these systems become an inevitable part of our daily lives.

For voice interfaces to work, they need to reduce choice (nobody wants Alexa rattling down a list of all the batteries it has on offer), and with reduced choice these systems will need (and want) to make choices for us. Now the million dollar question becomes: Who controls what anymore?


Don't Copy & Paste Images into Apple Keynote

I use Apple Keynote for all my presentations (and I create a lot of presentation decks). It is by far the best presentation platform out there. It beats the heck out of Microsoft PowerPoint in terms of ease-of-use, features and precision control. My decks have hundreds of slides and tons of graphics. And I always wondered why my Keynote files were so large. Many of my decks are 500 MB or more.

Recently I found the culprit: When you copy and paste an image/photo from a photo editor (in my case Pixelmator) into Keynote, it gets pasted as a TIFF. Presumably Apple wants to preserve any possible transparency in the image as well as the image quality. But it also leads to very (VERY) large files.

So here is the pro-tip for everyone using Apple Keynote and editing their images in an external editor: Never copy and paste them into your Keynote presentation but rather save them as a JPG or PNG (if you need transparency) and then drag & drop the resulting file into your deck.

I went through one of my larger decks and pulled out all the TIFFs which Keynote inserted upon copy & paste, resaved them as JPEGs and reduced the file size of the deck from nearly 2 GB to about 700 MB (it is a deck with about 800 slides).


Don't fall for the Time Horizon Fallacy

Steve Blank (of Business Model Canvas-fame) just published an article on Harvard Business Review titled “McKinsey’s Three Horizons Model Defined Innovation for Years. Here’s Why It No Longer Applies.” In the article, Steve makes the case that the innovation time horizons (the time it takes to develop a disruptive innovation) have shrunken so much, that McKinsey’s Three Horizons Model starts to fail us somewhat.

I think his analysis is flawed (not his conclusions – I wholeheartedly agree with those!).

In the first part of his analysis, Steve makes the argument that disruptors such as Tesla, Space X, Craigslist or Uber, and AirBnB have become the disruptive force they are effectively overnight. It is an argument you often hear – and one which is, in my eyes, mostly not true.

Steve Jobs once observed: “Things happen fairly slowly, you know. They do. These waves of technology, you can see them way before they happen, and you just have to choose wisely which ones you’re going to surf. If you choose unwisely, then you can waste a lot of energy, but if you choose wisely, it actually unfolds fairly slowly. It takes years.”

He is right. As we at radical Ventures show in our new “Knowledge Adoption Curve”-model, the vast amount of disruptive innovations take a long time to gestate. Tesla was not an overnight success (even if it might feel like one) but was incorporated 15 years ago. The (in)famous paper from Satoshi Nakamoto which outlined the workings of a blockchain was published in November 2008. I remember sitting in a meeting room with Garrett Camp in 2009 where he told me about Uber.

As we show in the Knowledge Adoption Curve, stuff takes time to mature – but once it hits, it hits hard and fast; which is the reason why we often make the mistake of believing these disruptions happened overnight.


Accelerators are dead. Long live the Accelerator.

The last decade has been truly the decade of the startup accelerator – from pioneering programs such as Y Combinator, TechStars and SeedCamp to the myriad of programs (including more and more “corporate accelerators”) all around the world today, there has never been a better support infrastructure for budding entrepreneurs and their fledgling companies.

The party is about to end.

For beginners, accelerators traditionally always had a hard time making money – they have to run and finance often in-person programs with very real operational expenses and tend to provide funding to their participating startups. All in exchange for a typically single-digit percentage of a startups equity – with no protection (and often no capital to avoid) from dilution. Take into account the average survival rate of a startup and the fact that it takes multiple rounds of (diluting) financing and the initial equity stake is not worth much in the end.

Further accelerators, as in most creative industries, have a natural draw to the stars – the handful of top programs can pick from the most promising startups (as they have a strong desire to be part of the “best” program), the others have to scour the hand-me-downs (the same is true for venture capital – the top firms have the highest returns as they have unique access to the best companies).

And lastly we have seen massive democratization of access to knowledge, tools and, to a certain extent, even networks, which is, of course, good news as now you can have access to the same insights a company going through Y Combinator (wildly regarded the best startup accelerator in the world) by signing up for the free Startup School.

We predict that we will see a large dying-off of these programs all around the world in the next 12-24 months. The top programs will be fine, as will very niche and specialized programs. For everyone else, we might not lose all that much – as we truly live in the best times to start a company ever (and it will only get better).


Disrupt Disruption

Disruption has become one of the trendiest words in 2018 — it simultaneously instills fear and excitement and has become a staple talking point in every business presentation you hear or see nowadays. It is used to describe any company’s undoing, often with the aim to get said company to buy some service or product from the person who introduces the word in a meeting or on a stage.

In the process the word has become “tofu”—it doesn’t have a flavor of its own but takes on the flavor of whatever sauce you pour over it. That doesn’t mean the underlying concept is meaningless. Look beneath a well-used word, and you’ll find some truth accounting for its popularity.

In disruption’s case, I try to avoid one model or definition. The excellent model Clayton Christensen described eloquently 20 years ago in his seminal book, The Innovators Dilemma, describes one particular model of disruption and is often misused by applying it out of context. It’s also useful to go to first principles. For example, in my teams’ work interviewing hundreds of innovators, and borrowing from the fantastic analysis done by Ben Thompson, we’ve found a trifecta of forces which lead to companies becoming disrupted.

1. Innovation is never just one feature.

A disruptive invention like the smartphone is not a single thing—it is the ingenious combination of many features into a singular package. When the smartphone broke onto the market in the form of the Apple iPhone, it combined breakthroughs in microprocessor technology, an innovative multi-finger touchscreen, powerful batteries, and an intuitive operating system. It is often hard for incumbents to combine these individual features into a competitive package due to point two.

2. Your existing skills and processes are no longer relevant.

The biggest challenge for incumbent firms is the fact that their carefully honed skills and processes don’t fit the new reality anymore. Kodak famously had the best skills and processes to manufacture and develop beautiful film (a chemical process). These skills became obsolete in a world of digital photography. Nokia was excellent at making phones, but despite its name, the iPhone is not a phone, it is a tiny computer.

Worse, the existence of these obsolete skills typically provides a strong internal immune system to anything new and different. To compete, Kodak and Nokia would have needed swift, strong buy-in to overhaul entrenched processes and teams purpose-built for the film and phone businesses.

3. Disruption almost always reaches a tipping point at go-to-market.

Markets don’t flip from an incumbent solution to something new in the lab or boardroom or even due to the technical superiority of a particular solution. New solutions take the lead with an artful combination of the four Ps: product, price, place, and promotion. Selling the iPhone in Apple’s own, highly frequented stores, instead of the traditional sales channels (which tended to be little, dinky mobile phone shops in malls), signaled strongly that this was a new era, and the phone wasn’t a phone anymore. Stripe became a major player in the electronic payment space by making it incredibly easy for software developers to integrate Stripe into their applications—targeting an audience no other payment provider cared to cater to.

I strongly encourage you to look beyond the words and figure out what is real by applying first principles thinking yourself; going all the way to the root of the subject at hand and analyzing the primary factors. Get a handle on those primary factors, and you can get to work making your team more future flexible.

The good news is that almost none of this is complicated; it is just hard.


Blockchain and Cryptocurrencies – From Hype to Reality to Disruption

The Blockchain (and related: Cryptocurrencies as well as Initial Coin Offerings / ICOs) is currently one of the most talked about technologies around. You hear people hailing them as “the end of the financial system as we know it” with others comparing the potential impact of the technology to be as great or even greater than the Internet itself. Meanwhile, others observe that many ICOs are plain fraud, cryptocurrencies are nothing more than the next tulip mania and the blockchain is just a hyped decentralized database. And of course, the truth will likely be somewhere in the middle.

To understand the blockchain one must come to terms with its underlying technology. Short of going into a lengthy explanation, consider the blockchain as a way to store data – similar to a database with a few notable differences: The data itself is stored in a truly decentralized fashion; i.e., the information doesn’t reside on a single server or a series of tightly synchronized servers but rather a copy of the data is stored on many nodes in the network. Further, the data is stored in a way that it is effectively tamper-proof (through the use of some clever cryptography and linking each entry to each other into a chain).

The result of this is that the blockchain enables the storage of data in a way which doesn’t require any of the participating parties to trust each other – and this is truly novel. In every other infrastructure so far we have to trust at least one party; the blockchain makes trust obsolete.

This feature alone means that the blockchain, as a storage mechanism for data, has tremendous potential and will be quite disruptive. Everywhere where we typically don’t trust the other party (think about topics such as land rights in developing countries) or where we pay money to establish trust (a notary in Germany charges you quite a bit to establish trust between two parties), the blockchain has the potential to revolutionize the way we transact.

Moreover, the blockchain (at least some implementation of a blockchain – note that there is not a single blockchain but instead many blockchains) has another trick up its sleeve: Using technologies such as Etherium or Stratis you can add functionality to a transaction – turning data storage into a smart contract.

The simplest way to think about a smart contract is a magazine subscription: Every month you receive a copy of your favorite magazine and in turn once a year the publisher automatically deducts the cost of your subscription from your bank account. Smart contracts are clever little pieces of software which can settle payments based on verifiable conditions. For example, a merchant gets paid automatically once you signed for delivery of her products into your warehouse. This, in turn, reduces the level of trust one needs to have in a system and increases efficiency. The merchant doesn’t need to trust the customer that he will pay on delivery as agreed upon and the customer doesn’t need to have his accounting department keep track of the payment as it is issued automatically once the condition in the smart contract is met.

Taken together these two core features of the blockchain (a trust-less cryptographic store of data combined with the ability to execute software commands on it) is what makes the technology genuinely disruptive. Today we are mostly in the explorative phase of the technology. Organizations all around the world are wrapping their heads around the core principles and how to best use them in either existing or entirely new processes. As usual in these situations we see a lot of useless or plain wrong implementations – it takes time for a new concept to be fully digested and leveraged to its real potential. Having said that we will see many backend implementations of blockchain technology resulting in reduced cost, increased transaction times and reliability. Moreover, we will also see entirely new applications which just weren’t possible before.

From supply chains (Walmart is currently implementing a blockchain-based supply chain software, cutting down the time it takes to track an item on the shelf to the lot it was manufactured in from two weeks to less than ten seconds) to new peer-based banking and insurance products, the blockchain holds many promises which we will see play out over the next decade. Your first step in wrapping your head around the potential and possible pitfalls is to study the technology, as without a good understanding of the underlying principles one is stuck in either following or dismissing the hype without much thought for true potential.


Group M / NextM Copenhagen 2018 Keynote

Earlier this year I gave a keynote at the excellent NextM conference organized by GroupM in Copenhagen:


Open Office Workspaces (Seem to) Suck

A new study published in The Royal Society indicates that open office workspaces (you know – the ones we thought were so cool, hip and trendy and made us work so much better together) create the exact opposite effect to what they are intended to do:

“In short, rather than prompting increasingly vibrant face-to-face collaboration, open architecture appeared to trigger a natural human response to socially withdraw from officemates and interact instead over email and IM.”

Important read for anyone kitting out their new office space.

Full study here: The impact of the ‘open’ workspace on human collaboration


How to Write Good Job Specs

Your first paragraph will be the boilerplate description of your organization.

Narrative description of role: 1-2 paragraphs of 5-8 sentences each that give an overview of the role. While you don’t want to be hyperbolic, you do want this to be attractive, so you will want to sell it.


Bulleted list of most important to least important responsibilities. In truth, candidates will self select based on just skimming the JD and won’t read the details unless/until they are granted an interview. This list should be not more than 8-10 bullets and won’t include each and every duty.


Bulleted list, starts with education and years of experience and is followed by most to least important skills or experiences you desire. E.g.:


macOS High Sierra Sound Problems

I recently had some pretty annoying problems with my 2016 MacBook Pro Touchbar where it refused to play any sound or recognize my headphones including the microphone. The “Sound” preferences didn’t even recognize any audio interface anymore.

After a good two hours on Google and trying a bunch of things out, it turned out that one has to reset the SMC (System Management Controller) on your Mac to fix this.

Hope this helps some poor souls running into the same issues.


Pascal on two Innovation Podcasts

Recently I had the great pleasure of not only being on one Podcast but two – each with a slightly different twist:

First I talked with Bill Murphy from the amazing Redzone Podcast about “How to use Exponential Technologies to Innovate at the Edge”:

And then I was on Donnie SC Lygonis’ Constant Innovation Podcast, talking about… Innovation:


DIE ZEIT FESTIVAL ‘Smashing Ideas‘ 2016

A few weeks ago I had the great pleasure of speaking at the DIE ZEIT FESTIVAL ‘Smashing Ideas 2016’ in Hamburg, Germany. My talk is a condensed version of what we are teaching here at Singularity University plus a short Q&A session with Manuel Hartung, Resortleiter Chancen at DIE ZEIT.

Hope you enjoy it.


Podcast – Inspiring Social Entrepreneurs

The other day Fergal Byrne interviewed me for his Podcast “Inspiring Social Entrepreneurs”. We touched upon topics such as:

You can listen to the Podcast in many different formats and mediums on the Inspiring Social Entrepreneurs Website.