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With the new Exposure Notification Express, which forms the second phase of Exposure Notification System, the system removes one of the key barriers to adoption that led to a slow start to the software. Once users update iOS 13.7, users can now enable COVID-19 Exposure Notifications directly in the Settings app on their iPhone. This new process is called Exposure Notifications Express. The process is as simple as enabling user preferences in any other application and just takes a few taps, including agreeing to the public health agency terms and conditions of service. Additionally, users will also be able to opt-in to receive a push notification when their local public health authority adopts Exposure Notifications Express.

The philosophy of the microservices architecture is: “Do one thing and do it well." Services might run within the same process, but they should be independently deployable and easy to replace. They can be implemented using different programming languages, databases, and software environment. The services are small and fine-grained to perform a single function. They embrace automation of testing and deployment, continuous delivery software development process, failure and faults, similar to anti-fragile systems. Each service is elastic, resilient, composable, minimal, and complete.

Classic machine learning algorithms involve techniques such as decision trees and association rule learning, including market basket analysis (ie, customers who bought Y also bought Z). Deep learning, a subset of machine learning that includes neural networks, attempts to model brain architecture through the use of multiple, overlaying models. Classic examples of Machine learning include Virtual Personal Assistants like Siri, Alexa, Google, Predictions while Commuting, Videos Surveillance, Social Media Services from personalizing your news feed to better ads targeting, Face recognition, Email Spam and Malware Filtering, Online Customer Support including chat bots, Search Engine Result Refining, Product Recommendations based on previous purchase trends, and Online Fraud Detection including efforts to curb money laundering. Removing bias from AI is the result of deliberate, calculated and thought-out human endeavors, and certainly not an unintended byproduct of certain data analysis. Companies employing any or all five forms of AI — computer vision, natural language, virtual assistants, robotic process automation, and advanced machine learning — must realize that any output they hope to derive are only as good as the data on which the applications are trained.

The Exposure Notification System or ENS allows public health authorities to develop apps that augment manual contact tracing efforts while preserving the privacy of their citizens. As of today, public health authorities have used ENS to launch in 16 countries and regions across Africa, Asia, Europe, North America and South America, with more apps currently under development. Apple likely made the change to use Exposure Notification service without the need for a contact tracing app to quietly encourage more public health departments to use its service. Only a handful of states in the United States and a few countries worldwide are using Google and Apple’s mobile technology. Most health departments still use an old fashioned contact tracing method that relies on in-person interviews and phone calls to locate those individuals who came in contact with an infected person.

All content platforms and social media companies must keep the content flowing because that is the business model: Content captures attention, provides viewership and generates data (users’ statistics). Content is the starting and the end point of consumers’ journeys on social media. A video, an information post, a tweet, blog post, picture, public service advisories, are all types of content. The platforms then sell that attention (read: viewership), enriched by that data (read: customized ads). But how do you deal with the objectionable, disgusting, pornographic, illegal, or otherwise verboten content uploaded alongside legitimate content? How do Facebook and other tech and social media companies ensure integrity of content on their networks? And how do these companies work to curb misinformation on their platforms about the Coronavirus pandemic or the 2020 elections or any other global or regional event. We have seen state and non-state sponsored actors with nefarious intent take advantage of lax content posting norms.

Whenever there is a talk of infusing technology, automation and intelligence in to tasks or processes, the solutions proposed fall in to two broad buckets. The first is the conventional use of the term Artificial intelligence, machine learning, deep learning and cognitive learning, which typically work outside human intervention and are largely driven by some kind of an algorithm to achieve its goal. The handling of regular transactions as well as any exceptions are defined within the AI program and the machine doing the job in case of touch and feel jobs like manufacturing or the algorithm producing the result in case of purely online work. The second category is where Artificial Intelligence is applied to work in conjunction with the humans and human intervention and interaction is a critical part of the successful completion of the job. This second type is known as Augmented intelligence or Augmented reality. Another way of looking at what happens with augmented and artificial intelligence is the degree to which algorithms and the programs running the physical machines are expected to make decisions on their own. Is the decision making assisted by humans, controlled by humans or completely out of control of humans?

Agile is great, but the demands of the next-gen software and application development require something greater. The software development community has caught on to the Agile Manifesto and its 12 principles as the defining standards of software development movement. Today, more and more teams are motivated to self-identify as using an Agile methodology, irrespective of its suitability to the goals. While many of those teams motivated to be identified as Agile teams are likely using a hybrid model that includes elements of several agile techniques as well as conventional waterfall method, that they identify so completely with the agile movement is a testament to both the strength of the statement and the power of the movement.

Most experts are not against every idea and practice in Scrum. For example, the principles of the whole team taking responsibility for the code base, or always having an integrated, working master are really noteworthy and something that all teams in all project settings can benefit from. Software is research; its as much discovery and going along the unknown path as it is about following standardized, laid down paths. It’s a matter of discovering the solution, not rummaging through it.

DevOps is as crucial to application delivery as Agile is to Development. As development is unthinkable without being Agile, or at least aspiring to be agile, similarly DevOps implementation is undeniable to deliver seamless deployment processes. DevOps is a philosophy under which the business function / teams, development teams, and the operations team collaborate on a continuous basis to make sure that IT solutions are available to business on time and that they run without disruption. In many ways, DevOps is a concept that can be used to manage end-to-end engineering process while Agile is a process used to manage development of complex projects. DevOps at its core should really be a culture, and the very important skills it cultivated over the years should be imparted to all developers, especially those of the next generation.

Agile performance management is an approach to manage employee performance and development throughout the year on a continual basks as opposed to on an annual or biannual basis. It is collaborative, involving regular conversations, continuous feedback loop and improvement measurements. Agile performance management isn’t solely focused on the end product only, i.e. to award a rating, rather is concerned with how to get there. Agile performance management is more about the process to arrive at the rating giving each employee optimum chances to learn and improve along the way. Agile performance management is created for and is being increasingly adapted by a brave new world that is faster, more social and more communicative. The main feature of agile performance management is the frequent performance discussions, or ​‘check-ins’, which ideally take place on a monthly basis. These sessions are designed to help cultivate authentic, meaningful relationships and dialogue between manager and employee while providing the opportunity to exchange much needed, real, improvement oriented feedback.

As team sizes grow, organizations grow and their needs become more complex, bigger and more complex impediments arise along the road. The role of Scaling Scrum is to provide a framework to continually identify and remove dependencies created by increased complexity. Scaling Scrum, like implementing Agile Scrum methodology is a matter of choice. Many organizations have reaped tremendous benefit and even more continue to do so. However, the primary integration point of Scaled Scrum is within the culture of an organization. The complexity of an organization’s hierarchy and culture defines the kind of products and applications it produces. In the words of programmer Melvin Conway: “organizations which design systems … are constrained to produce designs which are copies of the communication structures of these organizations.”

While it is true to a large extent that Agile methods advocate doing away with rigid guidelines, documentation and maintaining artifacts is not a rigid requirement to begin with. Lets keep in mind, agile is first of all a set of values, not a settled and strict, rigid framework. All Agile practitioners should be confident on how to adjust these values to their environment. Remember that every company has its own pace, characteristics and values. All Agile documentation must follow the same rule – it is not that agile eschews documentation, so much as it eschews up-front documentation.

Over the years as sports have become more competitive, sporting teams have realized that one coach for all aspects of the game is not enough. For example in Cricket, teams employ separate coaches for bowling, batting and fielding. In football, teams employ goalkeeping coaches, striking coaches, defensive coaches and more. Similarly, many large organizations today employ multiple Agile coaches with varying and diverse skill-sets, experience and backgrounds so as to derive maximum benefit and ROI. Adaption of Agile methods can have more than just tangible benefits. The benefits of Agile are not limited to the organization only. As an organization pursues it’s endeavors on the path of Agile journey, it contributes to its ecosystem and to the field of Agile teachings. By playing an instrumental role in an organization’s Agile journey, an Agile coach can have a lasting impact beyond their expected role.

Customer Centricity, cannot and must not be equated with customer collaboration. Most people make this basic error, partly due to the fact that both terms contain the word customer, and partly due to the belief that involving customers in the development process takes care of all their needs and makes them delighted customers. The truth of the matter is that Customer Centricity is a far wider term which requires placing customers’ requirements at the center of all activities; while collaboration is just a tool available to implement the vision of Customer Centricity.

Whenever there is a talk of infusing technology, automation and intelligence in to tasks or processes, the solutions proposed fall in to two broad buckets. The first is the conventional use of the term Artificial intelligence, machine learning, deep learning and cognitive learning, which typically work outside human intervention and are largely driven by some kind of an algorithm to achieve its goal. The handling of regular transactions as well as any exceptions are defined within the AI program and the machine doing the job in case of touch and feel jobs like manufacturing or the algorithm producing the result in case of purely online work. The second category is where Artificial Intelligence is applied to work in conjunction with the humans and human intervention and interaction is a critical part of the successful completion of the job. This second type is known as Augmented intelligence or Augmented reality.

Agile, Lean and Design Thinking place high focus on close collaboration with users and people closest to the work being done. While Design Thinking focuses on finding the right problem through empathetic approach and listening to the users, Agile places emphasis on collaboration and feedback loop, while Lean advocates placing power in the hands of those doing the work. Just like design thinking, a key tenet of effective agile application, irrespective of the Agile framework chosen, is to seek frequent inputs from end users and incorporate the feedback in iterations to achieve the right outcomes. Doing this during early stages of projects includes establishing project goals, defining business increments, writing user stories and / or features, establishing success criteria through definition of done and creating product backlogs from which iteration backlogs follow. Throughout the development process, the inputs through feedback process manifests form a crucial part of delivering the ‘right’ product .

Perhaps, what makes Agile difficult for lot of managers to grasp is that it’s not just a technology, methodology or process that gets implemented within an enterprise’s current culture and assumptions. The Agile way of running an organization seeks to fundamentally redefine the very concept of an enterprise which has prevailed for the last one hundred years. Instead of an enterprise being conceived as an efficient, profitable steady-state machine aimed at exploiting its environment and existing business model and the industry its part of, the Agile organization is a growing, learning, adapting living organism that is in constant flux to exploit new opportunities and add new value for customers.

The test process is not a separate process that can be outsourced or left alone, it is merged with the development processes. The true benefits of Agile testing are revealed when it is used as part of Agile development and accorded an equal importance. The sooner testing team and testers get involved, better it is for the project. Ideally, testers should be part of the overall scheme of things from day one, simply because giving testers a seat at the table from the start provides a higher level of insight into requirements and goals, encourages collaboration and helps hammer home the need to conduct frequent, continuous testing.

Today, most organizations view cloud-based services as a better way to deliver the services they need, including data protection and security. The risks and costs associated with maintaining self-managed, in-house IT security teams who manage organization’s IT infrastructure as a strategic answer to address security concerns is prohibitively high. Add to it the need to constantly upgrade skills and knowledge levels to respond to ever changing security landscape, changing and ever deepening nature of attacks, and redundancy of IT equipment at a faster pace than before, make it a luxury that many cannot afford. That’s precisely why most IT teams today understand that self-managed infrastructure — whether in-house or in third-party data centers — is almost always more tedious, less secure and more expensive than more modern, cloud-based alternatives. When building infrastructure in the cloud, it is important to assess your ability to prevent theft and control access. Determining who can enter data into the cloud, tracking resource modifications to identify abnormal behaviors, securing and hardening orchestration tools, and adding network analysis of both north–south and east–west traffic as a potential signal of compromise are all quickly becoming standard measures in protecting cloud infrastructure deployments at scale.

The thing with new, game-changing technologies, products or ideas, is that to thrive it needs to find an organization that will accept it. Adaption of any new technology has severe implications; it not only changes the organization but often times creates a new industry or segment altogether. An architectural innovation challenges an old organization because it demands that the organization remake itself. The simple explanation is that a market leader in producing printers is much likely to accept breakthrough innovations in printer ink technology as there is no real organizational stress in pursuing that product line, and highly unlikely to accept the idea for a personal computer as there is little organizational mechanism for paying attention to the innovation and nurturing it along.

Any IT product, application or software development effort is made up of stakeholders who are invested in the success of the product. These stakeholders typical comprise customers or users, executives, development team comprising architects, product owners, analysts, Ux/ UI developers, software developers, testers, etc. Scrum and Kanban are two of the most popular Agile approaches to software development. Both the approaches have lot in common, yet both have points of divergence as well. Many experts consider Kanban as the methodology closest to the spirit of Agile principles. It is often contended that while Scrum does contain vital benefits, like continuous feedback loop and the ability for teams to self-organize independently, these benefits are effectively absorbed by the self-arrangement features of Kanban.

Hello and welcome everyone to a brand new series of discussions on technology. We hope you will enjoy these discussions, thoughts, information and ideas as much as we did putting these together.