Scio Spotlight: Talking about passion, projects and videogame development with Pedro Ramírez

Scio Spotlight: Talking about passion, projects and videogame development with Pedro Ramírez

Written by: Scio Team 
Magnifying glass over a puzzle piece with a question mark, representing how side projects help engineers sharpen problem-solving and technical intuition outside formal workflows.

Introduction: Why Side Projects Still Matter in Modern Engineering

Across the software industry, leaders often talk about frameworks, delivery velocity, and architecture. Yet one of the most powerful indicators of engineering maturity is something far simpler, something that rarely appears in dashboards or performance reviews, and something that still separates great engineers from average ones. It is the ability to build things outside work, driven only by curiosity, experimentation, and genuine interest. For many developers, software is both a profession and a playground. The workday revolves around sprint planning, backlog refinement, and delivering features under pressure. But outside of those constraints, there is an entirely different space where creativity unfolds. Side projects give engineers room to explore new technologies, test ideas without bureaucracy, sharpen their skills, and learn in a way that cannot be replicated inside a production environment. Some people contribute to open-source projects. Others tinker with automation scripts or dive into new languages. And some take on challenges that stretch far beyond their comfort zone. This is where today’s story comes in. In this Scio Spotlight, we talk with Pedro Ramírez, Chief Architect at Scio, about a side project that required equal parts discipline, curiosity, and pure passion. Years ago, Pedro set out to build something he had never built before. Not an API. Not a web interface. Not a business application. A full videogame, designed, coded, optimized, published, and shipped to real users. The project became FlyFlyFly, an endless runner released on mobile and still available on the Microsoft Store today. The result was more than a finished product. It became a source of learning, a bridge between craft and creativity, and even an unexpected advantage later in his career. This is the story of what he built, what it taught him, and why leaders should care about what their engineers build when no one is telling them to.
Magnifying glass over a puzzle piece with a question mark, symbolizing how side projects reveal engineering maturity and problem-solving intuition.
Side projects uncover instincts no dashboard can measure—curiosity, experimentation, and the drive to understand how things work.

Section 1: When Curiosity Turns Into Craft, and Craft Turns Into Growth

One of the most common misconceptions in engineering leadership is the idea that side projects are distractions. In reality, the opposite is often true. Engineers who experiment outside their paid responsibilities bring sharper instincts, broader perspectives, and more resilient problem-solving skills into their daily work. For Pedro, this happened almost by accident. “Like many people, I assumed building a small mobile game would be straightforward,” he recalls. “You have game engines, libraries, and enough tutorials online to fill a lifetime. It sounded simple in theory.” It didn’t take long for reality to adjust those expectations. FlyFlyFly seemed small enough to build quickly. But the moment Pedro began prototyping, he realized how different game development is from the typical enterprise or product work most software engineers do. Optimization matters in ways that corporate systems never demand. Memory usage becomes critical. Framerate consistency becomes non-negotiable. Visual assets, performance tuning, collision detection, user input handling, and device compatibility all become part of the same equation. “You suddenly discover how little room you have,” Pedro says. “You try to run something on a slightly older device, and it forces you to rethink the entire way you’re handling resources. You end up debugging physics behavior one minute and reworking asset compression the next.” This level of constraint is rarely present in everyday engineering roles, which is precisely what makes the experience invaluable. It forces engineers to think beyond abstractions, beyond frameworks, and beyond library convenience. It demands an understanding of how systems behave when everything needs to run smoothly and consistently under real, user-facing pressure. Side projects like this sharpen instincts. Pedro didn’t simply build a game, he built an operating environment for himself where learning was unavoidable. And in the process, he developed a deeper sense of how software behaves in the wild.
Software engineer analyzing a holographic interface, representing how curiosity-driven work builds technical craft and stronger engineering instincts.
Curiosity becomes craft when engineers push into unfamiliar territory—and that growth shows up in real projects.

Section 2: The Unexpected Complexity Behind Building a Game From Scratch

Game development is a surprisingly multidimensional craft. Even small games require a blend of systems thinking, creative design, and user experience intuition. For an engineer accustomed to building business software, it can feel like stepping into an entirely different discipline. “You’re not just writing code,” Pedro explains. “You’re designing the interface, creating graphics, deciding how the character moves, balancing speed, difficulty, and even color choices. You become a full team of specialists inside one person.” Along the way, he discovered aspects of development that traditional roles rarely expose. Resource management, for example, became one of the biggest challenges. With limited memory and varying device capabilities, every asset had to be optimized and every decision measured. Another challenge was balancing gameplay. This required experimentation, iteration, and a willingness to rebuild entire components when a mechanic felt too slow, too difficult, or simply not fun. Pedro also had to learn how to market the game, prepare it for digital storefronts, and handle support once it launched. This led to one of the most surprising lessons of the entire journey. While working at Amazon at the time, he realized that his employment contract raised concerns about intellectual property ownership. “It technically made the game their property,” he says. “It created a conflict that made it difficult to maintain or grow the game later.” It was an unexpected but meaningful education in the importance of understanding IP agreements, licensing, and ownership terms, something many engineers overlook until it becomes a problem. All of this made FlyFlyFly more than a hobby. It was a masterclass in end-to-end product development. Pedro walked through every stage, from ideation to launch, while learning skills that would later prove useful in real client engagements and leadership roles. For engineering leaders, this is an important reminder. The most valuable learning often comes from unstructured, voluntary work. Engineers who push themselves through unfamiliar territory develop adaptability, versatility, and decision-making skills that are hard to teach in a classroom or through corporate training.
Fast-moving highway lights symbolizing the speed, constraints, and complexity behind building a game from scratch as a side project.
Game development exposes constraints most engineers never face—turning a side project into a full-scale learning engine.

Section 3: When Passion Projects Influence Real Work and Real Opportunities

Years after launching FlyFlyFly, an interesting opportunity appeared at Scio. A client was exploring the development of an RPG-style game similar to classic turn-based titles like Final Fantasy. They needed a technical lead who understood game mechanics, constraints, and the demands of building an experience rather than a business workflow. Pedro fit that profile immediately. “I was put in charge of the project because of my experience with FlyFlyFly,” he says. “Even though our client paused development later for budget reasons, the work we did and the trust they placed in us was a direct outcome of that personal project.” It’s a perfect example of how passion-driven work can influence professional opportunities in unexpected ways. Side projects demonstrate initiative. They reveal a person’s curiosity, drive, and willingness to explore. They also show how an engineer behaves when there is no roadmap, no product manager, and no established process guiding the way. This is why many leaders value them. They expose intrinsic motivation. Side projects also shape long-term leadership potential. Pedro’s experience gave him a first-hand look at navigating ambiguity, solving unstructured problems, and making decisions without a safety net. These are the same qualities that help teams move through complex transitions and high-stakes architectural decisions. For companies evaluating nearshore partners or expanding engineering teams, this is a meaningful reminder: experience is not just measured in years. It is measured in how people use their time, how they push themselves, and how they build when no one is assigning the work. Passion projects reveal patterns that traditional résumés rarely show. At Scio, these patterns often turn into leadership opportunities because they indicate the kind of engineer who learns continuously, adapts quickly, and sees beyond immediate deliverables.

Comparison Module: What Side Projects Build That Day Jobs Rarely Do

Capability
Built in the Day Job
Strengthened Through Side Projects
Ownership mindset Sometimes Always
Multidisciplinary learning Limited Required
Experimentation freedom Often constrained Unlimited
Resource optimization Only when needed Constant
User experience intuition Varies by role Essential
Ability to self-direct Depends on structure Core skill
Paper airplanes moving forward, illustrating how passion projects create unexpected professional opportunities and reveal intrinsic motivation.
Passion-driven work reveals initiative and adaptability—traits that often open doors to leadership and high-trust technical roles.

Section 4: The Human Side of Building Something for Yourself

Beyond the professional value, there is a deeply human side to building something outside work. When engineers create something purely for fun, they reconnect with the part of themselves that first led them into the industry. The sense of discovery. The desire to understand how things work. The excitement of solving a problem on your own terms. For Pedro, this aspect became even more meaningful because he shared the experience with his son. “We figured out the mechanics together,” he says. “It was fun not only as a developer, but as a dad.” This matters more than most leaders realize. Software development has always been a mix of logic and imagination. Passion fuels both. Engineers who maintain that spark stay curious longer, resist burnout more effectively, and handle ambiguity with greater patience. Passion does not replace hard work, but it lifts it. As Pedro explains, “When you enjoy the work, the hard parts feel different. You still deal with challenges, but they don’t drain you the same way.” This distinction is crucial, especially in technical leadership. Passion generates endurance. Endurance supports mastery. Mastery accelerates growth and increases the quality of decisions engineers make under pressure. Projects like FlyFlyFly become long-term confidence builders. They remind engineers that they can create, solve, and learn even in unfamiliar territory. That mindset strengthens entire teams, especially in organizations where innovation, experimentation, and continuous learning define success.

Conclusion: A Story About a Game, or a Story About Growth?

FlyFlyFly is still available in the Microsoft Store. But the real story lives in the journey of building it, not just the outcome. Pedro learned how to navigate new disciplines. He improved his technical instincts. He gained exposure to product thinking. He discovered unexpected IP challenges. He opened doors to new opportunities at Scio. And he reconnected with the creative spark that drives so many engineers into the field. Every engineering leader knows that great teams are built from people who care about their craft. Side projects help nurture that care. They create environments where engineers push themselves, experiment without fear, and grow in ways formal training rarely achieves. At Scio, we see these qualities often. Our teams combine strong fundamentals with curiosity, creativity, and a constant drive to learn. It is part of what makes nearshore collaboration so effective when the partner is aligned with your culture, expectations, and technical depth. If you’re looking for engineering teams that bring this mindset into your organization, Scio is here to help.

FAQ

  • Yes. Side projects push engineers into unfamiliar territory where they must self-direct, experiment, and troubleshoot new kinds of problems. This sharpens instincts and often accelerates professional growth.

  • Not necessarily. But leaders can create psychological space for engineers to explore ideas. This often leads to innovation, better retention, and more engaged teams.

  • Absolutely. Teams with curiosity-driven engineers tend to adapt faster, communicate more effectively, and bring stronger problem-solving skills to client work.

  • This is where clarity matters. Engineers should understand their employment contracts and IP clauses before publishing or commercializing personal work.

How is FinTech changing the retirement plans of tomorrow?

How is FinTech changing the retirement plans of tomorrow?

Curated by: Sergio A. Martínez

If there is something the FinTech landscape is transforming at an unprecedented pace, it’s the way we look at our finances. From mobile apps that help us control our budget, to online platforms that make investing easier and more accessible for the average person, today we have more options than ever when it comes to managing our money, down to our retirement plans.

How-is-FinTech-changing-the-retirement-plans-of-tomorrow

And it’s not just individuals who are benefitting from these innovations either; businesses are increasingly able to take the opportunity offered by these technologies to streamline their financial operations. Whether it’s reducing the cost of processing payments or making it easier to access capital, new platforms and applications are helping businesses of all sizes to compete every day. And as the FinTech revolution continues to unfold, it’s clear that we’re only just beginning to see the impact that these companies will have on our lives and our future.

And our future is exactly what many FinTech companies are looking to improve, with more and better options for a specific need that is becoming more important each day: retirement plans. Access to retirement plans has long been a growing concern for many Americans, and FinTech startups are taking on this challenge, providing small businesses and everyday people with solutions and access that were previously out of reach.

For many people, traditional retirement savings plans simply aren’t enough to provide the level of security they need in their golden years. FinTech companies are working to change that by developing products and services that can help people save more effectively for retirement. From automated investing platforms to personalized financial advice, the FinTech revolution is helping to make retirement planning more accessible and more efficient than ever before”, says Rod Aburto, Partner and Co-Founder at Scio. 

So, what are some of the key areas where FinTech retirement solutions could offer a new perspective? We’ll look into two sides: From the business side, where offering retirement plans are more affordable and convenient, and on a personal side, with tools helping to navigate the complex world of financial planning.

Overcoming a challenge

For a small business, the process of setting up and managing a retirement plan could be both time-consuming and expensive, even though there are many ways to make an impact in their employees’ lives, the biggest barrier to offering this benefit is the cost; setting up and administering a retirement plan can be expensive, and small businesses may not have the extra cash on hand to cover these expenses, especially when they are just starting.

 In addition, small businesses may not have the same negotiating power as larger companies when it comes to retirement plan providers, meaning they may have to pay higher fees. And yet another barrier is employee participation; for a retirement plan to be successful, employees need to be willing to contribute their own money. However, many workers are reluctant to do this, especially if they are already struggling to make ends meet. 

One of the biggest obstacles to saving for retirement is the high cost of living. Between housing, transportation, and childcare, many families are struggling to make ends meet. As a result, contributing to a 401(k) can seem like an impossible task”, continues Rod Aburto. “It’s difficult for families to save extra money when they rely on credit cards and loans. However, it is still important to save as much as possible for retirement, which is why FinTech companies looking into retirement solutions can make a difference. Every little bit helps, and it is never too late to start saving.

Moreover, some small business owners simply don’t feel like they have the time or expertise to set up a retirement plan, worried about making mistakes or being overwhelmed by the paperwork involved. Nevertheless, thanks to the rise of FinTech, there are now several options that are much more accessible for small businesses. 

For example, let’s look at Penelope, a “401(k) platform that gives small businesses an affordable and easy-to-use way to provide retirement benefits”, according to a profile published in Forbes. What this platform offers is a way for small business owners to set and automate different retirement plans, from pooled employees’ plans to more traditional 401(k), to even individual options for entrepreneurs to establish a strong corporate culture from the start, with minimal hassle. 

And that last point is crucial. What FinTechs are also enhancing with these retirement solutions is the culture of planning and long-term engagement among smaller businesses, helping build a better tomorrow for everyone.

A more personal touch: The rise of the robo-advisor

How-is-FinTech-changing-the-retirement-plans-of-tomorrow-opcional

Another side of the FinTech revolution, beyond helping businesses to offer benefits to their collaborators, is that retirement is also a personal choice on the part of the employee, but the necessary knowledge around this is often not very accessible to the average person, and making decisions on a very complex issue, like finance and investing, can be a daunting task. What could be done here, then?

Arguably, robo-advisors are the most well-known of the FinTech innovations, which refer to automated online services that use computer algorithms to provide financial advice and manage customers’ investment portfolios. These products are increasingly targeting the retirement marketplace. The advent of a computerized approach to financial advice offers huge promise to provide people access to data they need to make smart retirement plans at very low cost”, explains a paper called “The Disruptive Impact of FinTech on Retirement Systems”, which sets to study the actual impact of these innovations in real people’s lives.

In this case, robo-advisors are a new breed of financial advisors that use algorithms and software to automate complex analyses of investments and financial risks. And unlike human advisors, robo-advisors don’t require you to set up an appointment or meet in person, generally with lower fees, making them a good choice for investors looking to be more careful with their bank accounts. 

So, while this technology is still fairly new, it could have a big impact on the way people invest in the future, especially when it comes to planning retirements and financial security for the future, changing the way the financial industry currently works. And this is without taking into account how a huge market for these types of services comprises 50+ people, who tend to have more financial experience, but less familiarity with technology, a challenging gap for many FinTechs looking into this space need to navigate carefully. The same study cited earlier says:

…technological design should be driven by users’ needs. Accordingly, startups should consider how the older population interacts with technology and the unique concerns they have, versus millennials [and] considerations of culture and gender, which should help inform developers to create products that can be personalized for subgroups within the older cohort. Treating this population as one homogeneous group ignores important differences within this diverse population.

So while the idea of making financial decisions based on the advice of a robot might seem strange, the combination of ease of use, data-driven approach, and accessibility with affordable prices offer an interesting alternative for people of any age and tech familiarity to make informed choices about their future retirement investments and opportunities. 

It’s time to start thinking of retirement not as an endpoint, but as the beginning of a new phase. With FinTech companies leading the way, we can look forward to retiring with more options and less worry. Have you started planning for your retirement yet?

The Key Takeaways

  • Retirement is an important issue for everyone and a financial area where the FinTech space can really make a difference.
  • Among the most notable innovations are platforms that make it easier for small businesses to offer retirement plans to their employees, improving their lives and engagement greatly.
  • Robo-advisors that can also help individuals make better financial choices are a great help to build retirement plants, thanks to their data-driven approach that makes it easier to weigh the best options.

Scio is an established Nearshore software development company based in Mexico that specializes in providing high-quality, cost-effective technologies for pioneering tech companies. We have been building and mentoring teams of engineers since 2003 and our experience gives us access not only to the knowledge but also the expertise needed when tackling any project. Get started today by contacting us about your project needs – We have teams available to help you achieve your business goals. Get in contact today!

Is the future of FinTech in the hands of Artificial Intelligence?

Is the future of FinTech in the hands of Artificial Intelligence?

Curated by: Sergio A. Martínez

When most people think of Artificial Intelligence, they probably conjure the Hollywood depictions of evil robots that become sentient or self-aware, and then go out of control. However, even if this is the general pop culture stereotype of AI, the real-life technology is very different, already getting implemented in several key industries to streamline processes and improve efficiency. The Financial Technology sector is no different; AI is starting to have a major impact, from chatbots and digital assistants to complex algorithmic trading, reshaping the way we conceive and manage our finances.

Is-the-future-of-FinTech-in-the-hands-of-Artificial-Intelligence-1

And it’s not just big banks and financial institutions that are benefiting from the power of AI — FinTech startups use it to create innovative products and services that change the way we bank, invest and save, bringing more personalized experiences to customers by analyzing their spending patterns and providing tailored recommendations. 

So, while AI continues to evolve, its increasingly significant footprint on the FinTech industry is making financial services more efficient and accessible, playing a crucial role by helping to automate various tasks, from customer service to fraud detection. For example, AI-powered chatbots can provide personalized financial advice, and Machine Learning is being used to develop predictive analytics tools that can help identify investment opportunities, or red flags to watch out for.

As a result, AI will only become more embedded in FinTech, transforming the financial sector by automating processes and providing real-time insights, and helping cut costs. Perhaps most importantly, AI will give organizations the ability to make sense of the vast troves of data they collect daily, using Machine Learning algorithms to identify patterns and trends that would be impossible for humans to spot. As a result, this technology is poised to profoundly impact the financial sector in the years to come.

However, the popularity of AI solutions in FinTech has also raised questions within the industry; after all, with machines driving more financial systems, is their traditional risk management ready to keep pace with an increasingly automatized approach that brings innovations and disruption almost daily? For any business, it’s important to stay ahead of the curve and make sure you are using AI to benefit your customers and your bottom line, and risk assessment needs to be considered to succeed at it. But what will it look like?

Risk assessment in FinTech: A job for robots?

As FinTech companies become increasingly reliant on AI, the need for robust risk management processes is more important than ever. By its very nature, FinTech is a highly innovative sector, which means new risks are constantly emerging. And while AI and Machine Learning can help to identify these risks promptly, as well as monitor any exposure to them by automating data analysis and providing accurate results, gaps still exist.

One of the main concerns is that AI systems can be biased against certain groups of people, due to the data that they are trained on. If an AI system is only exposed to data skewed in favor of one group of people, it will produce biased results”, says Rod Aburto, Service Delivery Manager and Co-Founder of Scio. “And beyond that, AI systems can be hacked or tampered with, which could lead to disastrous consequences. These tools are still far from perfect, and there is always the possibility that they’ll make mistakes with serious implications, but despite these potential risks, AI remains promising.

Combining Machine Learning and AI can help financial institutions to make more informed decisions, like assessing the impact of new regulations on a business model or identifying risks associated with their products and services, but the availability of data is an important matter: the final assessment is only as good as the information entered into the system. This means FinTech companies need to be especially vigilant in their risk assessments due to the rapidly changing nature of the information. For example, if a training dataset is predominantly male, a Machine Learning algorithm may learn to associate certain traits with being male, leading to biased results when applied to a broader population. 

In the specific case of FinTech, a way that bias can be introduced is through algorithms that have been designed to achieve a particular outcome, rather than being impartial. An algorithm designed to identify creditworthy individuals is likely to be biased against low-income applicants, leaving people in need of these kinds of services out. 

Another challenge for FinTech companies reliant on AI to provide their services is that they are vulnerable to attacks by hackers who could exploit weaknesses in these systems. Hackers could gain access to sensitive customer data or even manipulate the algorithms used by FinTech companies, leading to disastrous outcomes. So when it comes to FinTech, security should be a top concern, and data breaches and security vulnerabilities can have a devastating impact on both consumers and businesses when machines cannot make critical decisions on their own. That’s why it’s so important for fintech firms to have robust security measures and know the risk involved in pure automatization.

A balanced future in FinTech

Is-the-future-of-FinTech-in-the-hands-of-Artificial-Intelligence-3

FinTech is an industry constantly evolving, and there are many good practices around risk assessment, but at its core, risk assessment in FinTech should focus on three key areas: regulatory compliance, customer impact, and business resilience”, continues Rod Aburto about the challenges in pure automatization. “And when it comes to implementing AI tech in this area, responsibility, due diligence, and human intervention are key to ensure they work as intended. These machines are more than capable of digesting data and coming up with insights than almost any person but are not infallible. Without human expertise guiding and implementing actual useful results, it’s easy to render any outcome from AI less than ideal.

AI is revolutionizing the fintech industry at every level, from software development to customer service. According to the International Data Corporation (IDC), “the worldwide market for AI software, hardware, and services is expected to surpass $500 billion by 2024”. As more FinTech companies are using AI to create new and innovative products and services that make financial services more efficient and accessible, it’s important to keep in mind that an ethical, responsible, and effective implementation of AI is one where humans are kept in the loop and can be made accountable for any mistake. AI will only become more embedded in FinTech as the industry evolves, and for businesses, it’s important to stay ahead of the curve and make sure you are using AI to benefit your customers and your bottom line.

So, by conducting responsible and human-curated risk assessments, FinTech companies can stay ahead of the curve and make sure that their products and services are as safe and secure as possible.

The Key Takeaways

  • The FinTech sector is one of the most innovative, and technologies like AI and Machine Learning are finding implementations in almost every area.
  • AI brings a speed of automation of processes, insights, and results without precedent, and while exciting, challenges arise alongside these tools.
  • Traditional risk assessment needs to keep pace with the technological revolution and has to keep a watch out for weaknesses and biases in these systems.
  • Human intervention and interaction will still be necessary for the foreseeable future, guiding these systems and achieving their best outcomes.

Scio is an established Nearshore software development company based in Mexico that specializes in providing high-quality, cost-effective technologies for pioneering tech companies. We have been building and mentoring teams of engineers since 2003 and our experience gives us access not only to the knowledge but also the expertise needed when tackling any project. Get started today by contacting us about your project needs – We have teams available to help you achieve your business goals. Get in contact today!

The future of Artificial Intelligence in software development: Bringing the best of both worlds, today.

The future of Artificial Intelligence in software development: Bringing the best of both worlds, today.

Curated by: Sergio A. Martínez

It’s no secret that software development is a rapidly evolving field. Every year, new tools and technologies are being introduced that promise to make developers more productive, and recently, AI has emerged as one of the most promising for software development. We have talked before about how unlikely (at least for now) that AI programs and tools could completely replace a software developer, but that doesn’t mean that these applications can’t have a profound impact on the way we develop software.

The-future-of-Artificial-Intelligence-in-software-development-1

In fact, alongside no-code platforms, AI is starting to change the way we approach development from the ground up, requiring new skills to make the most of these technologies. AI-powered tools can help developers write code faster and more accurately, and AI-based software testing and debugging tools can help to find and fix software defects more quickly. So, as this technology continues to improve, more AI-based tools will likely be adopted by software developers. However, how will this profession need to evolve in order to adapt to the AI revolution? What skills will be needed, and what repercussions can AI have in the long term?

Prompt engineering: A new skill to master.

As AI continues to become more advanced and available for the average developer, ‘prompt engineering’ will also become a basic skill for the future programmer.

But what is prompt engineering? Simply put, it’s the process of designing and creating prompts that can elicit the desired response from an AI system. For example, if you are planning a chatbot intended to provide customer support, you would need to create prompts that would help the chatbot to understand the customer’s issue and provide an appropriate response. While AI systems are becoming increasingly capable of understanding natural language, they still rely on prompts to some extent. 

In a way, prompt design is like playing a game of charades”, explains the essay “Prompt Engineering: The career of the future?” by Shubham Saboo. “We give the person just enough information to figure out the word using his/her intelligence. Similarly, with [the language prediction model] GPT-3, we give it just enough context in the form of a training prompt to figure out the patterns and perform the given task.” 

As a result, prompt engineering is an essential part of using AI applications, and anybody looking to work with these tools must master them to use their full capabilities in the most efficient way possible. In fact, this skill is becoming more common in all kinds of creative areas, from software to art, where AI applications are getting popular. Jasper.ai, for example, can generate full written content with the correct prompt, and even tools like DALL-E 2 can generate just about any image using the right combination of words. And when it comes to software development, the tools necessary to make this process faster and more efficient are becoming reality.

The machine is my Copilot

The-future-of-Artificial-Intelligence-in-software-development-2

Codex is a family of AI models from Open AI that translates between natural language and code in more than a dozen programming languages”, says the Microsoft GitHub page on prompt engineering. “The power of these AI models is that you can quickly develop and iterate on your ideas and build products that help people do more.

Ultimately, AI applications like Codex could drastically improve the efficiency of software development, making it possible to create better software in less time. If you’re a developer, chances are you already know about GitHub because it provides an easy way to share and collaborate on code. But what you may not know is that GitHub also offers a tool called Copilot, based on Codex, which can be a big help when it comes to writing better code. Copilot is a tool designed to create code suggestions from plain English prompts (for example: “Write a function that adds two numbers and returns the result”), giving you a hand in solving complex coding puzzles, showing you what the code could look like, or what you might need to make it work as intended. It also includes features like code snippets and templates, which can save you time when working on projects. Oege de Moor, Vice President of GitHub, explains Copilot the best:

Because it was trained both on source code and natural language, you can write a comment in English, and then Codex will suggest the code that follows. The technology works similarly to auto-complete in word processing but writing code instead of plain language and completing whole functions at a time. When you type in your editor, an excerpt of your code is sent to the AI, which response with ways to complete what you’re typing.

This could also work as a great teaching tool for people starting to learn to code, streamlining the process and letting its users’ experiment and prototype in a particular language, giving them the chance to test and start over in a very efficient way. Also, it works as a great alternative to no-code platforms where you can hit a ceiling in terms of what you can create, letting a user devise a specific solution by engineering the correct prompt to obtain it.

However, there’s still a long road ahead before Codex, Copilot, or other similar tools become a normal part of software development. For starters, there’s the issue of copyright, a problem shared with DALL-E and other art-generated tools, which have to feed from already created content to generate a result. In the case of Copilot, this means that the AI has been trained on GPL code stored in its servers, which is proven controversial, especially in Open-Source circles that point out that their code can easily be laundered with AI for commercial applications. 

With issues like this, it’s important also to start thinking about the discipline and good practices that these tools will require to actually add up to software development. From where we stand today, AI tools are here to stay, and learning to use them the correct way, or understanding the ramifications they will bring to our industry (reportedly, GitHub is working on an “origin tracker tool” to detect copyright violations, for example), there’s no doubt that the next few years of software development will change radically. 

With an AI companion at your side, whether you’re just getting started with coding or you’re an experienced developer, tools like GitHub Copilot can be a valuable resource for improving your productivity and writing better code. With that in mind, what will you be able to achieve tomorrow?

The Key Takeaways

  • AI tools are here to stay, and it’s important to be ahead of the curve and see the opportunity they bring in software development.
  • One of the most important skills to develop is ‘prompt engineering’: the ability to tell a machine exactly what you need to get the best result possible.
  • Software development is already changing thanks to AI-based coding tools like Codex and Copilot, which promise to make the process of development faster and more efficient.
  • Discipline and good practices are going to become a necessity to use these tools to their full potential while due diligence and copyright considerations will become a ‘must have’.

Scio is an established Nearshore software development company based in Mexico that specializes in providing high-quality, cost-effective technologies for pioneering tech companies. We have been building and mentoring teams of engineers since 2003 and our experience gives us access not only to the knowledge but also the expertise needed when tackling any project. Get started today by contacting us about your project needs – We have teams available to help you achieve your business goals. Get in contact today!

The Intelligent Edge: A new frontier in how we make software

The Intelligent Edge: A new frontier in how we make software

Curated by: Sergio A. Martínez

The intelligent edge is one of the most talked about topics in technology development today, and for good reason – it represents a shift away from the centralized model of computing that has dominated for so long. But along with this new way of doing things comes new challenges, which need to be addressed if the intelligent edge is to fulfill its potential.

Intelligent-Machine-Economy

Creating solutions at the intelligent edge

But what is the intelligent edge? Is it just a mere buzzword, the same way “the information superhighway” was in the 90s, or it is truly a change in the way we approach technology development? Simply put, the intelligent edge focuses on making applications and services more responsive to local conditions and events by moving computation and data storage closer to the devices that generate and use them. For example, imagine an AI assistant like Cortana contained entirely within your phone, analyzing everything (weather conditions, hotel prices, people density on a tourist spot, available parking space, etc.) as you travel, without the need for a constant connection to the cloud or a data center somewhere. That way, we could have applications that are more responsive, reliable, and secure.

The intelligent edge is an on-premises system that collects, processes, and acts upon data. Typically used within the Internet of Things arrays, the intelligent edge uses edge computing to reduce response times, bandwidth needs, and security risks. Since all the actions are taken on-premises, the data does not need to be sent to the cloud or a data center to be processed”, is the definition given by Insight.com.

And because they’re designed to work even when there’s no connection to a central server, they’re perfect for mobile and distributed environments, a technological paradigm that will become more important moving forward, from retail to healthcare. In retail, you can already see retailers are using the intelligent edge to provide real-time customer service and personalized product recommendations, and in healthcare, it’s being used to monitor patients’ vital signs and provide early detection of potential health problems, and the list goes on. 

In consequence, the intelligent edge is a revolutionary way of utilizing recent advances in artificial intelligence and machine learning, not only an advantage for those who are already ahead but also creating new opportunities by challenging organizations to embrace these technologies wholeheartedly.

A tangible cyberspace?

A tangible cyberspace?

In the future we once envisioned back in the 90s, when the Internet was beginning to gain an important place in our lives, we “entered the Matrix”, so to speak, where a digital reality existed separately from our everyday lives. But what actually happened is that “the Matrix” slowly got incorporated into our physical space; augmented reality, the Internet of Things, streaming services, autonomous machines, IA assistants, and more aren’t meant to transport us to a different (digital) existence, but to bring its possibilities to our daily lives, into our real world. 

 And the intelligent edge is where the physical and digital worlds come together, presenting a whole host of challenges for software developers. As a complex ecosystem of devices, sensors, data, and connectivity, it requires a new approach to development because traditional approaches simply don’t work in this environment. The challenges the intelligent edge presents are numerous, but they can be boiled down to three main areas: data management, security, and connectivity. 

  • Data management. Data management can be challenging because the data at our intelligent edge is often unorganized and distributed.
  • Security. The intelligent edge is a hotbed for hackers and cybercriminals, trying to take advantage of the security measures taken there.
  • Connectivity. Connectivity is a challenge because the intelligent edge is constantly changing and evolving.

These challenges are daunting, but they can be overcome with the right approach to development. After all, the intelligent edge it’s where the rubber meets the road, where developers are pushing the boundaries of what’s possible; it’s all about creating applications that are responsive to users’ needs and context, and that can make decisions on their behalf. It’s about creating software that is truly smart and can help users get the most out of their devices. It’s about creating applications that are always available, even when there’s no Internet connection to rely on.

But even with these challenges, the intelligent edge is the future of software development, and any organization that wants to stay ahead of the curve needs to start thinking about how to design applications to take full advantage of this new paradigm.

Looking for DevOps

Ghost-Colleagues

The set of development practices of DevOps, which bridge the gap between software developers and IT operations while shortening the production cycle, might hold an answer to the challenges of the intelligent edge. After all, the goal is to promote communication and collaboration between these two groups to improve the overall efficiency of the software development process required by this paradigm, and DevOps it’s characterized by a focus on automation, often using tools such as Puppet and Chef which allow developers to spend more time on writing code, and less time on manually deploying and configuring software. 

In addition, DevOps practices often emphasize the importance of monitoring and logging, as this can help to identify problems early on and prevent them from becoming major issues. By bringing developers and IT operations closer together, DevOps has the potential to vastly improve the quality and efficiency of software development, as analyzed in this article by Forbes Magazine

DevOps is the key component to assemble complex embedded software at the intelligent edge. Traditionally, embedded software developers wrote code. When they were finished, and the application had been through quality assurance, the embedded “Ops” (production) installed the systems. This sequential “waterfall” model is too slow for the intelligent edge, which is operating in real-time.”

Thus, when developing software for the intelligent edge, DevOps is king. By automating the software development process, DevOps helps developers create high-quality code faster and with fewer errors, automating the deployment of code to testing and production environments, making it easier to keep track of changes, and ensuring that code is always up to date. As a result, DevOps can help proponents of the intelligent edge move faster and achieve their goals with fewer headaches.

Under the DevOps banner, different embedded developer personas (e.g., platform developers, application developers, operators, data scientists, or DevOps engineers) work in scrums. They push out new software releases as part of agile teams and do it so rapidly that it’s better to integrate the Ops and QA (quality assurance, testing) teams into the development process”, continues the aforementioned Forbes article.

So, as the demand for software that can handle the challenges of the intelligent edge grows, so too will the need for DevOps, which consequently will drive up the demand for faster and more reliable software. That way, DevOps will continue to play an important role in the development of software for the intelligent edge.

Living on the edge with Nearshore

Creating solutions at the intelligent edge

Businesses are becoming more reliant on data, and the need for intelligent edge solutions is only going to grow. However, among the challenges associated with developing these solutions, one of the biggest is finding the right talent. There is a global shortage of skilled workers in the field of software development, and this problem is only compounded by the fact that many businesses are located in developed countries where technological labor demand is high. Nearshore development can help to overcome this by providing access to talent without sacrificing communication or compromising outcomes. 

The resulting collaboration between businesses and nearshore development companies can help to create an ecosystem of innovation that leads to better results, and by overcoming the challenges associated with developing intelligent edge solutions, businesses can stay ahead of the curve and keep their competitive advantage.

In today’s fast-paced world, software development needs to be agile and adaptive to keep up, and by reducing silos and communication barriers between these two teams, DevOps enables quicker and more reliable software delivery”, says Rodimiro Aburto, Service Delivery Manager and Co-Founder at Scio. “In addition, DevOps also brings other benefits to Nearshore software development, such as increased collaboration, better quality code, and improved customer satisfaction, helping businesses respond faster to market changes and stay ahead of the competition, especially when it comes to working at the intelligent edge.

As a result, DevOps is a key ingredient for any successful Nearshore software development team, especially in today’s business world, where the intelligent edge will seemingly become a norm. And for businesses looking to prepare for this paradigm, the answer is spread out across multiple locations in Nearshore collaboration hubs, where teams of experts can work together to find the right solution, and businesses can tap into a wide pool of talent, which can help to speed up decision making and prepare for a new approach in software development.

So, if you’re looking to get ahead in the world of intelligent edge development, make sure you’re using DevOps. It’ll make your life a whole lot easier. As the world becomes more connected, nearshore collaboration hubs are becoming an essential part of doing business.

The Key Takeaways

  • As tech applications move towards a purely mobile environment, a new paradigm in software design approaches: the Intelligent Edge.
  • This intelligent edge will require new solutions to development challenges, mainly the fact that these applications will always be “on”.
  • Frameworks like DevOps might offer a solution to “change the tire while the car is running”, but this presents further challenges.
  • Access to talented developers and engineers will grow, and looking towards Nearshore development is positioned as one of the best solutions around.

Scio is an established Nearshore software development company based in Mexico that specializes in providing high-quality, cost-effective technologies for pioneering tech companies. We have been building and mentoring teams of engineers since 2003 and our experience gives us access not only to the knowledge but also the expertise needed when tackling any project. Get started today by contacting us about your project needs – We have teams available to help you achieve your business goals. Get in contact today!