Category: How tech works

Stepping out of the firehose



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I’ve been collecting pictures like this for a while now, partly because they’re hilarious, but mostly because I think they say something interesting about how we find room for digital in our lives. The internet is a firehose. I don’t, myself, have 351 thousand unread emails, but when anyone can publish and connecting and sharing is free and frictionless, then there is always far more than we can possibly read. So how do we engage with that?

The first generation of internet services tried to help with filters and settings, but most normal people ignore the settings and don’t want to write filters, and so we very quickly went to systems that tried to help automatically. Gmail has its priority inbox, and social networks build recommendation engines and algorithmic feeds. Given that the average Facebook user is apparently eligible to see over a thousand times a day, it seems (or seemed) to make sense to try to show the video of your niece before the special offer from a restaurant you ate at five years ago. So your feed becomes a sample - an informed guess of the posts you might like most. This has always been a paradox of Facebook product - half the engineers work on adding stuff to your feed and the other half on taking stuff out.

Snap proposed a different model - that if everything disappears after 24 hours then there’s less pressure to be great but also less pressure to read everything. You can let (Read more...)

Mainframes, ML and digital transformation



Patrick Collison once made a joke that if you erect enough enterprise software billboards, an airport will spontaneously appear around them. It’s a pretty good bet that all of those billboards would say ‘digital transformation’, and that phrase always sounds to me like a parody of tech marketing. It’s got ‘digital!’ in there, and ‘transformation!’ - what on earth could this mean? If you poke away at it a little, though, this describes a pretty interesting generational shift in the technology inside big companies. 

Perhaps the best high level way to talk about this is just to say, as a gross generalisation, that in the 60s and 70s giant companies bought mainframes, and in the 80s and 90s the centre of gravity of enterprise IT moved from mainframes to client-server, Oracle, Windows and PCs, and now it’s moving again, to cloud and SaaS, and a bunch of other technologies that come with that. 

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Moving from mainframes to client-server didn't just mean you went from renting one kind of box to buying another - it changed the whole way that computing worked. In particular, software became a separate business, and there were all sorts of new companies selling you new kinds of software, some of which solved existing problems but some of which changed how a company could operate. SAP made just-in-time supply chains a lot easier, and that enabled Zara, and Tim Cook’s Apple. New categories of software enabled new ways of doing business. 

The same shift is happening now, (Read more...)

Outgrowing software



Source: Walmart

Source: Walmart

Ten years ago Marc Andreessen wrote an article in the WSJ called ‘Software is eating the world’, arguing that there was a fundamental shift in the role that software plays in the economy. In the past, IBM, Oracle or Microsoft sold technology to other companies, as a tool - they sold computers and software to GE, P&G and Citibank. Now there’s a generation of companies that both create software and use it themselves to enter another industry, and often to change it. Uber and Airbnb don’t sell software to taxi companies and hotel companies, Instacart doesn’t sell software to grocery companies, and Transferwise doesn’t sell software to banks. 

It’s useful to compare this to electricity, or cars and trucks. Walmart was built on trucking and freeways (and computers), but Walmart is a retailer, not a trucking company: it used trucks to change retail. Now people do the same with software. 

But it’s also interesting to look at the specific industries that have already been destabilised by software, and at what happened next. The first one, pretty obviously, was recorded music. Tech had a huge effect on the music business, but no-one in tech today spends much time thinking about it. 15 and 20 years ago music was a way to sell devices and to keep people in an ecosystem, but streaming subscription services mean music no longer has much strategic leverage - you don’t lose a music library if you switch from iPhone to Android, or even (Read more...)

What comes after smartphones?



For as long as most people can remember, the tech industry has had a new centre roughly every fifteen years. A model of computing sets the agenda, and the company or companies that win that model dominate the industry, and everyone is scared of them, and then a new model comes along, forms a new centre, and the old model stops mattering.  Mainframes were followed by PCs, and then the web, and then smartphones. 

Each of these new models started out looking limited and insignificant, but each of them unlocked a new market that was so much bigger that it pulled in all of the investment, innovation and company creation and so grew to overtake the old one. 

Meanwhile, the old models didn’t go away, and neither, mostly, did the companies that had been created by them. Mainframes are still a big business and so is IBM; PCs are still a big business and so is Microsoft. But they don’t set the agenda anymore - no-one is afraid of them. 

Today, multitouch smartphones are getting on for 15 years old, and the S curve is flattening out. All the obvious stuff has been built, Apple and Google won, and the new iPhone isn’t very exciting, because it can’t be. So, we ask “what’s the next generation?” 

There are several ways to try to answer this. 

First, each of the previous S Curves unlocked a dramatically larger new market, but well over 4bn people have a smartphone today and there are only (Read more...)

What comes after smartphones?



For as long as most people can remember, the tech industry has had a new centre roughly every fifteen years. A model of computing sets the agenda, and the company or companies that win that model dominate the industry, and everyone is scared of them, and then a new model comes along, forms a new centre, and the old model stops mattering.  Mainframes were followed by PCs, and then the web, and then smartphones. 

Each of these new models started out looking limited and insignificant, but each of them unlocked a new market that was so much bigger that it pulled in all of the investment, innovation and company creation and so grew to overtake the old one. 

Meanwhile, the old models didn’t go away, and neither, mostly, did the companies that had been created by them. Mainframes are still a big business and so is IBM; PCs are still a big business and so is Microsoft. But they don’t set the agenda anymore - no-one is afraid of them. 

Today, multitouch smartphones are getting on for 15 years old, and the S curve is flattening out. All the obvious stuff has been built, Apple and Google won, and the new iPhone isn’t very exciting, because it can’t be. So, we ask “what’s the next generation?” 

There are several ways to try to answer this. 

First, each of the previous S Curves unlocked a dramatically larger new market, but well over 4bn people have a smartphone today and there are only (Read more...)

Are you a seal?



There is a theory that when a shark bites a surfer, this is because they look like a seal, especially from 50 feet underwater. The shark circles, comes close, and sometimes it takes a bite out of a leg, and sometimes it takes a bite out of the surfboard and gets a mouthful of fibreglass. Generally, it realises the mistake and leaves, though this may or may not be any consolation to the surfer. 

I think about this theory a fair bit when I talk to big companies worried that Amazon or Google seem to circling around them, getting closer, and bumping into their legs. Maybe you look like a seal. And of course, maybe you are a seal. 

What does it mean to look like a ‘seal’, in this analogy, or indeed to be one? Well, a trillion dollar company with tens of thousands of engineers runs lots of projects and experiments, and there are lots of things that theoretically they could do, and that they might explore. But you have to ask not ‘would it be a problem for me if they got into my industry?’ but rather ‘would it make any sense for them to get into my industry?’ 

How do you tell if it would make sense for them? I’d suggest a few overlapping questions: 

  • Can this naturally be added to the existing skills, assets and points of leverage that they already have? Might they squash you without noticing?

  • Can it scale massively with little incremental, marginal (Read more...)

Are you a seal?



There is a theory that when a shark bites a surfer, this is because they look like a seal, especially from 50 feet underwater. The shark circles, comes close, and sometimes it takes a bite out of a leg, and sometimes it takes a bite out of the surfboard and gets a mouthful of fibreglass. Generally, it realises the mistake and leaves, though this may or may not be any consolation to the surfer. 

I think about this theory a fair bit when I talk to big companies worried that Amazon or Google seem to circling around them, getting closer, and bumping into their legs. Maybe you look like a seal. And of course, maybe you are a seal. 

What does it mean to look like a ‘seal’, in this analogy, or indeed to be one? Well, a trillion dollar company with tens of thousands of engineers runs lots of projects and experiments, and there are lots of things that theoretically they could do, and that they might explore. But you have to ask not ‘would it be a problem for me if they got into my industry?’ but rather ‘would it make any sense for them to get into my industry?’ 

How do you tell if it would make sense for them? I’d suggest a few overlapping questions: 

  • Can this naturally be added to the existing skills, assets and points of leverage that they already have? Might they squash you without noticing?

  • Can it scale massively with little incremental, marginal (Read more...)

Not even wrong: predicting tech



"That is not only not right; it is not even wrong"

- Wolfgang Pauli

A lot of really important technologies started out looking like expensive, impractical toys. The engineering wasn't finished, the building blocks didn’t fit together, the volumes were too low and the manufacturing process was new and imperfect. In parallel, many or even most important things propose some new way of doing things, or even an entirely new thing to do. So it doesn’t work, it’s expensive, and it’s silly. It’s a toy.

Some of the most important things of the last 100 years or so looked like this - aircraft, cars, telephones, mobile phones and personal computers were all dismissed.

But on the other hand, plenty of things that looked like useless toys never did become anything more.

This means that there is no predictive value in saying ‘that doesn’t work’ or ‘that looks like a toy’ - and that there is also no predictive value in saying ‘people always say that’. As Pauli put it, statements like this are ‘not even wrong’ - they give no insight into what will happen. You have to go one level further. You have to ask ‘do you have a theory for why this will get better, or why it won’t, and for why people will change their behaviour, or for why they won’t’?

“They laughed at Columbus and they laughed at the Wright brothers. But they also laughed at Bozo the Clown.”

- Carl Sagan

To understand this, it’s (Read more...)

Not even wrong: predicting tech



"That is not only not right; it is not even wrong"

- Wolfgang Pauli

A lot of really important technologies started out looking like expensive, impractical toys. The engineering wasn't finished, the building blocks didn’t fit together, the volumes were too low and the manufacturing process was new and imperfect. In parallel, many or even most important things propose some new way of doing things, or even an entirely new thing to do. So it doesn’t work, it’s expensive, and it’s silly. It’s a toy.

Some of the most important things of the last 100 years or so looked like this - aircraft, cars, telephones, mobile phones and personal computers were all dismissed.

But on the other hand, plenty of things that looked like useless toys never did become anything more.

This means that there is no predictive value in saying ‘that doesn’t work’ or ‘that looks like a toy’ - and that there is also no predictive value in saying ‘people always say that’. As Pauli put it, statements like this are ‘not even wrong’ - they give no insight into what will happen. You have to go one level further. You have to ask ‘do you have a theory for why this will get better, or why it won’t, and for why people will change their behaviour, or for why they won’t’?

“They laughed at Columbus and they laughed at the Wright brothers. But they also laughed at Bozo the Clown.”

- Carl Sagan

To understand this, it’s (Read more...)