The Rubber Duck Method: What is the explanation behind this debugging approach?

The Rubber Duck Method: What is the explanation behind this debugging approach?

Project Management, Technologies

Curated by: Sergio A. Martínez

Debugging software is an important, if often tedious, the task for any programmer. Finding and removing errors generating crashes, freezes, or incorrect results is critical to ensuring the quality of a piece of software, and while some bugs can be fixed with a few simple tests, more difficult ones require special approaches and techniques. And thankfully, there are many resources available to help programmers debug their software; after all, with patience and perseverance, even the most difficult bugs can be squashed.

The Rubber Duck Method: What is the explanation behind this debugging approach?

One such technique is the popular Rubber Duck method, which may already be familiar to a seasoned developer. In short, the Rubber Duck method is a debugging approach in which developers explain their code line by line to an inanimate object, such as a rubber duck. This may sound silly, but it’s an incredibly effective way to find and fix mistakes. 

“Computers process information differently than humans do. Anyone who’s first learning to program understands this well. What’s hard about programming for a beginner isn’t really big hard esoteric concepts, but that you’ve got to be so painfully exacting in how you describe everything to a (dumb) computer. That’s why we do rubber duck debugging.”

However, have you ever been curious about why this approach works? What exactly happens in our brains when we verbalize a problem to someone else (even if that someone just happens to be a bath toy), that could lead to a solution that was obvious all along? And what is the best way to implement this method to finally find and solve that bug that has been bothering you all week?

The challenge of language

Computers are dumb. And we don’t mean that in a Luddite, anti-tech sort of way, we mean it in the original definition of “dumb”: incapable of human speech. And speech here is more than just talking; speech includes context, mood, choice of words, familiarity, and an infinity of other variables that a computer can’t understand (yet).

Of course, this doesn’t mean that we cannot communicate with computers, it just means that we use specialized languages to do so, and every single one of them works with the principle that computers are dumb: unless you tell a machine exactly what they need it to do, or how to react when something happens, they will not produce a desirable outcome. Thoughtful Code put it best:

“‘Is it cold outside?’ is a question that most humans, having some idea of the weather, will answer pretty easily. They’ll say something like, “No, it’s pretty nice.” Asked that question, a computer — or a really finicky and hyper-rational person — will need you to define each of those words.”  

A computer understands the most literal and absolute terms and learning to manipulate those terms is the basic principle of programming. This also means that computers don’t make mistakes, people do. So, if something within the instructions given to the machine doesn’t add up, then the program will not work as intended, and finding the exact place where the communication between a person and a computer got out of alignment can be a challenge. Here’s where the rubber duck comes in handy, thanks to the way we process language.

Here’s a fun fact: did you know that reading, writing, and speaking are located in completely different parts of our brain? Our understanding of the way we use and apply language is always evolving, but it is understood that we use different functions depending on the type of language we employ, which is why it’s so useful to verbalize a problem to find a solution: you involve a completely different part of your mind to help.

Of course, the Rubber Duck method is not useful only in software development, but since computers are very linguistically complex tools (being probably the only ones we need to “speak to” to use), verbalization is useful here, forcing developers to slow down and think about the minute details of their code, which can help to spot mistakes that they would otherwise overlook. As the blog “The Psychology Behind Rubber Duck Debugging” puts it:

“A lot of times, I’ve experienced some programmers that will ask my help about a specific bug they are fixing. I will then ask them how their application and their code works. I literally have no idea how to fix a program that is not mine and have no idea about the flow. However, I let them explain the flow of the process and the connection between functions and files. Oftentimes, they think of a solution before I even understand what is happening. Many people have been so thankful for me — for doing literally, nothing.”

Programmers understanding themselves

The Rubber Duck Method: What is the explanation behind this debugging approach?

You can see the same principle at work in the classroom. Teachers probing students with questions are intended to make sure a lesson has been learned, forcing the students to consider and explain it by themselves. The only difference is that a programmer using the Rubber Duck method is taking both roles (teacher and student) at once. 

In other words, this method allows developers to share their thoughts with a neutral party, questioning and probing themselves regarding their code, which can help identify areas of confusion or misunderstanding. And most importantly, it encourages developers to develop a clear and concise explanation of their code, which can be useful for future reference. 

“The real magic doesn’t happen on the rubber duck itself (sorry, Duck Norris). However, it happens in our minds. It uses the same psychological principle wherein we are encouraged to explain to ourselves why we did such actions and have a self-realization about what we’ve done. It is usually used by most psychologists to fully understand a person and, at the same time, for the person to understand himself/herself fully.”

And understanding yourself is fundamental to being a good programmer. Just like writing any other thing (a novel, or a sheet of music), everyone has their own style, approach, and technique when coding an application, which makes the ability to explain what you wrote so important; if you aren’t able to understand your process inside and out, then debugging will always be a challenge, especially when working as part of a team, where the code must always be in sync. In fact, the Rubber Duck method can be used as a form of collaboration, as another programmer can serve as your rubber duck and offer feedback or suggestions while you go through your code trying to find an answer.

“When working on a software development project, it’s important to have a good collaboration method in place, and the rubber duck method is one way to ensure that everyone on the team is on the same page”, says Jesús Magaña, Senior Project Manager at Scio. “It can help a developer to articulate his or her thought process, and as a result, team members can quickly identify any gaps in understanding and address them before they cause problems. Additionally, the rubber duck method can help to uncover errors in logic or coding syntax, and overall is an effective way to ensure that everyone on the team can contribute.”

In a Nearshore development environment, where collaboration has come a long way in recent years, the Rubber Duck method can also be useful to bring keep everyone on the same page by improving communication, helping maintain contributions clear, and easing the challenge of solving a tough bug even in remote settings (where a developer may not have anyone to immediately bounce ideas or solutions during debugging), which can help projects to come together more easily. After all, Nearshore software development has its challenges, but by using the proper approach (or bath toy), teams can overcome obstacles and build better software together.

The Key Takeaways

  • A bug in the code is basically a mistake in communication between a developer and a computer.
  • Following this, it’s no wonder that approaches to problem-solving like the Rubber Duck method can help to find the precise place where a code is not working.
  • Although you only need something to talk to (like a rubber duck), this process can involve many people in a team, offering advice and feedback.
  • However, in remote setups (like with a Nearshore development partner), having a way to find and fix bugs without the insight of anyone else can be a valuable resource.

Scio is a Nearshore software development company based in Mexico where we believe that everyone deserves everyone should have the opportunity to work in an environment where they feel like a part of something. A place to excel and unlock their full potential which is the best approach to create a better world. We have been collaborating with US-based clients since 2003, solving challenging programming puzzles, and in the process showcasing the skills of Latin American Engineers. Want to be part of Scio? Get in contact today!

“Soft Tech”: Bridging the gap between technology and mindfulness in the workplace

“Soft Tech”: Bridging the gap between technology and mindfulness in the workplace

Technologies

Curated by: Sergio A. Martínez

We all know how it feels to have a long, stressful day at work. After sitting in front of a computer for hours, staring at code on a screen, or attending back-to-back meetings in faraway places, the last thing you probably want to do is come home and use even more technology, even if it is to relax. 

“Soft Tech”: Bridging the gap between technology and mindfulness in the workplace

However, there are some great ways to take advantage of technology to unwind after a stressful day, from streaming music to meditation apps can help to calm your mind and ease anxiety, and this is thanks to the rise of the “self-care” movement and increasing awareness of the critical importance of mental health in the workplace, where the plague of burnout and social anxiety has made more difficult for many developers to keep a healthy relationship with themselves. 

However, when people think about self-care, they often think of things like taking a bubble bath or going for a massage, but this is far from the truth. Self-care is an important tool for software developers, who do an activity that can have a physical toll (is well known how sitting in front of a computer for long hours can lead to eye strain, back pain, and even carpal tunnel syndrome, for example), as well as a mental weight thanks to the continuous challenge of solving technological puzzles under constraints almost every day. 

And today, this is the raison d’être behind the rise of a new field of software development currently known as “soft tech”; the idea of creating applications, interfaces, and programs whose purpose is helping us take care of ourselves, especially during those short windows that sometimes appear during a stressful day (or week, or month).  The essay “Radical Softness” by Kat Brewster, from the boutique videogame magazine A Profound Waste of Time, explains it best:

“To be radically soft in the digital age is not simply to recognize caring for one’s self as potentially a radical act, but also to recognize the unique strengths, limits, and realities of soft things. The radicalization of organic, messy, squishy, real-world bodies through creative technologies”.

“Soft tech” has been gaining traction during the last decade, and that shot up in importance since the COVID pandemic began in 2020, helping people to get through the isolation and anxiety that those circumstances brought in. In short, what “soft tech” wants to accomplish is using technology to create self-care tools to relax and regain a lost balance, a few minutes at a time. And when it comes to software development of every kind, whose demand skyrocketed during the pandemic, creating unending deadlines to meet and problems to solve, these kinds of applications can be a great resource to take care of oneself.

The best “soft tech” applications you can get

It seems like everywhere you look these days, a new app or software tool is promising to help you take better care of yourself. And it’s no wonder that this is becoming such a popular topic, especially with so many people moving towards working remotely, which can be isolating depending on your set-up. When you’re not surrounded by colleagues and are just working all the time, it can be easy to let your health and well-being fall by the wayside, but with soft tech apps, you can stay on track and make sure you’re taking care of your mental health. 

Many of these apps even offer helpful tips and articles on everything, from reducing stress to eating better, and with so many people now working remotely, it’s easier than ever to find an app that fits your needs and lifestyle. Whether you’re looking for help with meditation, fitness, or diet, there’s sure to be an app that can help you out, so we compiled some recommendations from our team on the best ones you can get right now:

Soft-Tech-Bridging--mindfulness-in-the-workplace-headspace

Headspace

If you’re looking for a meditation app that will help you relax and de-stress, then you should check out Headspace. This app is extremely user-friendly, and it has a ton of great features; you can choose from a variety of different guided meditations, and some helpful animations that explain the concepts behind this practice. In addition, the app keeps track of your progress, so you can see how your meditation practice is improving over time. “I’ve been using Headspace for a while now, and I can feel a notable difference”, says Denisse Morelos, Marketing Executive at Scio. “With just ten minutes spent on it, my day can always get better.”

Soft-Tech-Bridging--mindfulness-in-the-workplace-mountain

Mountain

This is a simulation game with a pretty simple concept: the app procedurally generates a digital mountain, with its own geography and climate, and you watch it evolve through simulated time (hours, days, years). It sometimes generates some insights to share, but that’s pretty much it. It doesn’t have controls, or anything else; it’s about stopping and enjoying the passage of time, a pretty calm, and even meditative, experience.

Soft-Tech-Bridging--mindfulness-in-the-workplace-mountain

Viridi

Depending on the type of person you are, you might find gardening either very stressful or one of the most rewarding pastimes you can have. If you are one of the latter, Viridi was made for you. Similar to Mountain, this game lets you watch the growth of a digital object (in this case, a succulent plant), giving you the task of watering and taking proper care of it, accompanied by nice, soft visuals and a relaxing atmosphere with nothing pressing on you.  

Soft-Tech-Bridging--mindfulness-in-the-workplace-throw-cubes

Throw cubes into brick towers to collapse them

Yes, the title tells you everything you need to know: a “sandbox” game where you can generate block towers (choosing everything from the shape of the bricks to the configuration of the tower, to even the parameters of the physics), and you just topple it down throwing cubes, selecting their size and mass, or even dynamite, if you want something messier. It’s basically a digital Jenga tower that you can collapse over and over, so just put some of your favorite music as background and unwind after a stressful day. “Toppling down writer’s block is more literal than you might think”, says Sergio Martinez, Content Manager at Scio.

An application for every need

Nearshore and FinTech: Easier than you may think

“Technology doesn’t need to be this hard-edged dark thing. It can be something that embraces your body, where the interfaces are designed around you, where the colors are warm and gentle, and promote health and well-being. And that’s really different from the attitude a lot of people had in the 90s, which was ‘Jack me in the Matrix and get rid of my physical body”, indicates the aforementioned “Radical Softness” essay.

We know that, as a software developer, a lot of your time is spent sitting in front of a computer screen. And while you might be used to working long hours, it’s important to make sure that you’re taking care of yourself both mentally and physically. That’s why learning some basic self-care techniques can be so important; things like getting enough sleep, eating healthy meals, and exercising regularly can help improve your focus and concentration and reduce your stress levels, and something as simple as an application on your phone can make the difference in your day.

It’s no secret that the workplace can be stressful. But by taking a few to focus on your wellbeing, you can increase your productivity, improve your mood, and reduce your anxiety levels. So, if you’re feeling overwhelmed at work, be sure to download a self-care app and give yourself the break you deserve.

The Key Takeaways

  • Self-care is not bubble baths and having your favorite tea; it’s a discipline where you take proper maintenance of your physical and mental health, keeping a proper balance in your life.
  • In software development, which saw demand skyrocket during the pandemic, taking proper care of yourself is becoming more important than ever to keep performing as well as you can.
  • This resulted in the rise of “soft tech”, applications meant to help you reach a state of relaxation through meditation guidelines, or simply engaging, low-stake activities designed to bring mindfulness a few minutes at a time.

Scio is a Nearshore software development company based in Mexico where we believe that everyone deserves everyone should have the opportunity to work in an environment where they feel like a part of something. A place to excel and unlock their full potential which is the best approach to create a better world. We have been collaborating with US-based clients since 2003, solving challenging programming puzzles, and in the process showcasing the skills of Latin American Engineers. Want to be part of Scio? Get in contact today!

Optimizing for licensing versus optimizing for performance: A complex IT puzzle

Optimizing for licensing versus optimizing for performance: A complex IT puzzle

Technologies

Curated by: Sergio A. Martínez

It’s not a secret that IT environments are getting more complex by the day, with every new product and application nowadays needing deployment across multiple clouds, data centers, and architectures, which makes optimization through multiple licenses and states an ever-increasing challenge. And that’s without mentioning that our current path to digitalization was sped up considerably after the COVID-19 pandemic pushed our need for software solutions further away.

Optimizing for licensing versus optimizing for performance: A complex IT puzzle

This complexity is such, that according to Flexera’s 2021 State of IT Visibility report, “less than 25% of IT leaders have complete visibility into their IT estates”, which is a mind-blowing fact once we digest it properly; it means that up to 75% of our current IT environments have unknown areas that pose a challenge to the development and implementation of many software solutions.

But why does this happen? 

The truth is, organizations today are under the pressure to drive more value from IT investments, and as a result, leaders are always looking for ways to optimize their IT estates, creating a very specific challenge in today’s software development, creating a situation where a company has to choose between optimizing for licensing and optimizing for performance. And this is key for the success of any project.

Performance Vs. Licensing

Keeping Your Compliance: The other meaning for “KYC”

“As leaders look for ways to optimize their IT estates, they are challenged with choosing between optimizing for licensing and optimizing for performance. Each one has implications for the other, and without a holistic approach, organizations must choose where to focus their efforts”, explains this article published by IBM. In short, an organization should look to integrate applications (that is, “optimizing for performance”); however, since most third-party software charges a licensing fee to use them at business level, carefully weighing options that fit within budget (or “optimizing for licensing”) could make or break a project.  

So while it is important to optimize your software options for performance, choosing the applications, platforms, or software that best suit your needs it’s also important, and a balance must be struck between the two, understanding the advantages and disadvantages they bring. On one hand, when optimizing for licensing, leaders need to consider the type of license that is best suited for their business needs, how many licenses they need, and how they can get the most from them. A license from a big corporation like Oracle, for example, can charge up to 22% of the total price in licensing, so having multiple ones without careful consideration can be quite a hit to the bank account.

On the other hand, when optimizing for performance, leaders need to focus on how they can improve the efficiency of their systems and make them more effective, making financial considerations less of a priority, although it’s rare when an organization can do this without immediate concerns. So to make the best decision, leaders need to carefully weigh options and choose the path that will help them meet their goals.

Controlling your IT states

Nearshore and FinTech: Easier than you may think

“Traditional Software Asset Management (SAM) and IT Asset Management (ITAM) help organizations to understand where licenses are deployed, how software is being used, what versions of software are deployed, and if license use is compliant. This approach yields substantial benefits, but does not provide mechanisms to optimize on a continuous basis”, continues the aforementioned IBM article about some solutions currently implemented.

The thing is, current IT environments are so complex, that manual intervention is often required to understand a system holistically, especially when critical data gets ‘siloed’ in specific IT states, making it unlikely to have a complete view of the organization. After all, it’s easy for a growing company to look for solutions in the short term, and end with critical data concentrated in an external platform, creating issues to distribute it properly if it doesn’t play well with the rest of the IT environment. For example, cloud technology that might be challenging to troubleshoot if errors or other issues occur.

“What many [companies] don’t realize is that a software usage metering tool is just the first step, not the end-all and be-all, of managing these expensive software assets. The wide array of features and functionalities of software usage metering tools are only valuable if you know how to properly use them to accomplish your software license optimization goals.”

So to facilitate the task of implementing better automation into a processes, organizations need to be very smart about the tools, platforms, and systems they adopt into their IT environments, giving weight to the pros and cons of licensing a more uniform product, what the company is trying to accomplish product and/or service-wise, and the best way to achieve a good outcome.

“Combining license asset data and application performance data with intelligent automation gives IT leaders the visibility needed to optimize their IT estates while ensuring they remain in compliance”, concludes the IBM blog.

A solution in smart collaboration

As more and more organizations are outsourcing their IT needs to remain competitive, looking to optimize their spending and remain compliant with the license contracts without losing visibility into the entire IT estate, an answer can be found in Nearshore collaboration. With a Nearshore partner, an organization can gain visibility into their IT estate while optimizing their technology investments, getting the best of both worlds: the ability to remain compliant and the flexibility to optimize your technology investments.

This kind of collaboration can help simplify this systemic complexity by providing a single point of contact for all of their IT challenges by developing applications and products suited for their own context. The reason is that Nearshore development enables better collaboration between teams thanks to a close geographical location, and as a result, it’s a great way to combat the complexity of today’s IT environments. 

By working with a Nearshore partner, you can get the benefit of their expertise in managing complex deployments by making it easier to coordinate and manage projects, a great solution for companies that are looking to simplify their IT environment. The reality is that, as traditional workforces evolve, organizations to start investing in digital transformation efforts to keep up, and while the balance between licensing and performance is still an important consideration, choosing to develop internal tools and applications to reach a digital workplace is becoming more feasible thanks to the Nearshore model, which can help organizations fill skills gaps and reduce costs, 

However, it’s important to choose a partner that understands your culture and values, so while collaboration tools can help remote teams stay connected and aligned, they need to be used effectively. In other words, the workplace (as well as the IT environments that come along with it) is changing, and organizations need to be ready for it. So if you’re looking for a way to stay competitive in today’s digital world, and considering your options between optimizing and licensing, maybe Nearshore outsourcing is the answer you are looking for.

The Key Takeaways

  • Choosing a software application to implement in your organization requires a careful balance between optimizing for performance and optimizing for licensing.
  • Many of the bigger cloud-based service platforms can offer all the solutions you need, but the licensing costs, plus the risk of siloing information in an external system, could pose some issues in the long run.
  • However, depending on your needs and the size of your organization, opting to develop custom solutions that hit a performance target without getting tangled in too many licensing issues is possible by collaborating with a Nearshore outsourcing company.

Scio is an established Nearshore software development company based in Mexico that specializes in providing high-quality, cost-effective technologies to help you reach new heights. We have been developing 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’ll be happy to help you achieve your business goals.

DevOpinions: Is the Python language here to stay?

DevOpinions: Is the Python language here to stay?

Technologies

Curated by Sergio A. Martinez 

Introduction: Why Python Still Shapes Modern Engineering

More than three decades after its release, Python continues to stand at the center of software conversations across enterprise engineering teams, university classrooms, data labs, and product-led organizations. Its usefulness spans far beyond its early reputation as a “beginner-friendly” language. Python sits at the core of high-impact systems, from machine learning pipelines to large-scale backend services, automation frameworks, and distributed research platforms.
Its position at the top of the TIOBE Index in recent years isn’t an accident. Python has grown into an ecosystem that powers some of the most influential platforms in the world — Instagram, Pinterest, Dropbox, and large components of Google’s App Engine among them. It is also the default instructional language in hundreds of universities, training an entire generation of engineers to think and build in Python first.
However, popularity alone doesn’t tell the full story, especially for engineering leaders who need clarity around long-term maintainability, scaling concerns, staffing challenges, and architectural trade-offs. The real question isn’t “Is Python popular?” It’s “Does Python remain strategically relevant for modern software companies evaluating longevity, cost, and capability?”
This article examines Python through the lens of U.S. engineering leaders — CTOs, VPs of Engineering, technical founders, and architecture owners — balancing what Python does extraordinarily well with where it falls short. We also weave in the firsthand experience of two Scio engineers, Martín Ruiz and Elier Ramos, to understand how the language behaves in real production environments.

Section 1: Why Python Earned Its Place in Modern Engineering

Python’s staying power can be traced back to one idea: reducing cognitive load for developers. Its syntax, structure, and conventions were designed to help teams write clear code with minimal ceremony. In large organizations where onboarding speed, cross-team alignment, and maintainability are constant priorities, these traits are incredibly valuable.
1. Readability as a Design Principle
Python’s whitespace-driven structure forces developers to write code that is visually consistent. This has two major effects:
It lowers the barrier to entry for incoming engineers.

It makes large codebases easier to reason about, especially in long-lived enterprise systems.

Engineers often describe Python as “executable pseudocode,” and that is more than a marketing line. For U.S. teams working in hybrid or distributed models — including nearshore teams — readability directly impacts productivity, handoff quality, and defect rates.
2. Multi-Paradigm Flexibility
Python supports procedural, object-oriented, and functional programming styles. As Martín Ruiz notes:
“It’s possible to build the same type of program you’d create in C, Java, or C#, but with far more concise code.”
That flexibility makes Python a useful choice for prototyping, refactoring, or iterating on complex logic where teams don’t want to wrestle with boilerplate.
3. A Mature, Expanding Ecosystem
Python offers one of the largest standard libraries in the industry. Combined with PyPI’s extensive ecosystem, it gives teams immediate access to tools for:
Data analysis

Machine learning

Web APIs

Automation

Scientific computing

DevOps workflows

Testing frameworks

As Elier Ramos puts it:
“It’s a language focused on engineering, simulation, and analysis, but it can also replicate what other languages do, making it a sort of all-in-one.”
This ability to stretch across domains is especially valuable for tech organizations trying to unify scattered toolchains or build internal platforms.
4. Ideal for ML, AI, and Research Work
Python’s rise coincides heavily with the explosion of machine learning. Libraries like NumPy, TensorFlow, PyTorch, and scikit-learn have turned Python into the default language for data-driven engineering. Universities and R&D teams rely on Python because it allows rapid iteration and shared collaboration.
Taken together, these strengths explain why Python won over the last decade — and why many engineering leaders still consider it essential today.

Section 2: Where Python Shows Its Limits

Every engineering leader knows that no language is perfect. Python is no exception. Its biggest strengths — flexibility and dynamism — also introduce risk and technical debt when structures are not enforced rigorously.

1. Dynamic Typing Cuts Both Ways
Python’s dynamic nature is powerful for rapid development but dangerous for scaling without discipline. Martín summarizes the risk clearly:
“Because Python doesn’t have as many restrictions as other languages, the developer is responsible for enforcing clean practices. It’s easy to generate unreadable code, and the language is more prone to errors because variables can take any type.”
Dynamic typing can introduce runtime failures that languages like Java, C#, Go, and TypeScript would block at compile time.
This requires teams to enforce:
Strong linting

Type hints (PEP 484)

Rigorous code reviews

Clear architectural boundaries

Without these guardrails, Python codebases can spiral into ambiguity fast.

2. Performance Constraints
Python’s interpreted nature can’t match the performance of compiled languages like C++ or Rust. For CPU-intensive operations or real-time systems, Python may introduce unacceptable latency.
While workarounds exist — C-extensions, PyPy, Numba, and Cython — these often complicate the simplicity developers love about Python.

3. Not Built for Low-Level or Embedded Systems
Python’s design makes it less suitable for:
OS-level tooling

Network drivers

Embedded or resource-constrained devices

High-performance game engines

For teams building hardware-adjacent products, Python is often a secondary language rather than the core implementation.

4. Architectural Drift and Pattern Inconsistency
Because Python enables many programming styles, teams may drift into inconsistent architectures. Elier notes:
“Design patterns and dependency injections can get lost very easily. You can end up with too many instantiated objects, and it becomes hard to follow.”
This creates risks in long-term maintainability — especially for companies with large or rotating engineering teams.

5. Market Competition for Senior Python Engineers
Python’s popularity works against hiring teams. Large enterprises, FAANG companies, and AI labs aggressively recruit Python engineers, shrinking the available talent pool. This increases time-to-fill for senior positions and encourages organizations to explore nearshore or hybrid models to maintain velocity.
These issues don’t diminish Python’s relevance — they simply clarify where leaders must be intentional about controls, team structure, and architectural discipline.

Section 3: Python’s Future — Stable, Evolving, but Not Untouchable.

Python’s future isn’t guaranteed by dominance alone. Its continued relevance will depend on how well it adapts to three modern pressures: mobile acceleration, performance-driven engineering, and AI-powered development.
1. Mobile Development Isn’t Python’s Strength
As referenced in Data Towards Science, Python wasn’t designed for mobile environments. Python-based mobile apps can function, but rarely at the level expected in modern app ecosystems. Engineering organizations building mobile-first products typically rely on:
Swift (iOS)

Kotlin (Android)

React Native / Flutter for cross-platform

Python, in contrast, remains a backend, ML, and automation powerhouse — not a primary mobile choice.
2. The Rise of High-Performance Languages
Languages like Rust, Go, and even modern C++ occupy the performance-centric niche Python can’t realistically reach. Engineering teams increasingly pair Python with faster languages where needed. For example:

Use Case
Python Fit
Better Alternatives
Data science, ML, automation Excellent —
Backend API services Strong Go, Node.js
Systems programming Weak Rust, C++
Mobile apps Limited Swift, Kotlin
High-performance computation Moderate (with extensions) Rust, C++

This hybrid approach will likely continue to define Python’s role in modern stacks.

3. AI and ML Keep Python at the Center
As long as the AI ecosystem continues to build around Python, the language will remain essential. Research teams, academic institutions, and enterprise ML groups align around it because no other language offers the same blend of readability, library support, and community size.

4. A Legacy That Ensures Long-Term Relevance
Even if a “next big language” overtakes Python in the future, millions of existing Python systems will require maintenance, updates, and integrations. That alone ensures Python will remain fundamental knowledge for engineers.
Martín captures this well:
“Python can be high risk and high reward. When constructed and documented carefully, the results are formidable.”
Python’s future is stable, but evolving — not a default choice for everything, but a durable, strategic one for many workloads.

Section 4: What CTOs Should Consider When Choosing or Continuing with Python

Engineering leaders evaluating Python for upcoming initiatives should approach the decision from a practical, not emotional, angle. Python’s popularity is not a reason to choose it — its alignment with goals, scale, architecture, and talent strategy is.

1. Python Is a Strong Fit When:
Your team needs rapid iteration cycles.

You’re building ML, automation, analytics, or research-heavy products.

You value a large ecosystem and community.

Cross-team readability is important.

You want a language that scales well across domains.

Python thrives in organizations where speed, clarity, and experimentation matter.

2. Python Is a Weaker Fit When:
Your system requires consistent low-level performance.

You’re building mobile-first.

You want strict compile-time guarantees.

Your team struggles with inconsistent coding styles.

In these environments, Python may add unnecessary friction.

3. Consider the Talent Strategy
Because senior Python engineers are in high demand, many U.S. companies supplement local hiring with nearshore engineering teams. Teams like those at Scio integrate directly with U.S. engineering organizations, providing skilled Python developers aligned with U.S. work culture and communication expectations.

4. Architectural Guardrails Are Non-Negotiable
To make Python sustainable at scale, leaders should enforce:
Type hints

Strong linting (Flake8, Pylint)

Code formatters (Black, isort)

Clear architectural patterns

Dependency boundaries

Active documentation practices

Without these, Python evolves into a fragmented ecosystem inside your own organization.

5. Python Still Belongs in Most Enterprise Stacks
Python may not be the best choice for every module, but it remains a strong pillar in full-stack architectures. It pairs effectively with React, Go, Rust, Node, modern cloud-native frameworks, and event-driven infrastructure.

Leaders benefit most when they treat Python as a strategic component — not a universal decision.

FAQ

Python for Modern Engineering Teams – FAQs

Practical guidance for leaders evaluating Python’s role in long-term engineering strategy.

Yes. Python’s ecosystem, readability, and dominance in data science and machine learning make it a foundational skill for modern engineering teams.

Not entirely. Python complements languages like Go and Node.js but does not eliminate the need for them in performance-critical or highly concurrent systems.

Because Python is interpreted rather than compiled. This design prioritizes flexibility and development speed, at the cost of raw runtime performance.

Yes. Even as new languages emerge, Python’s massive installed base, dominance in machine learning, and widespread academic use secure its long-term relevance.

Closing Note

Python isn’t perfect, but it continues to deliver value where it matters: clarity, ecosystem depth, and adaptability. For engineering leaders, the question is not whether Python will disappear — it won’t — but how intentionally it should be applied inside your architecture, team strategy, and long-term product vision.

The significant impact of Green Coding on the environment: Is balanced software development possible?

The significant impact of Green Coding on the environment: Is balanced software development possible?

Product Development, Technologies

Curated by: Sergio A. Martínez

With the need to be more environmentally focused every day, we look at an approach to software development that can help our industry utilize its resources better and more efficiently: Green Coding.

With the need to be more environmentally-focused every day, we take a look at an approach to software development that can help our industry to utilize its resources better and more efficiently: Green Coding.

When it comes to good practices in software development, there’s more to it than just efficiency and delivery of results during every sprint; there’s also a lot to consider about the impact caused by the products we make, both for our clients, final users, and the world at large. 

After all, we all know that software development can be a resource-intensive process. First, it generally requires a significant amount of development time to create robust and efficient applications. And second, developing software often requires the use of multiple tools and technologies, which can add to the cost of development. However, beyond these normal cases of resource investment from any software development company, what many people don’t realize is that coding can have a significant impact on the environment. After all, software development has always been a complex and time-consuming process, but in recent years this process has come into sharp focus, as the effects of global warming (and the time we have left to mitigate its effects) have become more and more pressing. 

In the case of technology, the creation of new software often requires the use of powerful machines, which consume large amounts of energy, and generate considerable amounts of heat and noise, in addition to the involvement of dozens or even hundreds of software development tools, each of which has a footprint. As a result, the environmental impact of software development can be significant.

Fortunately, there are several ways to reduce the environmental impact of software development, like using more efficient development tools that consume less energy or developing software in collaboration with other developers, which can help to reduce the overall number of development tools in use. However, all this could be for naught if our approach to software development doesn’t include a responsible mindset, which is the origin of a new way to approach the creation of new applications: Green Coding.

Green Coding: Efficiency in balance

The significant impact of Green Coding on the environment Is balanced software development possible

By taking these steps, developers can help to protect the environment while still creating high-quality software products, which is why more and more companies are adopting “Green Coding” practices. Green Coding is all about developing software in a way that minimizes its environmental impact, and that means anything from using energy-efficient hardware to writing code that is easier to recycle or reuse.

There are a lot of reasons why green coding is becoming a necessary practice in the software industry. For one, it’s simply the right thing to do: we have a responsibility to take care of our planet, and Green Coding is one way we can make a difference. But there are also practical reasons for adopting these practices; energy-efficient hardware, for example, can save developers money on their electric bills (an essential concern in remote setups), and code that is easier to reuse can save time and resources in the long run. So no matter what your motivation is, there are plenty of ways to go, so let’s review some techniques to ensure your code is as environment-friendly as possible.

  • Efficient writing: Before going into coding itself, let’s take a step back and think about the physical tool you use to write: your keyboard. How much energy does your keyboard spend during the day? Although the amount might seem negligible (around 1W per hour on average, maybe even less), most USB keyboards increase around 5 times the amount of energy they consume the older they get, depending on their build type and brand. And going along with the energy used by the whole computer setup, this energy adds up, which is why using wireless, rechargeable keyboards is getting popular in Green Coding circles, as it only needs a single 3-hour charge to work most of the day, and doesn’t consume energy directly while you use them. It may seem like a very small change, but considering how, on average, 600,000 people hit a space bar at the same time every 1/10 of a second, saving energy will have benefits in the long run.

  • Efficient coding: “Coding, for the most part, can become greener almost instantly if we adopt the same software development processes as our industry did 20+ years ago, when coding was confined to strict lengths and sizes”, is an interesting point mentioned by Dean Clark, Chief Technology Officer at GFT, regarding the idea of implementing Green Coding practices. The truth is that, while our ability to code today is virtually limitless, the lean way of writing code when you had to make the most with limited space also meant that no waste of resources was allowed, and optimization was a day-to-day practical concern. “Nowadays, with a lot more leeway in the way we write code”, says Adolfo Cruz,  Project Management Officer, and partner at Scio. “And these approaches to making software could still teach us a thing or two in regards to taking care of our resources, allowing us to create more environmentally-responsible applications whose efficiency could save us a lot of energy and time in the long run”. 

 

  • Efficient debugging: “Coding will inevitably result in bugs, and the act of debugging is, by itself, a way to improve the energy efficiency of software”, is the opinion of the blog TechXplore, which is why having a strong QA department with the appropriate tools is so important to achieve a true Green Coding approach. Following the last point, making sure that our applications are using resources responsibly, and wasting the least amount of energy possible at every step, could go a long way toward making software development more friendly to the ecosystem, and leading to more environmentally responsible practices overall. 

Collaboration as a key to Green Coding

The significant impact of Green Coding on the environment Is balanced software development possible_2

So to recap, Green Coding is the process of developing software in a way that minimizes its impact on the environment. We already mentioned some ways to achieve it, but a key practice in environmentally-friendly coding includes collaboration, Nearshore development, and expertise sharing. Collaboration is essential to Green Coding because working closely with others helps to ensure that everyone is on the same page and that no one is duplicating effort, allowing for more efficient use of resources, which can help to reduce a company’s carbon footprint. 

In the specific case of Nearshore development, working with developers in countries closer to their clients and end-users helps reduce travel emissions, allowing you to take advantage of different time zones so work can be done around the clock, which combined with good Green Coding practices, can make a difference when it comes to leaving a carbon footprint. 

“You might not think that Nearshoring your software development would have anything to do with the environment, but the truth is it can be very beneficial, helping to improve efficiency and cut down on waste”, is the summary Adolfo Cruz offers about the advantages of collaborating within your same time zone, as expertise sharing is crucial to Green Coding, helping to raise the overall level of expertise in the industry to not only improve the quality of software but also help it reduce the need for training and support. 

Development involving a team of experts can often get the job done faster, with fewer errors, and less need for constant testing and development, saving a lot of time and resources. As a result, expertise sharing is an essential part of green coding. All in all, there are many good reasons to consider outsourcing your software development – even if you’re worried about the environment.

In the software development industry, going green is not just about being eco-friendly; it’s also about being efficient, effective, and collaborative. When development teams adopt Green Coding practices, they can work faster, and more efficiently, and as a result, have a positive impact on the software development process. In addition, by adopting green coding practices, development teams can help to make the software development industry more sustainable, and in turn, help the march towards a better future.

The Key Takeaways

  • The technology industry as a whole is very resource-intensive, and thus, a good starting point for more environmentally friendly practices.
  • However, beyond adopting hardware that spends less energy overall, there are practices in the software side of things that could help to be more responsible with resources.
  • Green Coding is an approach to software development where code is as efficient, light, and bug-free as possible, helping to run applications that overall leave a smaller footprint in the environment.
  • Nearshore development is a good approach to green coding, reducing the need for long travels (and thus, the emissions they involve), as well as sharing the necessary knowledge to always improve software, achieving a better balance with our environment.

Scio is an established Nearshore software development company based in Mexico that specializes in providing high-quality, cost-effective technologies to help you reach new heights. We have been developing 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’ll be happy to help you achieve your business goals.

Five years of technology: What has changed in the world of software since 2017?

Five years of technology: What has changed in the world of software since 2017?

Technologies

Curated by: Sergio A. Martínez

Every year, the data insight company Gartner, as part of their mission to help our industry to pay attention to the latest trends and development in software and development, publishes a list of the most promising technologies of that year, the ones that seem to be able to change the direction of the future.

It’s (not) about time: Why is managing your energy the best software development approach?

Knowing this, and with the benefit of insight, we took a look into some of the predictions made way back in 2017, asking some of Scio’s leader, Luis Aburto, Rod Aburto y Adolfo Cruz, their thoughts about these technologies during the past five years, what they got right, and if some new developments could still await for us in the future. Enjoy!

Prediction 1: AI & Advanced Machine Learning

“It has definitely become popular”, Luis Aburto, CEO, and Co-founder of Scio, comments. “Applications like Jasper.io have advanced to a point where they are not toys anymore, but tools that a professional organization can rely on.” On the other hand, Adolfo Cruz, PMO Director, holds the opinion that this technology is still in its infancy. “There’s still a long road ahead. These programs are still unable to emulate the soul of many creative tasks. Maybe one day, but not very soon.” 

And in the case of software like the Applicant Tracking Systems we have talked about before, Luis still believes that AIs and Advanced Machine Learning are still not a “one-size-fits-all” solution. “These programs could work well in bigger companies that have an enormous amount of information to sift through, so an AI program could perform better in that case. But for medium companies like Scio or even smaller companies, human intervention keeps being preferable.” 

Prediction 2: Intelligent Apps

“Although they aren’t ubiquitous yet, applications like chatbots and virtual assistants have proven to be a valuable tool in many businesses”, comments Luis Aburto. “We are currently building a chat application along with one of our clients, and it’s an interesting challenge that will get more complex, but also more useful day by day. Someday, you’re probably not going to be talking to humans in any client service.”

Prediction 3: Digital Twinning

“Building a virtual mirror of a physical object is going to get big in manufacture and development of systems”, says Rod Aburto. “I know of business areas like airspace that can develop planes using the tons of data generated in each flight, gigabytes of information transmitted directly from the plane that could revolutionize the industry. In that sense, digital twinning might be a useful tool from now on, but I only see it in specific industries. Not much in the mainstream.” 

Prediction 4: Virtual and Augmented Reality

“I believe AR is still marching slowly. Maybe now with the Metaverse, they can jump forward, although I see more future in full virtual reality than AR”, says Luis. 

“And it’s still more of a plaything than anything else, without much in the way of practical applications”, adds Rod Aburto, referring to the current state of most popular AR uses. “At some point, it was said that doctors could do surgery at a distance with the help of this technology, but I see that as a very unlikely outcome.  

“Even Microsoft, with the big push of the Hololens, couldn’t really crack it”, continued Luis. “They sold some to the military and the like, but for the average person, it seemed more of a novelty than a truly groundbreaking tool. And the idea of everyone walking around with Google glasses, seeing augmented reality applications everywhere, is not really the future I expect.” 

Prediction 5: Blockchain

“Okay, that one is everywhere”, said Rod Aburto. “But not necessarily with their original purpose of being a public ledger audited by everyone. Their main application is still in cryptocurrency, and more as a financial gamble than anything else.”

“Although the future seems to lead to the so-called Web3, where the more transactional aspects of the blockchain become clearer”, intervenes Luis at the end. “Like the whole “digital ownership” concept of NFTs, I think that this technology still has many issues to solve, like how costly it is to make transactions and not to mention how slow it is for any practical purpose. But those things can only improve.” 

So what do you think? With all these technologies constantly growing and evolving, where will we be standing in five years’ time? Will some of these still be around as we know them, will they find new and exciting applications or something new will throw our predictions in an unexpected direction? Because one thing is sure: however the future shapes up, here at Scio we will be ready to help you explore new technological territories with the best talent in all of LATAM. Give us a call and let’s get started!

Scio is an established Nearshore software development company based in Mexico that specializes in providing high-quality, cost-effective technologies to help you reach new heights. We have been developing 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’ll be happy to help you achieve your business goals.