Releasing Software Developer Superpowers

Article is aimed at anyone looking to gain the edge in their software development team creation or advancement in the digital age. Concepts can be applied outside of sw dev at some level. Open to discussion – views are my own.

UX is not just for Customers

User Experience is an ever growing component of product development, with creating user centric design paradigms to ensure that personalisation and consumer/market fit is achieved. From a development team view, leveraging some of the user experience concepts in how they work can achieve operational efficiency, to accelerate product development. For example, how is the experience for each of the developer personnas in your team? How do their days translate to user stories? Can interviewing the development community lead to creating better features for your development culture?

Build Products not Technology

Super important. Sometimes with developers, there is an over emphasis on the importance of building features, a lot of the time for features sake. By keeping the lens on the value or “job to be done” for the customer in the delivery of a product at all times can ensure you are building what is truly needed by your customer. To do this, select and leverage a series of metrics to measure value for that product, along with keeping your product developent in series, and tightly coupled to your customer experience development.

Leverage PaaS to deliver SaaS

This sounds catching but its becoming the norm. 5 years ago, it took a developer a week of development time to do what you can do in Amazon Web Services or Azure now in minutes. This has led to a paradigm shift, where you being to look at the various platforms and tools that are available to enable the developers to deliver great products to customers. Of course, there will always be custom development apps, but you can help your developers by getting them the right toolkit. There is no point reinventing the wheel when OTS open source components are sitting there, right? Products like Docker and Spring and concepts like DevOps are bringing huge value to organisations, enabling the delivery of software or microservices at enhanced speed. Also, the balance between buying OTS and building custom is a careful decision at product and strategic levels.

“The role of a developer is evolving to one like a top chef, where all the ingredients and tools are available, its just getting the recipe right to deliver beautiful products to your customer.”

Create Lean Ninjas!

Evolving the cultural mindset of developers and the organisation toward agile development is super important. Having critical mass of development resources, plus defined agile processes to deliver business success  can really reshape how your organisation into one where value creation in a rapid manner can take place. However, its important to perform ethnographical studies on the organisation to assess the culture. This can help decide on which agile frameworks and practices (kanban, scrum, xp etc) can work best to evolve the development life cycle.

Implement the 10% rule

Could be slightly controversial, and can be hard to do. Developers should aim to spend 10% of their time looking at the new. The new technologies, development practices, company direction, conferences, training. Otherwise you will have a siloed mis-skilled pool of superheros with their powers bottled.

However, with lean ninjas and effective agile company wide processes, resources and time can be closely aligned to exact projects and avoid injecting randomness into the development lifecycle. Developers need time to immerse and focus. If you cant do that for them, or continously distract them with mistimed requests – they will leave. If you can enable them 10% is achievable.

Risk Awareness

We are seeing an evolution in threats to enterprise all over the world, and in a software driven and defined world, getting developers to have security inherent design practices prior to products hitting the market can help protect companies. Moons ago, everything sat on prem. The demands of consumers mean a myriad of cloud deployed services are adding to a complex technology footprint globally. If they know the risk landscape metrics from where they deploy, they can act accordingly. Naturally, lining them up with business leaders on compliance and security can also help on the educational pathway.

Business and Technology Convergence

We are beginning to see not only evolution in development practices –  we are also seeing a new type of convergance (brought about by lean agile and other methods) where business roles and technology roles are converging. We are beginning to see business analysts and UX people directly positioned into development teams to represent the customer and change the mindset. We are seeing technology roles being positioned directly into business services teams like HR and finance. This is impacting culture, wherby the saviness in both directions needs to be embraced and developed.

Growth Mindset

We mentioned mindset a lot in the article. That because its hugely important. Having the right culture and mindset can make all the difference in team success. As Carol Dweck talks about in her book “Mindset”, you can broadly categorise them into two – growth and fixed. This can be applied in all walks of life, but for team building it can be critical.

In a fixed mindset students believe their basic abilities, their intelligence, their talents, are just fixed traits. They have a certain amount and that’s that, and then their goal becomes to look smart all the time and never look dumb. In a growth mindset students understand that their talents and abilities can be developed through effort, good teaching and persistence. They don’t necessarily think everyone’s the same or anyone can be Einstein, but they believe everyone can get smarter if they work at it.

Creating a team where being on a growth curve and failures are seen as learning can really enable a brilliant culture. As Michaelangelo said “I am still learning”. Especially as we evolve to six generations of developers. How do we ensure we are creating and mentoring the next set of leaders from interns through to experienced people?

Check a Ted talk from Carol here – link.

And most importantly … HAVE FUN!

Closing off Web Summit 2015 – Day 2/3

And so it ends. The Web Summit on Irish shores finished on Thursday (for now), and I must admit there was an athmosphere of “what if” and that of sombreness. But we cannot allow this to affect our perspective and thinking of the impact this conference has had on Ireland tech landscape.. Paddy Cosgrave has built a conference which he began with 400 attendees to now 35,000. Let’s put that into context in regards to people’s perspective of Ireland as a Tech Hub. With over 100 countries represented, and technology itself ensuring their own tech landscape is quite small, the voices of the 35,000 will translate into millions. And I am certain the conversation will be about Web Summit, the friendliness of the services and the vibrant Night Summit, and not the number/cost of hotels, government and traffic.

Wednesday was a great day and one of the best I have had at a web summit event. It’s started on the Machine Stage, where a panel including Nell Watson from Singularity spoke on how machines and humans will coexist and complement each other in our smart future. I liked how Nell spoke about how the seamless integration of machines, and the governance of same will be a key piece of the puzzle.

Nell Watson from Singularity speaks on Machine Stage

Next up on Machine was another panel, which included Dr. Joe Salvo from GE and Dr. Said Tabet from EMC. The panel was expertly hosted by Ed Walsh who is the director of technology vision for EMC. Whilst interviewing the guys, Ed brought out not only the technology vision required for IoT, but also the collaboration that can be enabled by consortiums like the IIC, of which Dr Salvo and Dr Tabet have been so instrumental in building.

Ed Walsh hosting a panel session on the industrial internet

As already mentioned, the proliferation of Virtual reality was evident, and I got a demo of Amazons audible technology! It was quite neat!

Friday was a more relaxed day, with numbers down a little but this allowed for a different kind of networking experience. It was a day to chat with as many startups as possible, and to catch some great talks. One that stood out was on centre stage, where a panel (including Christine Herron from Intel Capital, Albert Wenger from Union Square Ventures, Mood Rowghani from KPCB ) was hosted by Charlie Wells of the Wall Street Journal. Topic discussed – tomorrow’s tech landscape. A growth or just a bubble?

 

Panel Discussion on Future of Tech

Well it looks like what Nell mentioned above is already happening from who I bumped into!

And so, we are off to Lisbon. Whilst I believe that there will be challenges there also, it is Cosgraves personality that will shine through. An excellent CI labs data science company spawned out of the web summit, and whist there is that data science feel to a lot of the web summit, it’s this personality of Cosgrave and his team that still makes this event stand above many.

Numenta and MemComputing: Perfect AI Synergy

Let’s look at two forces of attraction that are happening in the technology space, specifically looking at creating true artificial intelligent systems, utilizing advances in both software and hardware technologies.

For years, even decades we have chased it. AI has been at the top of any list of research interest groups, and while there have been some advances, the pertinent challenge has been that advances in hardware electronics in the 70’s and 80’s occurred, software design was lagging behind. Then, software advanced incredibly in the past decade. So now, in July 2015, we reach a key point of intersection of two “brain based technologies”, which could be built together in a way that may lead to “true AI”.

At no other point in history have we had both hardware and software technologies that can “learn” like we can, whose design is based on how our mind functions.

Numenta

First, let’s look at Numenta. Apart from having the pleasure of reading Jeff Hawkins excellent book “On Intelligence”, I have started to look at all the open source AI algorithms ( github here) that they provide. In a journey that start nine years ago, when Jeff Hawkins and Donna Dubinsky started Numenta, the plan was to create software that was modeled on the way our human brain processes information. Whilst its been a long journey, the California based startup have made accelerated progress lately.

Hawkins, the creator of the original Palm Pilot, is the brain expert and co-author of the 2004 book “On Intelligence.” Dubinsky and Hawkins met during their time building Handspring, they pulled together again in 2005 with researcher Dileep George to start Numenta. The company is dedicated to reproducing the processing power of the human brain, and it shipped its first product, Grok, earlier this year to detect odd patterns in information technology systems. Those anomalies may signal a problem in a computer server, and detecting the problems early could save time, money or both. (Think power efficiency in servers)

You might think, hmm, that’s not anything great for a first application of algorithms based on the mind, but its what we actually started doing as neanderthals. Pattern recognition. First it was objects, then it was patterns of events. And so on. Numenta is built on Hawkins theory of Hierarchical Temporal Memory (HTM), about how the brain has layers of memory that store data in time sequences, which explains why we easily remember the words and music of a song. (Try this in your head. Try start a song in the middle.. Or the alphabet.. It takes a second longer to start it). HTM became the formulation for Numenta’s code base, called Cortical Learning Algorithm (CLA), which in turn forms the basis of applications such as Grok.

Still with me? Great. So that’s the software designed and built on the layers of the cortex of our brains. Now lets look at the hardware side.

 

Memcomputing

After reading this article on Scientific American recently, and at the same time as reading Hawkins book, I really began to see how these two technologies could meet somewhere, silicon up, algorithms down.

A new computer prototype called a “memcomputer” works by mimicking the human brain, and could one day perform notoriously complex tasks like breaking codes, scientists say. These new, brain-inspired computing devices also could help neuroscientists better understand the workings of the human brain, researchers say.

In a conventional microchip, the processor, which executes computations, and the memory, which stores data, are separate entities. This constant transfer of data between the processor and the memory consumes energy and time, thus limiting the performance of standard computers.

In contrast, Massimiliano Di Ventra, a theoretical physicist at the University of California, San Diego, and his colleagues are building “memcomputers,” made up of “memprocessors,” that can actually store and process data. This setup mimics the neurons that make up the human brain, with each neuron serving as both the processor and the memory.

I wont go into specifics of the building blocks of how they are designed, but its based on three basic components of electronics – capacitors, resistors and inductors, or more aptly called memcapacitors, memresistors and meminductors. The paper describing this is here.

Di Ventra and his associates have built a prototype that are built from standard microelectronics. The scientists investigated a class of problems known as NP-complete. With this type of problem, a person may be able to quickly confirm whether any given solution may or may not work but can’t quickly find the best solution. One example of such a conundrum is the “traveling salesman problem,” in which someone is given a list of cities and asked to find the shortest route from a city that visits every other city exactly once and returns to the starting city. Finding the best solution is a brute force exercise.

The memprocessors in a memcomputer can work together to find every possible solution to such problems. If we work with this paradigm shift in computation, those problems that are notoriously difficult to solve with current computers can be solved more efficiently with memcomputers,” Di Ventra said. In addition, memcomputers could tackle problems that scientists are exploring with quantum computers, such as code breaking.

Imagine running software that is designed based on our minds, on hardware that is designed on our minds. Yikes!

In a future blog, I will discuss what this means in the context of the internet of things.

 

 

Ideate! Innovation strategy in your company

“Innovation is hard. The larger your business, the harder it gets.”

Is the above statement true? Maybe. More importantly, does it have to be true? No it doesn’t.

One of the most common mistakes in large companies in respect to innovation strategy is that when they see themselves as “big”, they need a “big” innovation model to succeed. Consider the life-cycle of a company. First, in startup mode, they are agile by default. They don’t look out past 2/3 months, with many looking at bringing new features to their product so they can secure the next round of funding. Once they grow and mature, and longer term goals become a priority and less financial pressure results, innovation slows down. The longer it does so, the more investment is needed to get it back.

Whilst having a large business means sharing knowledge becomes more of a challenge, there are advantages to size and scale. For one, diversity is a critical component in innovation, and the larger the company, generally the more diverse it is, its how you identify and partner that diverse thinking that can differentiate your innovation strategy. To enable a large organisation to reach its true innovative capacity, there are a number of approaches that can be used to reach it. Some of these are introduced below.

Disruptive Innovation Task Teams

A concept to consider when maintaining your innovation strategy is placing disruptive innovation task teams into your existing business model, whereby they act with limited budget and resources, look no further than 2/3 months out and are agile by nature. The also have a keen eye on not what the customer wants now, but what they will need in the future ( but not too far out 6-12 months). Planting a seed team like this can result in cross pollination with other product teams around it, and this will increase your companies overall ideation. A key component of these teams is to ensure there is diversity present, with both seasoned campaigners that have the business history, along with new generation employees that can bring outside thinking to the table.

Agile. Rinse. Repeat

One of the first aspects that is critical to success is to introduce agile as a mantra. This isn’t easy in large companies, and this is why an upfront investigation must be performed to assess how you inject it. Unfortunately, agile has been targeted mainly at software development teams, but it can have uses in other business teams, such as finance and human resources. However, it must be adapted to suit. No agile paradigm fits all. And within certain types of projects, if agile is not adjusted, then success becomes difficult (Read Ken Collier’s book on Agile Analytics for any data intelligence readers).

Think Lean

Think fast, learn fast, fail fast. The concept of Lean Startup is now well known, and has huge advantages. Lean startup is a method for developing businesses and products first proposed in 2011 by Eric Ries. Whether in your large organisation or in the start up space, most new ideas/ concepts fail. T he odds are not with you: As new research by Harvard Business School’s Shikhar Ghosh shows, 75% of all start-ups fail. A key component of the lean startup philosophy is to favor experimentation over elaborate planning, working with the customer over intuition, and incremental design over big design planning meetings. The aim is to build a minimum viable product, and iterate and pivot on that product. For more on this, check out the website.

Innovation Identity

Do you know your companies innovation identity? Innovation identity is the intersections between your companies technology, your innovation teams, the market(s),  and other departments of the company. Two main innovation models seem to emerge:

1. Thriving innovation model means the innovation culture is at the cornerstone of the corporate company; the company develops interactions both across internal departments and with external resources to complete its innovations. Cisco, Sanofi, 3M, Renault, and the open source way of working are championing this model.
2. Dedicated entity model involves the creation of an autonomous unit pursuing new and uncertain activity lines. Lockheed with its skunk works, At Google for instance, innovation is at the core DNA, which links them to the first model; reversely, as they enable small teams to investigate disruptive innovation in a flexible framework, they are really close to this model

Open Innovation

The identity of innovation has been gradually shaped by multiple interactions between different levels of a company with other external groups/organisations. And not just any type or size of external companies. The people you collaborate with must be suited to the market entry you are trying to achieve. Although they may exist within a market you are trying to enter, sometimes it is key to identify the technology required to enter that market, and even look at university collaboration to fulfill the technology requirements for market penetration.

In the way to define our innovation mantra and strategy,  a look at the 10 facets defined by Jeffrey Philips can also help, positioning where you want to be:

• open vs closed innovation:
• skunk works vs broadly participative;
• suggestive vs directed, incremental vs disruptive (also stretching innovation vs “all included” innovation vs disruptive innovation);
• centralized vs decentralized;
• product / service / operations / business model, funding, wisdom of crowd vs defined criteria and experts.

In closing..

Creating and maintaining the innovation strategy at your company is both a challenge and an evolution of not only your company, but also the internal personality and dynamic of the individuals who contribute to it. The direction you take and how you make the journey is down to you.