Sunday, May 31, 2015

How Tech is Leading us Back to a Village-style Life

This post was also published in VentureBeat.

There has been a lot of discussion about how the acceleration of technology is decimating the middle class and traditional jobs. But there has been very little discussion of an emerging trend where individuals are opting out of these same jobs people fear will disappear.

Driven by a post-scarcity economic model whereby you can live very frugally if you choose to, some workers (mostly college-educated and urban) are opting out of the now traditional work structure and choosing their own path. As Chelsea Rustrum puts it in her book It’s a Shareable Life, “You can live a life dictated by choice, passion, and freedom — a life where your … experiences are of the highest value.”

They are opting into alternative, passion-based professions that have gained popularity and acceptance, such as craft beer producer or yoga teacher, and that have flexible hours. Twenty years ago, if Bob, the valedictorian, showed up to his high school reunion and said he was starting an artisanal coffee shop and manually roasting his own beans, most of the attendees would have laughed and asked each other, “What the heck happened to Bob?” Today, Bob is admired as one of the few that are beginning to embrace the lifestyles of a hundred years ago. Yes, machines can manufacture pretty darn good coffee. But Bob likes to hand roast coffee, and people like to drink it.

The economics underlying this shift are of course driven by technology, which has progressively driven down the cost of commodity goods and enabled the easy sharing of capital assets. However, in an ironic twist, technological progress and abundance are ushering in a very retro lifestyle.

Housing, dining, and even employment are being unbundled into pre-industrial age configurations. Shervin Pishevar, an investor who funded Uber, posited this when he noticed that village services could be implemented at city-wide scales. But perhaps what is actually occurring is the reverse; the cities and services are decentralizing themselves into villages and village-like urban neighborhoods.

Some of these trends are already well established, while others such as food carts are of course small micro-trends amongst relatively wealthy city-dwellers.

1920s 2000s 2010s Breakout Company
Goods Local artisans Amazon Local artisans Etsy
Coffee Local artisans Starbucks Local artisans Blue Bottle
Barber Local artisans Supercuts Local artisans StyleSeat
Cities Villages and urban neighborhoods Suburbs Villages and urban villages
Personal Transport Hitch a ride and pay Own a car Hitch a ride and pay – Uber and Lyft Uber
Commuter Transport Small shared vehicle Mass transit Small shared vehicle Chariot
Hotel Rent a room in a guest house Hotel Rent a room in a guest house AirBnB
Housing Small houses McMansions Small houses and microapartments
Spirituality Church Consumerism Yoga and meditation CorePower Yoga
Work Independent craftspeople Companies Independent contractors oDesk
Trade Barter Paypal Barter and apps
Food Local store with local food and neighborhood delivery Safeway and factory farms Farmer’s markets and local food delivery FreshDirect
Entertainment Local artists Pop stars YouTube Stars and local bands Maker Studios
Restaurants Small restaurants, many home-based Chipotle Food carts Munchery
Schooling Schoolhouse, Home schooling, Trade apprenticeship Factory schools Charter schools, Home schooling, Trade schools AltSchool

Many of these new services offer very predictable quality due to built-in recommendations or via TripAdvisor or Yelp. Others are very haphazard, like a Burning Man camp during its heyday a few years ago. You can’t buy your way into a top restaurant when it’s a food cart whose owner has everything she needs. She’s much more incentivized to trade her services for a private yoga session, or just simply offer her food to people she already knows and likes.

The “return to the village” trend is, of course, limited to a small population that can afford to spend their time on personal pursuits and eschew higher wages. This privileged demographic could certainly suck it up and work 12 hours a day, be online every weekend, and live the materialistic American dream – but they now have the luxury of trading less time for less wages, while still meeting their needs and leading excellent lives.

In parallel to the great migrations of the Depression era, young, educated people are flocking to cities like Detroit and Buffalo to begin a new kind of life. While the 1 percent worries about the new home construction index, others are taking advantage of relatively empty cities and abundant, inexpensive housing. The recent unbundling of healthcare from traditional career-track jobs is only making the opt-out path even more attractive.

People spent extremely long hours at work well before the industrial revolution. However, research shows that they actually spent far fewer hours actually performing work due to limited light, a lackadaisical work ethic, and numerous religious observances. The shift-based work day schedule developed during the industrial age has lasted well through the information age, and has extended into even longer hours for most knowledge workers. What happened to John Maynard Keynes’ prediction of a 15 hour workweek where people’s needs could easily be met with very little work?

While we’re still a long way from a post-scarcity economy, we are already at a point where a large portion of the population no longer works the traditional 40+ hour work week, and it has become increasingly difficult to find service workers that can reliably perform monotonous jobs. Perhaps, in the near future, the time-for-wages equation will shift positively and benefit all Americans, well beyond the privileged few that can choose to opt-out and return to a village lifestyle. A world where workers will be empowered to dictate their own hours, their own wages, and most importantly, their own freedom to explore their passions. A massive shift that opens up the opportunity for numerous peer-to-peer services and networks.

Tuesday, May 12, 2015

Push Comes To Shove: The New Way We Interact With Information

This post was also published in ReadWriteWeb.

Since its inception in the 1960s, the modern computer has offered humans the same “pull computing” paradigm: make a query, get a response. Or, as we often experience it: Go to the haystack, try to find the needle.

But that’s quickly changing. As software grows more intelligent and learns more about our preferences and behavior, it seemingly gets to know us. That knowledge makes software more valuable because it means that it can deliver things to us, perhaps even before we know we want it. We are at the start of the era of push computing.


With push computing, a computer is no longer just a question-and-answer service; it’s expected to proactively figure out what’s interesting to you and deliver that data. On mobile, that’s often an actionable stream of cards and timely notifications of important items.

Push computing represents a major shift in architecture from the pull relationship computers have long maintained with users. Computing interfaces have evolved from green screens to GUIs to HTML5 to apps, but most applications have the same workflows and address the same needs in a pull-based fashion.

Outside the view of users, however, software delivery has steadily evolved toward a push-type model. Just consider how far we've come, from the hosted timesharing of mainframes and minicomputers to dedicated Unix servers to the PC floppy disk and CD and finally to the increasingly prevalent “software-as-a-service” we see today.

Over the past few years, push computing has also begun to infiltrate the interfaces of key consumer apps. Of course, as Chris Dixon recently pointed out, some Internet services are further along than others. Facebook, for instance, has mastered intelligent news feeds of cards and relevant notifications while Twitter delivers a straight temporal stream that grows more overwhelming the more accounts you follow.

Don’t Push Me

Not all pushes are the same, after all, and companies have to think carefully about the information that is important to push, when and why it‘s pushed, and how they expect users to react.

Major players are also trying to figure out how to make push a central part of the mobile OS. As I wrote a few months ago, Google is aggressively recasting itself as a push player with Google Now and answer cards in search. Apple is decidedly in the pull camp, as Siri is rarely proactive, although the iOS notification manager is well ahead of Android’s. Push has also become the backbone of successful mobile apps powered by real time infrastructure such as PubNub and Amazon’s Simple Notification Service.

Machine learning is key to the success of contemporary push-based services. Notifications and cards should only presented to users if they deliver relevant information users can act on easily.

Previous attempts to provide user notifications via email failed because email notifications are typically irrelevant and spammy. We’re all well trained to avoid spam like the plague, so users typically dumped all notifications into an email folder and never looked at them at all. Email is also inherently less actionable because a user has to click on a link, log into an application, and then perform an action.

For push to work, it’s crucial for applications to make their notifications actionable, friction-free, and rooted in sophisticated machine learning. Early efforts like PointCast to push information were too static and overloaded networks with continual updates.

Getting Pushy At Work

While push got its start in the consumer realm, the case for business-based push is in many ways much stronger. Enterprise systems manage discrete events that often require urgent action. For example, a sales opportunity might be closing in a CRM system, a complaint from a customer you cover could pop up in the service system, or the HR database could flag you about a new hire you need to onboard.

Conversely, the relative importance of events in consumer apps are much more nebulous. To deliver a superior experience to users, Google Now must continually learn, confirm and re-confirm details about where you live, where you work, your calendar, your travel arrangements, your preferences. Peoples’ lives and environs are constantly shifting, making it hard for the new generation of consumer apps to keep up.

What is more difficult about enterprise events is that they must be extremely secure and the data is often locked away in a variety of data siloes.

As users increasingly expect their services to be intelligent and proactive, push computing is making its way not just to mobile, but also to desktops and laptops by means of browser notifications. The new generation of push software is ushering in a new way for humans to interact with technology, and in the case of the Internet of Things, for technology to interact with itself in the form of networks of “smart” devices.

But as digital data becomes more voluminous, our systems have to get more intelligent. They have to filter, analyze, and deliver information to users—and then only when they need to know it or act on it. The goal should always be simple: for the haystack to bring you the needle—whatever it is—before you even start to look for it.

Saturday, May 09, 2015

Goodbye, SaaS — Hello, Containers-as-a-Service

This post was also published in VentureBeat.

When Salesforce’s Marc Benioff first started pitching on-demand CRM software, people thought he was insane and were convinced software-as-a-service would never work. Although we are now living in a SaaS heaven with all of the benefits of software that is always available and up-to-date, we are also beginning to see the SaaS hell naysayers were warning us about.

When selling Salesforce to a mid to large organization, Salesforce expects multi-year contracts with pre-negotiated user counts, exactly like the on-premise predecessors it ridiculed during its early days. The whole idea of “pay for what you use” has been subsumed by the realities of the sweet cash flow dynamics of a traditional enterprise sale, which ends up as shelfware when customers over-provision.

Compounding this issue is that the expense is accounted as an operating expense that affects EBITDA, a key Wall Street metric, while on-premise software was accounted as a much more palatable capital expense.

There are some other cracks in the SaaS armor. In a world of “big data,” enterprises are starting to realize that SaaS solutions do not offer unfettered access to their own data. Salesforce’s API access to your own data is metered and hinged off of user counts or API purchases – an enterprise has to take out its wallet and pay these vendors for scaled access to its own data. In a world of extreme security consciousness among CIOs, security is fully delegated to the SaaS provider. The multi-tenant model shares data infrastructure to the benefit of the vendor, not the customer. Integrating various SaaS silos has become so complicated that the field now has dedicated systems integrators like Appirio.

SaaS has become the orthodoxy du jour, with an ecosystem ranging from accelerators to post-traction venture funds focused solidly on SaaS. After 15 years of SaaS, you do have to ask, what’s left to SaaS-ify? In many segments, we are now on the third or fourth iteration of software that offers essentially the same workflow, such as Namely and Betterworks on the heels of Workday. The latest entrants are forced to target verticals in sluggish industries like construction and energy. So the question is, what’s next?

Containers and Containers-as-a-Service

There has definitely been a lot of buzz about Docker containers. The ability to separate an application, microservices, and their configuration from the underlying Linux operating system is very attractive. Orchestration layers built on top of containers such as Docker Swarm and Google’s Kubernetes make it easier to manage and scale clusters of containers.

The three major cloud providers, Amazon, Google, and Microsoft, have all added CaaS (Containers-as-a-Service), allowing any Docker container to run on their platform, filling a void between IaaS (Infrastructure-as-a-Service) that requires a lot more system administration and configuration, and PaaS (Platform-as-a-Service) that is typically very limiting in terms of language support and libraries.

Containers have been around for quite a while. As Bill Coleman, the former head of Sun Micrososytems’ Software group, recently reminded me, Solaris offered containers in 2005. What’s changed is that the new generation of Docker-powered containers have widespread support and are easy to learn. Now that there is a standard way to manage and deploy applications, there is the potential to reinvent how cloud software is delivered.

The Potential for CaaSi to Fix SaaS

Imagine a world where when you can purchase software or rent an application, then run it in the public or private cloud of your choice. Just like SaaS, the software would be automatically maintained by the vendor. But you would own and control all of your data, including the access by the vendor.

Until recently, this would have seemed like a pipe dream due to the intricacies of hosting, managing, and updating the software. Now, we are almost there. With some small incremental improvements, CaaS can evolve into CaaSi – Containers-as-a-Service for ISVs (Independent Software Vendors). Whether in a public cloud or in your own private cloud, the vendor would have the access and keys to manage and update the containers on your schedule rather than theirs. The vendor would not, however, have the ability to access your data without your explicit permission.

With the new CaaSi model, software customers have the best of the on-premise world combined with the best of the SaaS world. When customers buy software, just like with on-premise software, they have complete visibility into the hosting costs, full ownership of their data, tightly controlled security, and also the flexibility to use capital expense accounting. Just like with SaaS, they have the ability to scale as needed and receive automatic updates from the vendor.

Given such a huge transition on the horizon, it is no wonder that Docker is a newly minted billion-dollar unicorn with companies like CoreOS and Mesosphere battling over the best implementation of Google’s Kubernetes. In order to build out a CaaS/i future, CaaS providers need to add better support for immutable infrastructure by maintaining the separation between application containers and their underlying data, along with the delegated management of containers, usage metering for billing and abstraction for services such as logging and monitoring.

One highly material benefit that customers receive from SaaS is the network effect – the ability of the vendor to analyze in aggregate how all of the users are using the system and accelerate that usage in new features. In order to provide a similar level of functionality in a CaaS/i world, customers would need to opt-in to anonymous collection of their data usage in order to receive the same benefits of the analysis. But rather than a drawback, perhaps this is the point: the vendor should have to ask permission in the first place, and the customer should control their sensitive data.

A few startups are kicking off this trend. My own company, Sapho, is enthralled about the ship-as-a-container option and has launched that alternative., an orchestration backend, is only available as Docker containers. And Replicated and Infradash are providing the infrastructure for an independent software vendor to ship and manage Docker containers. The coming year should see a lot of activity on this front.