We Don’t Build Skyscrapers on Sand: How to Ship Fast Without Breaking Your Product Later

Nearshore Software Development, Product Development

Written by: Monserrat Raya 

Cybersecurity concept with a glowing lock and directional arrows representing secure data flow in software development.

Engineering leaders are feeling an unusual mix of pressure and optimism right now. Markets move quickly, boards want velocity, and AI promises ten times the output with the same headcount. Yet the day-to-day reality inside most engineering organizations tells a different story. Delivery is fast until it suddenly isn’t. Fragile systems slow down releases. Outages wipe out months of goodwill. Teams rush to ship features, but each shortcut quietly becomes part of the permanent structure.

One comment in a recent r/ExperiencedDevs discussion captured this tension perfectly. A former engineering manager described how their team used a simple philosophy to guide decisions about speed. They labeled every shortcut as product enablement and consistently reminded themselves, “We won’t build skyscrapers on sand.”
This quote belongs to that Reddit conversation, and the mindset behind it reflects something many teams already feel but rarely articulate. It’s not speed that breaks products. It’s building tall structures on unstable ground.

That’s the heart of this article. Leaders can ship fast, respond to the market, and keep teams energized, but only if they stay clear about one thing: where they’re building on rock and where they’re temporarily on sand. Without that clarity, shortcuts become liabilities, prototypes become production, and systems age faster than anyone expected. This piece offers a framework for CTOs and VPs of Engineering who want both speed and long-term stability, especially as teams grow, architectures evolve, and nearshore partners enter the picture.

The Real Problem Isn’t Speed, It’s What You’re Building On

Engineering teams rarely struggle because they move too quickly. More often, they struggle because the foundation of the system wasn’t prepared for the weight that came later. New features rest on shortcuts taken months or years before. Deadlines stack. Monitoring lags. A quick workaround becomes a permanent dependency. Suddenly, people begin saying things like “don’t touch that service” or “we avoid that part of the codebase unless absolutely necessary.” Leaders know the pattern all too well. Teams push forward with urgency. The roadmap is full. Product expectations rise. AI-generated pull requests accelerate everything. But the real issue is not speed, it’s the assumption that everything built today will carry weight tomorrow. That assumption isn’t always true. This is why the Reddit anecdote resonates. A simple rule, “we won’t build skyscrapers on sand,” separates intentional shortcuts from dangerous instability. You can build fast, you can build high, but not if the bottom layers weren’t designed with the future in mind. CTOs often face a subtle dilemma here:
  • If you slow down, competitors gain ground.
  • If you go too fast without a plan for reinforcement, your future velocity drops.
  • If you rely heavily on prototypes that become production, the system becomes fragile before anyone notices.
This article aims to give leaders a vocabulary and a structure to navigate that tension. Once a team understands that not all speed is equal, everything, from sprint planning to architectural reviews, becomes clearer and more predictable.
  • Pressure pushes teams toward shortcuts.
  • Shortcuts without ownership become long-term liabilities.
  • Prototypes becoming production code is one of the fastest ways to create instability.
  • Leaders are responsible for distinguishing temporary scaffolding from permanent structure.
The promise of the framework ahead is simple. You can move fast, as long as you know when the ground beneath you needs reinforcement.

Three Types of “Speed” (And Only One Works at Scale)

Speed is not a single state. Teams move quickly for different reasons, and each reason carries different risks. The largest failures come when leaders treat all forms of speed the same. Below is a practical model used by experienced engineering organizations to clarify intent before writing a single line of code.

1. Exploratory Speed — Safe by Design

This is the world of prototypes, spikes, and small experiments. The entire point is to learn something quickly, not to build something durable. Teams can run wild here because the blast radius is intentionally small. Healthy exploratory work uses labels and boundaries such as:
  • Dedicated repositories or folders
  • Environment segregation
  • A clear understanding that prototypes are disposable
  • Feature flags that ensure experiments never leak into production
  • No dependencies on permanent systems
This form of speed is not only safe. It’s essential for innovation.

2. Enablement Speed — Sand With a Plan

This is where most real-world engineering happens. You ship something early because you want users to validate direction. You tolerate imperfections because learning matters more in the beginning. But for this to work, you must plan a “foundation pass” before the feature scales. This idea ties directly to Scio’s internal perspective on technical debt and expectations, explored deeply in the article Technical Debt vs. Misaligned Expectations: Which Costs More? In enablement speed, teams must define:
  • What must be refactored
  • What tests must be added
  • What architecture boundaries need reinforcement
  • What version of the feature becomes “real”
  • When that foundation work will take place
Enablement speed is the fastest way to deliver value without creating future chaos, as long as the team honors the commitment to revisit the foundation before growth increases the load.

3. Reckless Speed — The Skyscraper on Sand

Every CTO knows this mode, often too well. This is where outages, regressions, and brittle systems come from. You are operating in reckless speed when:
  • Prototypes quietly turn into production
  • Monitoring is missing or unreliable
  • Core components lack owners
  • Tests are skipped entirely
  • Shortcuts stack without review
  • Teams accept instability as “normal”
Reckless speed feels productive in the moment, but it erodes predictability and slows the organization over time. The tragedy is that most teams in reckless speed didn’t choose it intentionally. They drifted into it because nobody named the mode they were operating in.

How Skyscrapers on Sand Actually Show Up in Your Company

CTOs often feel issues long before they can point to a clear cause. They notice delivery slowing down. They see senior engineers burned out. They observe mounting operational drag. Skyscrapers built on sand reveal themselves through subtle, recurring patterns. Common symptoms include:
  • Test suites that are flaky and ignored
  • Deploy freezes before major releases because trust in the system is low
  • A few senior developers acting as bottlenecks for all critical knowledge
  • A rising frequency of production incidents
  • Teams afraid to modify certain services or modules
  • Onboarding timelines stretching from weeks to months
These symptoms all trace back to the same root cause. The foundation wasn’t ready for the height of the structure. The cost of this is not abstract. It affects:
  • Roadmap predictability
  • Developer morale
  • Customer trust
  • Recruitment and retention
  • Engineering velocity
Organizations that ignore foundational work end up paying compound interest on every shortcut. The longer the debt persists, the more expensive it becomes to fix.
  • Fragile systems increase operational overhead
  • Burnout rises when teams operate in a constant state of urgency
  • New developers struggle to navigate unclear boundaries
  • Leadership loses confidence in estimates and delivery
This is why the framework ahead matters. It gives leaders a repeatable pattern to decide when to reinforce, when to slow down, and when to push forward confidently.

A Practical Framework: When to Pour Concrete, Not Sand

To balance speed and stability, teams need rules for deciding when a feature is allowed to be scrappy and when it requires durable engineering. The following model gives leaders a repeatable decision structure.

Ask These Three Questions for Every Initiative

  • Are we exploring, enabling, or scaling?
  • If this feature succeeds, will it become core to the product?
  • What must be true for this to survive the next three to five years?
If you can’t answer these questions clearly, you’re already on sand.

Define a Foundation Pass

After a feature launches and gains traction, schedule a moment where the team stabilizes the core. This work typically includes:
  • Strengthening APIs
  • Increasing test coverage where risk is highest
  • Improving observability and monitoring
  • Removing temporary hacks
  • Reinforcing architectural boundaries
  • Improving deployment predictability
When discussing stability metrics, reliability work, and long-term architectural resilience, referencing the DORA Research Program provides credibility. DORA’s metrics — deployment frequency, MTTR, change failure rate, and lead time — serve as guideposts for deciding where foundational reinforcement is most urgent.

Use Time-Boxed Stability Cycles

Many high-performing engineering orgs run periodic stability sprints or reliability weeks. They focus on removing papercuts and reducing operational drag. These cycles maintain momentum without derailing the roadmap.

Guardrails for Leaders

Non-negotiables:
  • Observability
  • Rollback mechanisms
  • Baseline test suite
  • Architectural boundaries
Flexible areas:
  • Aesthetic refactors
  • Internal naming
  • Pure style cleanups
Teams need to know what is sacred and what can move. Without these guardrails, inconsistency creeps in.

Where Nearshore Teams Fit: Speed With Memory and Discipline

Modern engineering teams often run at or beyond capacity. Roadmaps expand. Customer expectations grow. AI accelerates code generation, but not code comprehension. Meanwhile, stability work rarely gets the attention it deserves. This is where a nearshore partner becomes transformative. A high-performing nearshore engineering team, especially one aligned by culture and time zone, supports both speed and long-term stability by:
  • Owning papercut backlogs and reliability cycles
  • Bringing senior engineers who keep institutional memory intact
  • Working in sync with in-house teams across aligned working hours
  • Offering continuity in architecture, testing, and long-term maintenance
  • Reinforcing engineering discipline during moments when internal teams are overwhelmed
The value is not simply “more hands.” It’s sustained attention on long-term stability while still supporting fast delivery. Scio’s experience working with mid-market engineering leaders shows that the healthiest partnerships maintain momentum without sacrificing foundation work. Over months and years, this increases predictability, reduces outages, and lowers the cost of change.

Actionable Checklist for CTOs: Are You Building on Rock or Sand?

Use this list during roadmap planning, quarterly reviews, or architectural conversations.
Rock Indicators
  • Prototypes are clearly labeled and isolated
  • Monitoring and observability are in place
  • The team trusts deployments
  • Ownership of critical systems is documented
  • The blast radius of changes is controlled
Sand Indicators
  • “Temporary” code has lived longer than expected
  • Critical systems depend on one or two individuals
  • Tests are regularly skipped
  • Releases require freeze periods
  • Production issues are rising quarter over quarter
Leadership Actions
  • Assign a foundation pass to each major initiative
  • Schedule quarterly stability cycles
  • Ensure nearshore teams work on long-lived components
  • Review architecture boundaries annually
A simple rule closes this section. Speed becomes sustainable only when teams know exactly which parts of the system can support growth.
Mode
Purpose
Risk Level
When It Works
When It Fails
Exploratory Speed Learn fast through disposable experiments Low Short-lived prototypes, isolated environments When prototypes become production
Enablement Speed Ship early to validate direction Moderate When a foundation pass is scheduled and honored If stabilization is skipped
Reckless Speed Ship without regard for future load High Only for true one-off throwaway tasks Always, if used for product features

Build Fast, but Make Sure What You Build Can Last

Ship fast. Move confidently. And keep in mind what that engineering manager on Reddit expressed so simply. We don’t build skyscrapers on sand. Not when customers depend on reliability, not when your roadmap drives the pace of innovation, and not when your team wants to deliver work that still holds up a year from now. The leaders who consistently deliver aren’t the ones who slow the team down, but the ones who understand when acceleration is safe and when the foundation deserves attention.

Moving fast doesn’t mean cutting corners. It means choosing intentionally where speed creates value and where stability protects future momentum. Teams that operate with that clarity build systems that grow with them instead of holding them back.

If your roadmap is pushing forward but the underlying structure feels stretched, that’s usually the moment to bring in a partner who can help reinforce the base without interrupting progress. Scio supports engineering organizations that want to ship quickly while strengthening long-term reliability. Our nearshore developers are easy to work with, aligned with your culture, and committed to supporting both velocity and durability. Because the products that last aren’t just built quickly, they’re built on something solid.

Ready to strengthen your foundation and move faster with confidence? Contact us and let’s talk about how Scio can support your engineering goals.

Speed vs Stability in Software Development: Key Questions

  • Yes, if leaders distinguish between exploratory, enablement, and reckless speed. Debt becomes dangerous only when temporary shortcuts evolve into permanent structures without a stabilization cycle.

  • It works during early validation, as long as the team documents a path to reinforcement. The risk grows when the same shortcuts remain after the feature becomes strategic for the business.

  • Tie stability work to delivery metrics, customer impact, and risk reduction. Product teams respond well when they see how foundation work increases future velocity and prevents roadmap disruptions.

  • Experienced partners onboard quickly and maintain long-term continuity. They reduce the load on internal teams by owning reliability cycles, documenting complex areas, and reinforcing foundation layers.

Suggested Reading

From Idea to Vulnerability: The Risks of Vibe Coding

From Idea to Vulnerability: The Risks of Vibe Coding

AI, Product Development, Software Development, vibe coding

Written by: Monserrat Raya 

Engineering dashboard displaying system metrics, security alerts, and performance signals in a production environment

Vibe Coding Is Booming, and Attackers Have Noticed

There has never been more excitement around building software quickly. Anyone with an idea, a browser, and an AI model can now spin up an app in a matter of hours. This wave of accessible development has clear benefits. It invites new creators, accelerates exploration, and encourages experimentation without heavy upfront investment.

At the same time, something more complicated is happening beneath the surface. As the barrier to entry gets lower, the volume of applications deployed without fundamental security practices skyrockets. Engineering leaders are seeing this daily. New tools make it incredibly simple to launch, but they also make it incredibly easy to overlook the things that keep an application alive once it is exposed to real traffic.

This shift has not gone unnoticed by attackers. Bots that scan the internet looking for predictable patterns in code are finding an increasing number of targets. In community forums, people share stories about how their simple AI-generated app was hit with DDoS traffic within minutes or how a small prototype suffered SQL injection attempts shortly after going live. No fame, no visibility, no marketing campaign. Just automated systems sweeping the web for weak points.

The common thread in these incidents is not sophisticated hacking. It is the predictable absence of guardrails. Most vibe-built projects launch with unprotected endpoints, permissive defaults, outdated dependencies, and no validation. These gaps are not subtle. They are easy targets for automated exploitation.

Because this trend is becoming widespread, engineering leaders need a clear understanding of why vibe coding introduces so much risk and how to set boundaries that preserve creativity without opening unnecessary attack surfaces.

To provide foundational context, consider a trusted external reference that outlines the most common security weaknesses exploited today.
Before diving deeper, it’s useful to review the OWASP Top 10, a global standard for understanding modern security risks:

Developer using AI-assisted coding tools while security alerts appear on screen
AI accelerates development speed, but security awareness still depends on human judgment.

Why Vibe Coders Are Getting Hacked

When reviewing these incidents, the question leadership teams often ask is simple. Why are so many fast-built or AI-generated apps getting compromised almost immediately? The answer is not that people are careless. It is that the environment encourages speed without structure.

Many new builders create with enthusiasm, but with limited awareness of fundamental security principles. Add generative AI into the process and the situation becomes even more interesting. Builders start to trust the output, assuming that code produced by a model must be correct or safe by default. What they often miss is that these models prioritize functionality, not protection.
Several behaviors feed into this vulnerability trend.

  • Limited understanding of security basics A developer can assemble a functional system without grasping why input sanitization matters or why access control must be explicit.
  • Overconfidence in AI-generated output If it runs smoothly, people assume it is safe. The smooth experience hides the fact that the code may contain unguarded entry points.
  • Copy-paste dependency Developers often combine snippets from different sources without truly understanding the internals, producing systems held together by assumptions.
  • Permissive defaults Popular frameworks are powerful, but their default configurations are rarely production-ready. Security must be configured, not assumed.
  • No limits or protections Endpoints without rate limiting or structured access control may survive small internal tests, but collapse instantly under automated attacks.
  • Lack of reviews Side projects, experimental tools, and MVPs rarely go through peer review. One set of eyes means one set of blind spots.

To contextualize this trend inside a professional engineering environment, consider how it intersects with technical debt and design tradeoffs.
For deeper reading, here is an internal Scio resource that expands on how rushed development often creates misaligned expectations and hidden vulnerabilities:
sciodev.com/blog/technical-debt-vs-misaligned-expectations/

Common Vulnerabilities in AI-Generated or Fast-Built Code

Once an app is released without a security baseline, predictable failures appear quickly. These issues are not obscure. They are the same classic vulnerabilities seen for decades, now resurfacing through apps assembled without sufficient guardrails. Below are the patterns engineering leaders see most often when reviewing vibe-built projects.
SQL Injection
Inputs passed directly to queries without sanitization or parameterization.
APIs without real authentication
Hardcoded keys, temporary tokens left in the frontend, or missing access layers altogether.
Overly permissive CORS
Allowing requests from any origin makes the system vulnerable to malicious use by third parties.
Exposed admin routes
Administrative panels accessible without restrictions, sometimes even visible through predictable URLs.
Outdated dependencies
Packages containing known vulnerabilities because they were never scanned or updated.
Unvalidated file uploads
Accepting any file type creates opportunities for remote execution or malware injection.
Poor HTTPS configuration
Certificates that are expired, misconfigured, or completely absent.
Missing rate limiting
Endpoints that become trivial to brute-force or overwhelm.
Sensitive data in logs
Plain-text tokens, user credentials, or full payloads captured for debugging and forgotten later. These vulnerabilities often stem from the same root cause. The project was created to «work», not to «survive». When builders rely on AI output, template code, and optimistic testing, they produce systems that appear stable until the moment real traffic hits them.
Software engineer reviewing system security and access controls on a digital interface
Fast delivery without structure often shifts risk downstream.

Speed Without Guardrails Becomes a Liability

Fast development is appealing. Leaders feel pressure from all sides to deliver quickly. Teams want to ship prototypes before competitors. Stakeholders want early demos. Founders want to validate ideas before investing more. And in this climate, vibe coding feels like a natural approach. The challenge is that speed without structure creates a false sense of productivity. When code is generated quickly, deployed quickly, and tested lightly, it looks efficient. Yet engineering leaders know that anything pushed to production without controls will create more work later. Here are three dynamics that explain why unstructured speed becomes a liability.
  • Productivity that only looks productive Fast development becomes slow recovery when vulnerabilities emerge.
  • A false sense of control A simple app can feel manageable, but a public endpoint turns it into a moving target.
  • Skipping security is not real speed Avoiding basic protections might save hours today, but it often costs weeks in restoration, patching, and re-architecture.
Guardrails do not exist to slow development. They exist to prevent the spiral of unpredictable failures that follow rushed releases.

What Makes Vibe Coding Especially Vulnerable

To understand why this trend is so susceptible to attacks, it helps to look at how these projects are formed. Vibe coding emphasizes spontaneity. There is little planning, minimal architecture, and a heavy reliance on generated suggestions. This can be great for creativity, but dangerous when connected to live environments. Several recurring patterns increase the risk surface.
  • No code reviews
  • No unit or integration testing
  • No threat modeling
  • Minimal understanding of frameworks’ internal behavior
  • No dependency audit
  • No logging strategy
  • No access control definition
  • No structured deployment pipeline
These omissions explain the fundamental weakness behind many vibe-built apps. You can build something functional without much context, but you cannot defend it without understanding how the underlying system works. A functional app is not necessarily a resilient app.
Engineering team collaborating around security practices and system design
Even experimental projects benefit from basic security discipline.

Security Basics Every Builder Should Use, Even in a Vibe Project

Engineering leaders do not need to ban fast prototyping. They simply need minimum safety practices that apply even to experimental work. These principles do not hinder creativity. They create boundaries that reduce risk while leaving room for exploration.
Minimum viable security checklist
  • Validate all inputs
  • Use proper authentication, JWT or managed API keys
  • Never hardcode secrets
  • Use environment variables for all sensitive data
  • Implement rate limiting
  • Enforce HTTPS across all services
  • Remove sensitive information from logs
  • Add basic unit tests and smoke tests
  • Run dependency scans (Snyk, OWASP Dependency Check)
  • Configure CORS explicitly
  • Define role-based access control even at a basic level
These steps are lightweight, practical, and universal. Even small tools or prototypes benefit from them.

How Engineering Leaders Can Protect Their Teams From This Trend

Engineering leaders face a balance. They want teams to innovate, experiment, and move fast, yet they cannot allow risky shortcuts to reach production. The goal is not to eliminate vibe coding. The goal is to embed structure around it.
Practical actions for modern engineering organizations:
  • Introduce lightweight review processes Even quick prototypes should get at least one review before exposure.
  • Teach simple threat modeling It can be informal, but it should happen before connecting the app to real data.
  • Provide secure starter templates Prebuilt modules for auth, rate limiting, logging, and configuration.
  • Run periodic micro-audits Not full security reviews, just intentional checkpoints.
  • Review AI-generated code Ask why each permission exists and what could go wrong.
  • Lean on experienced partners Internal senior engineers or trusted nearshore teams can help elevate standards and catch issues early. Strong engineering partners, whether distributed, hybrid, or nearshore, help ensure that speed never replaces responsible design.
The point is to support momentum without creating unnecessary blind spots. Teams do not need heavy process. They need boundaries that prevent predictable mistakes.
Developers reviewing system integrity and security posture together
Speed becomes sustainable only when teams understand the risks they accept.

Closing: You Can Move Fast, Just Not Blind

You don’t need enterprise-level security to stay safe. You just need fundamentals, awareness, and the discipline to treat even the smallest prototype with a bit of respect. Vibe coding is fun, until it’s public. After that, it’s engineering. And once it becomes engineering, every shortcut turns into something real. Every missing validation becomes an entry point. Every overlooked detail becomes a path someone else can exploit. Speed still matters, but judgment matters more. The teams that thrive today aren’t the ones who move the fastest. They’re the ones who know when speed is an advantage, when it’s a risk, and how to balance both without losing momentum. Move fast, yes. But move with your eyes open. Because the moment your code hits the outside world, it stops being a vibe and becomes part of your system’s integrity.

Fast Builds vs Secure Builds Comparison

Aspect
Vibe Coding
Secure Engineering
Security Minimal protections based on defaults, common blind spots Intentional safeguards, reviewed authentication and validated configurations
Speed Over Time Very fast at the beginning but slows down later due to fixes and rework Balanced delivery speed with predictable timelines and fewer regressions
Risk Level High exposure, wide attack surface, easily exploited by automated scans Low exposure, controlled surfaces, fewer predictable entry points
Maintainability Patchwork solutions that break under load or scale Structured, maintainable foundation built for long-term evolution
Dependency Health Outdated libraries or unscanned packages Regular dependency scanning, updates and monitored vulnerabilities
Operational Overhead Frequent hotfixes, instability and reactive work Stable roadmap, fewer interruptions and proactive improvement cycles

Vibe Coding Security: Key FAQs

  • Because attackers know these apps often expose unnecessary endpoints, lack proper authentication, and rely on insecure defaults left by rapid prototyping. Automated bots detect these weaknesses quickly to initiate attacks.

  • Not by design, but it absolutely needs validation. AI produces functional output, not secure output. Without rigorous human review and security testing, potential vulnerabilities and compliance risks often go unnoticed.

  • The most frequent issues include SQL injection (See ), exposed admin routes, outdated dependencies, insecure CORS settings, and missing rate limits. These are often easy to fix but overlooked during rapid development.

  • By setting minimum security standards, offering secure templates for rapid building, validating AI-generated code, and providing dedicated support from experienced engineers or specialized nearshore partners to manage the risk pipeline.

What does modern career growth look like in software development?

What does modern career growth look like in software development?

Nearshore Software Development, Product Development

Written by: Scio Team 
Digital growth chart emerging from a mobile device, representing modern and multidimensional software career growth
Career growth in software development no longer resembles a single ladder with predictable steps. For many engineers, the question is no longer “What’s the next title?” but “What shape do I want my career to take?” The industry has shifted toward adaptability, breadth of skill, and multidimensional development. For engineering leaders, this shift is a reminder that talent grows best in environments built for experimentation, learning, and genuine human connection. The software sector moves quickly, and so do the expectations around modern careers. Today’s junior engineer can become a product strategist, a mid-career QA analyst can transition into security, and a senior developer can jump into coaching, architecture, or a completely new technical domain without leaving the field. Rather than a single direction, careers now expand outward, creating more space for curiosity and autonomy. This evolution raises an important question for every developer: where do you want your work to take you? And equally important for every CTO: how can your organization make that growth possible?
Software engineer reflecting at a desk, representing career stagnation caused by traditional promotion paths
When growth is limited to promotion alone, talented engineers are often pushed into roles that don’t fit their strengths.

Understanding the Peter Principle in the Context of Engineering

The conversation about modern career paths begins with an honest look at why traditional structures often fail. The Peter Principle, introduced by educator Laurence J. Peter, describes a simple but persistent pattern: when people are promoted solely based on success in their current role, they eventually reach a position where they are no longer competent. In many companies, especially before the shift toward flexible career paths, this pattern shaped careers in unhealthy ways. A top-performing individual contributor was often promoted into management because upward movement was the only visible path. Salespeople became sales managers. Strong QA engineers became QA leads. Talented developers became engineering managers, even when leadership, coaching, or strategic planning were not part of their core strengths. Organizations inadvertently set people up for roles they never truly wanted. Software development has long suffered from this dynamic. High-performing engineers often get pushed toward management, even when they prefer to remain hands-on. Engineering leaders have experienced the consequences: team leads who don’t enjoy leading; managers who miss coding; senior roles held by people who would thrive if allowed to explore different branches of the craft. The Peter Principle persists when organizations limit growth to a ladder instead of a lattice. The issue is not the individual but the structure around them. When promotion becomes the only recognized form of advancement, companies lose the opportunity to nurture talent in more nuanced ways. Worse, they risk placing people in roles where their strengths are underutilized. Modern companies are starting to recognize this. As Skip Richard explains in his analysis of new career dynamics, organizations now value breadth of expertise, cross-functional learning, and generalist mindsets just as much as deep specialization. This shift reduces the likelihood of placing individuals in roles that don’t fit them and instead encourages a more fluid approach to professional growth. For software teams, this means creating environments where developers can explore, rotate, cross-train, or advance without feeling forced into a single storyline. It also means recognizing that competence is not static. With the right support, people can learn new skills, shift directions, and grow into roles that once seemed out of reach.
Digital interface showing interconnected skills and roles in a modern software career
Modern software careers grow sideways, diagonally, and across disciplines — not just upward.

The New Shape of Software Careers

The modern workplace is rapidly moving away from the idea of linear growth. Software development, in particular, rewards people who explore diverse skills. The industry now encourages flexibility because the needs of engineering teams evolve as quickly as the technologies they use. A developer today might contribute to QA, DevOps, product discovery, or data engineering tomorrow. This fluidity improves adaptability and widens the impact of individual contributors. Cross-functional curiosity is now a competitive advantage. A full-stack developer who understands testing improves code quality. A tester who understands APIs reduces friction in a sprint. An IT analyst who learns programming can accelerate automation. A marketer who learns to code can contribute to technical storytelling, analytics, or product growth initiatives. Stories like those within Scio reflect this change. Ivan Guerrero, originally a Pharmaceutical Chemist, discovered software development and transitioned into Scio’s Application Developer Apprenticeship. His journey is one example of a growing trend: people entering tech from nontraditional backgrounds, enriching teams through diverse thinking. Víctor Ariel Rodríguez Cruz, now a full-stack Application Developer, shares a similar story. Coming from a nontraditional path, he found space to grow in areas such as web development, cybersecurity, and game development. These interests reflect a broader truth: modern developers want careers that adapt to their evolving passions, not the other way around. This flexibility benefits teams as well. Cross-trained developers bring broader perspectives to projects, spot risks earlier, and collaborate more effectively across disciplines. The result is not only better engineering outcomes but more resilient teams. Career development has become “squiggly,” as Skip Richard describes. Developers move up, sideways, across, and sometimes down to refine their craft. They may leave and return, explore new specialties, or hybridize their skills. For CTOs, the challenge is designing structures that support this evolution—formal learning paths, mentorship programs, apprenticeship opportunities, and environments where experimentation is encouraged. Modern careers are no longer predefined. They are shaped by interests, exposure, and the quality of opportunities available inside the organization.
Diverse software team collaborating in a meeting, representing mentorship and human connection in career growth
Careers grow faster and more sustainably in environments built on trust, mentorship, and collaboration.

The Role of Human Connection in Career Growth

No career flourishes in isolation. Modern software development depends on collaboration, mentorship, and the relationships that form inside engineering teams. Human connection fuels learning, confidence, and the resilience individuals need to navigate complex work. At Scio, this principle is foundational. Human connection shapes how teams collaborate, how apprentices learn, and how engineers grow into new responsibilities. It also drives the formal structure behind Scio’s learning ecosystem, including technical coaching, certifications, English programs, leadership development, and mentorship frameworks like the Leadership, Apprenticeship, and Sensei-Creati Coaching & Mentoring Programs. These programs serve a strategic purpose: they give developers multiple avenues to explore their interests while receiving support from experienced peers. Whether someone needs deep technical guidance, leadership preparation, or informal advice during a coffee chat, connection becomes the enabling force for every stage of growth. Soft skills also play a critical role. Engineers transitioning into leadership benefit from coaching in communication, conflict resolution, feedback delivery, and decision-making. These skills rarely develop organically. Without proper support, promotions can replicate the issues outlined in the Peter Principle. With coaching, they create leaders who drive alignment, stability, and healthy team culture. This dimension of connection is especially important in distributed environments. Remote and hybrid teams depend on trust, clarity, and psychological safety. Engineers grow when they feel supported. They ask better questions, explore new technologies with confidence, and communicate more openly about challenges. Career development, therefore, becomes multidimensional. It includes technical skill, interpersonal growth, adaptability, and the confidence gained through belonging. Scio’s focus on connection ensures that developers can choose the path that fits them without feeling restricted by traditional hierarchies.

A Comparative Look: Traditional vs. Modern Career Paths

Career Model Traditional Path Modern Software Path
Structure Linear advancement Lattice of multiple directions
Promotion Logic Based on current performance Based on interests, skill growth, and contribution patterns
Risk Peter Principle, role mismatch Fluid roles reduce mismatch risk
Flexibility Low High mobility across functions
Learning Limited to role Continuous skill development
Hand holding digital skill icons, representing the multiple dimensions of a modern software career
Sustainable career growth comes from combining technical, interpersonal, and strategic skills.

The Many Dimensions of a Modern Software Career

Modern careers demand more than a vertical trajectory. They rely on layered development across technical, interpersonal, and strategic skills. This multidimensional approach ensures developers can shift paths without losing momentum and grow into roles that match both their talent and their interests. At Scio, these dimensions take shape through structured programs, informal learning, cross-team collaboration, and a culture that values curiosity. Developers can expand their expertise through paid courses, certifications, or guided practice with senior mentors. They can also explore new specialties by participating in different projects or working across functions. One of the most valuable aspects of this multidimensional model is its impact on autonomy. Instead of feeling boxed into a single path, developers can make informed choices about their future. Some may pursue leadership, others may deepen technical mastery, and some may branch into adjacent areas like security, DevOps, product, or research. This flexibility also supports sustainable growth. Engineers who feel empowered to explore different paths are less likely to stagnate or experience burnout. They engage with their work more fully because they see meaningful possibilities ahead. As Ivan Guerrero notes, opening doors for people without traditional backgrounds not only strengthens organizations but also attracts passionate learners who bring fresh perspectives. That diversity of experience becomes an asset in complex engineering environments. Ultimately, modern career growth is about intentional development. It requires leaders to create clear paths, offer real support, and nurture environments where people feel safe exploring new territory.

Key Takeaways

  • Traditional career paths often led to the Peter Principle due to limited advancement options.
  • Modern career growth embraces multiple directions, not just upward movement.
  • Companies that support cross-functional exploration build stronger, more adaptive teams.
  • Human connection and collaborative culture are essential for multidimensional growth.

FAQ: Navigating Modern Software Engineering Career Paths

  • Because modern engineering work benefits from cross-functional understanding, adaptability, and diverse technical backgrounds. Flexibility allows teams to leverage unique skill sets that don't always fit into linear silos.

  • By offering multiple growth paths, mentorship, and continuous development programs. The goal is to avoid promoting individuals into roles they aren't suited for simply because promotion is seen as the only form of advancement.

  • No. Modern organizations support hybrid, lateral, and exploratory paths. This allows developers to grow their influence and expertise without being forced into leadership roles that may lead to role mismatches.

  • Culture is the foundation; it determines whether people feel safe exploring new skills, asking for guidance, and taking on the specific responsibilities that ultimately shape their unique professional careers.

“How much value, not how much code”: A reflection on productivity in software development with Adolfo Cruz.

“How much value, not how much code”: A reflection on productivity in software development with Adolfo Cruz.

Product Development, Project Management

Written by: Adolfo Cruz 

Person using a laptop with analytics and productivity icons projected above the keyboard, representing measurement and software development metrics.
How to measure productivity? That’s a question that many in the business, from CEOs to coders to engineers to managers, have in their minds all the time, and Adolfo Cruz, Scio’s very own Project Management Office director, discusses metrics, measures, and meanings of productivity. At the end of the 90s, a methodology called “Personal Software Process”, or PSP, was designed to help developers measure their productivity. You had to take a course, there was a lot of documentation to follow through, and you had to use a timer to measure your progress, stopping it every time you needed a cup of coffee or to go to the bathroom. The idea was to see how much you accomplished in a day, but in fact, this methodology was entangled too closely with the number of lines you wrote, meaning that you were more productive the more you coded, which is not necessarily true. 

But if this is not productivity, what is it? 

I define “productivity” as finishing a task in a reasonable time. The word “finishing” here is key because productivity is not starting a lot of things, but seeing a project to completion, right until you get a product. However, how do you define exactly when something is “finished” in software development? What criteria do you have to fulfill to say something is done? If we were building something physical, let’s say a boat, first, you need to build a hull, and this phase ends when it fulfills certain requirements.  And although not all boats are the same (building a freighter or a yacht would look very different), in essence, you have the same process, blueprints, and requirements to do it. Software development doesn’t work that way. Developing software involves a lot of things. You may see it conceptualized as a “factory”, or a development team working like a well-oiled machine, where you input requirements and get a product at the other end. But in truth, there’s an artisanal quality to developing software; everyone has their approach and style, and progress changes according to the team you are with. This results in a lively debate where no one agrees on the best way to measure productivity. If you ask a room full of developers how many lines of code they write to see if they are productive, you can get a very heated discussion, because how are you measuring that? The best code is concise and everyone checking it can understand it, so I don’t know how you can see someone writing 10,000 lines of code and conclude he is more productive than someone achieving the same in 500. Maybe it made more sense at a time with no frameworks to build things faster, when everything was a bit more rudimentary and you coded every single piece of the product, but today you have to write very few things from scratch, with a whole range of tools that let you produce, let’s say, the shell of a website in a minute without coding anything directly. 

Where Traditional Productivity Metrics Fall Short

Comparative Overview: Software Development Productivity Approaches

Productivity Approach How It Works Risks Best For
Lines of Code (LOC) Measures output based on how many lines a developer writes. Produces bloated code, encourages gaming the system, poor maintainability. Legacy systems, basic scripting tasks.
Velocity / Story Points Tracks work completed per sprint using Agile practices. Can be manipulated, doesn't always reflect real value to the user. Agile teams, iterative development cycles.
Value Delivered (Scio Model) Measures impact, user value, quality, stakeholder feedback, and stability. Requires strong alignment and communication; harder to quantify. Nearshore teams, complex products, evolving requirements.
In short, this comparison is not just about geography or pricing. It’s about whether your security partner responds within minutes—or the next day. And in cybersecurity, that delay is unacceptable.

So imagine if a company starts giving productivity bonuses based on lines of code produced per project. They would end up with developers gaming the system to get the bonus or at least trying to not look worse than their peers by writing less, resulting in bloated, inefficient products because the incentive wasn’t centered on creating something useful.

You have to be very careful when linking rewards to metrics, or else you’ll generate a perverse environment where everybody is just racing to inflate numbers.

At Scio, we’ve learned that real productivity emerges when teams focus on delivering value, not producing more code. This shift in mindset aligns closely with Agile practices, where outcomes matter more than output. We explore this approach in more detail in our article on how to transition to Agile without compromising product stability: From Waterfall to Agile: How to Migrate Without Losing Product Stability

Hand arranging wooden blocks with icons for goals, processes, teamwork, and analytics, symbolizing Agile productivity.
Agile reframed productivity around what users can achieve — not what systems “shall” do.

The Scio way

I’ve been with Scio for more than 14 years, and since then, perspectives have changed. With the arrival of Agile Methodologies, we moved on from counting lines of code to seeing how that code comes together, achieving working software whose process of development is not focused on numbers, but on how the product is going to be used. To give you an idea of this evolution, not long ago the requirements of a project were written from the point of view of the system, so every requirement started with the phrase “The system shall…”: the system shall do X thing, the system shall do Y thing, the system shall do Z thing, etc.  So you ended up with a massive document repeating “The system shall…” for every little thing. Then the Agile Movement centered on the user, with requirements stating “The Administrator can…” or “The Manager can…” because we understood that software is not about a system that “shall” do things, but what people in different roles “can” achieve with the product, resulting in productivity built around how much value we give to the final user, not how much code our devs write. Coming back to Scio, we see it from the perspective of the stakeholders and clients we are building a product for, and our productivity is measured on the information we get from them, knowing how our teams are doing, how much value they are adding to a project, and what their perception of the whole process is. It’s a more people-oriented approach, far from the days of counting lines of code, and more interested in understanding how a developer is contributing to the goals of our clients.  To that end, we developed some internal tools, like the Team Self-Assessment, based on our prior experiences, consisting of questionnaires about the things we consider important for a team to focus on. For example, there’s an entire section about quality, how they are preventing issues during development, if they are doing Pair Testing practices, or if they are doing code reviews to make sure the code is maintainable and scalable… Are they giving issues the proper attention? Are they documenting them? The team members have to ask themselves if they are focusing on the right issues, and if they aren’t, it’s something we have to improve. That’s how we try to motivate our teams to share their experiences, practices, and insights into our client’s projects. It is said that only 35% of software development projects succeed, and I think it has to do with the planning stage of a product. Let’s say I want to complete the A, B, and C steps of a project in six months, based on previous experiences in similar projects. But it ended up taking 8 months instead of 6 because something needed to change, does that 2-month delay mean the project is going wrong?  It happens a lot with start-ups trying to create something completely new. In the course of development, it’s common to see something, a feature or function of the product that changes the client’s perspective, that taps into some potential we haven’t seen before, so the plan has to get reworked to harness that and bring its full potential. In six months, priorities can change. But if we measure the productivity of the process very rigidly, and then that very same process brings out the value in unexpected places that, nonetheless, force you to rework entire parts of the project, it’s easy to see it as a failure. The Project Management Institute uses these rigid measures a lot, asking for a specific basis, beginning, and end of every phase of a project, and if you don’t deliver them exactly as planned, then you get a mark against you. In an actual software development environment, that doesn’t happen, because the dynamics of a development cycle can change fast.

Software development works by evolution

The measures you have to use are subjective more often than not. Some industries require strictness, especially when manufacturing something, but in the world of software, and start-ups in specific, I don’t think it’s necessary to be like this to create a successful product.

This is why we back away a little from the technical aspects of a project and focus instead on the business side of things, having conversations with stakeholders and product owners to get them involved, reconciling all these points of view about what the business needs, and how development is.

We take a look at the features planned, check how many people ask for them, how critical they are for the business model to work, and decide how to proceed from there, adding real value by focusing on building those pieces first. Technical aspects are solved later, as you first see what the business needs, and then the technical team starts sketching solutions for the challenge.

This perspective is also supported by industry research. McKinsey’s analysis shows that teams who optimize delivery through value-driven Agile practices consistently achieve higher speed, quality, and long-term stability.

Person holding a digital interface with collaboration and network icons, representing modern teamwork and adaptive software development.
True productivity emerges from teams that adapt, collaborate, and deliver outcomes that matter.

Productivity is a question with no definitive answer yet.

Considering all this, forming an exact image of productivity is a question with no definitive answer yet. Every individual has to decide what works, but only in the specific context in which that person is acting, so no one has come up with a universal method to measure productivity in software development, as even the perspective from which you measure can change; seeing it from a client’s perspective is a world apart from a developer’s. As you discover better routes during development that weren’t foreseen during the planning stage, or maybe because the technical aspect ended up being unfeasible for one reason or another, or the infrastructure cost is too high for your purposes, or any other number of reasons, a lot of what you may define at the beginning of the project will change. You adapt, which is very different from building furniture or producing food, where it is clear what you are trying to accomplish over and over. But in software, where there’s no single solution for the same problem, it’s difficult to reach a consensus on what you need to do in detail.  However, you want to measure productivity, metrics evolve, and whatever method you use to decide how productive your team or your company is, I think the Agile Methodologies got it right, where it doesn’t matter the number of lines, or the documentation you have, or how pretty your database is, what matters to the client and the final user is having software that works. In the end, the most reliable measure of productivity comes from how well a team can deliver meaningful outcomes under real conditions. Tools, metrics, and methodologies will continue to evolve, but the ability to collaborate effectively, respond to change, and build software that genuinely supports users remains the true benchmark. This is especially clear in distributed and nearshore models, where alignment, communication, and shared context matter far more than raw output.

FAQs: Measuring Productivity in Software Development

  • Because software development isn’t repetitive or linear. Every team, product, and problem space is different. Unlike manufacturing, software work varies widely in complexity and evolves quickly, making one-size-fits-all metrics unreliable.

  • Not in modern development. More lines of code usually mean more complexity, higher maintenance costs, and increased risk. Effective teams focus on clarity, stability, and value delivered—not code volume.

  • Instead of measuring output, it evaluates impact: user value, product quality, stability, stakeholder feedback, and team alignment. This approach reduces waste and improves decision-making, especially in Agile environments where context matters most.

  • Yes. Nearshore teams working in aligned time zones with strong communication practices reduce delays, accelerate feedback cycles, and deliver features faster. This is especially valuable for U.S. tech leaders in Austin, Dallas, and other fast-moving markets.

The “Jurassic Park” Problem: How to avoid having a rogue IT person wreaking havoc in your business?

The “Jurassic Park” Problem: How to avoid having a rogue IT person wreaking havoc in your business?

Outsourced Engineering Team, Product Development, Project Management

Written by: Monserrat Raya 
Team extension model for software development in Austin and Dallas

The Jurassic Park Analogy: When IT Fails from the Inside

Just like in Jurassic Park, where one insider caused a total collapse of operations, a rogue IT employee can wreak havoc in a modern business. With privileged access, they can:

    • Delete or manipulate sensitive data
    • Leave systems unpatched, opening doors to attackers
    • Create hidden admin accounts for ongoing access

Leak insider information to competitors

Lesson: It’s not always the hackers outside your walls. Sometimes, the threat comes from the inside.

IT has become a vital element of modern businesses. It helps streamline complicated tasks like data management, customer communications, logistic planning, inventory tracking, and much more, and with a reliable IT infrastructure, businesses can identify new opportunities to secure better positions and increase success. Technology also increases the efficiency of employee productivity with tools such as remote collaboration platforms and automation solutions-enhancing operational agility, and (perhaps most importantly), businesses can gain an invaluable understanding of their customers by leveraging Big Data technologies which help gather customer feedback in real-time to make better decisions quickly. All in all, it becomes clear that modern businesses cannot survive without reliable IT support, making it the backbone of every successful organization today.

IT has become a vital element of modern businesses. It helps streamline complicated tasks like data management, customer communications, logistic planning, inventory tracking, and much more, and with a reliable IT infrastructure, businesses can identify new opportunities to secure better positions and increase success. Technology also increases the efficiency of employee productivity with tools such as remote collaboration platforms and automation solutions-enhancing operational agility, and (perhaps most importantly), businesses can gain an invaluable understanding of their customers by leveraging Big Data technologies which help gather customer feedback in real-time to make better decisions quickly. All in all, it becomes clear that modern businesses cannot survive without reliable IT support, making it the backbone of every successful organization today.

The “Jurassic Park” Problem: How to avoid having a rogue IT person wreaking havoc in your business?

However, the importance of IT means that, if not managed properly, this area can become a vulnerable spot for malicious activities. And we are talking about more than outdated systems or weak passwords; a lack of the proper protection and approach to the IT demands of a business can set off a chain reaction that leads to data loss, security breaches, and serious financial damages. To avoid such breakdowns, organizations should remain diligent in their approach to IT – regularly updating their systems and educating staff on how to protect confidential information. But sometimes, even this is not enough. Sometimes, the call comes “from inside the house”.

Let’s take a funny example of what we mean: Jurassic Park, a cinematic classic that depicted the consequences of human curiosity getting ahead of our technical knowledge and abilities. In the movie, the breakdown of the park is set by a chain reaction of deficient approaches to security, management, and technology, really underscoring how vital these security measures are, even for the most cutting-edge technology. Disaster can quickly occur when deficiencies or malicious actors are not addressed appropriately, perhaps offering an allegory for the high stakes involved with managing today’s cyber infrastructure. As illustrated throughout the film, underestimating risks carries great consequences, and whether computing networks, industrial structures, or hybrid environments, a secure foundation is key to avoiding catastrophic repercussions. 

Implementing best practices, such as authentication and encryption protocols, testing networks regularly and actively informing employees about threat scenarios can minimize risk and maximize resilience in any system. By providing a great storyline while emphasizing essential IT principles, this classic film reinforces why taking security precautions should always be considered—now more than ever before. For businesses or organizations handling sensitive data, individuals need to take initiative in understanding their responsibilities and roles in protecting corporate information from cyber-attacks or malicious use.

Red alert icon symbolizing IT security risks in modern businesses
Even a single IT employee with privileged access can disrupt operations.

The human element of IT risk

Arguably, one of the main points of Jurassic Park is showing why having less-than-ideal IT personnel causes all sorts of problems, and can be catastrophic for a business. By the nature of their job, they have access to sensitive data which, when put in the wrong hands, can be used for nefarious purposes, as well as let in malicious actors by neglecting to patch systems or by not monitoring user activity, allowing third-parties access to information they shouldn’t. Furthermore, they can misuse privileged access, delete data, or create accounts with admin privileges to keep the system and networks open to themselves. 

Ultimately, what a rogue IT person can do is put an entire business at risk outside of traditional cybercrime, giving competitors advantageous inside knowledge (just like the character of Dennis Nedry does in the movie) or manipulating software to perform unwanted tasks. Indeed, in most cases, the development of malicious software by an insider is virtually indistinguishable from cyberattacks by outside actors, so taking steps to secure your business and prevent unauthorized changes is essential if you want to protect your assets, resources, and brand reputation. In hindsight, taking full measures to prevent such situations is what protects businesses, ensuring they have policies and procedures in place to monitor the behavior of their IT staff, particularly when it comes to sensitive matters such as data access and storage. It’s important to review logs and technical security measures such as firewalls and system software patches to make sure they are up-to-date. However, you could say that these steps are more about mitigating potential harm done by disruptive people than outright preventing it. What is the best approach, then, to avoid falling into such circumstances?

Rogue IT Risk · Quick Check

Mark what applies to your IT today. Your score updates live.

Score: 0/8
LOW RISK

Good start. Want to validate your IT posture with a nearshore partner?

Let’s review your case

Why Trust Matters Most in IT

Technology evolves fast, but trust is timeless. Businesses need IT staff—and partners—that are both technically strong and trustworthy.

Nearshore Partnerships as a Safeguard

Instead of relying solely on local hires or freelancers, many mid-sized companies in Austin and Dallas are turning to nearshore development partners in Mexico.
Here’s why:

Cybersecurity breach concept with red lock among blue locks
IT insider threats can compromise security as much as external hackers.
IT Delivery Options vs Pros & Cons (Nearshore Mexico vs U.S. In-House & Contractors)
Option Pros Cons
In-House IT (U.S.) Full control, cultural fit High cost, long hiring cycles
Freelancers / Contractors Flexible, quick onboarding Low accountability, inconsistent security
Nearshore Partner (Mexico) Trusted teams, lower costs, real-time collaboration, strong oversight Requires proper vendor evaluation
Business professional handling IT data security with digital padlock interface
Strong IT governance reduces insider risks in modern businesses.

Trust is the name of the game

When it comes to IT, technology alone isn’t enough—trust is what makes systems reliable and secure. A single technician with too much access, or a partner without proper accountability, can expose your business to risks that no software update can fix.

For mid-sized companies in Dallas and Austin looking to build or strengthen their IT departments, establishing trust with anyone who manages sensitive data is critical. That’s why many leaders choose to work with nearshore development partners in Mexico. Instead of struggling to stay on top of every new security patch or compliance requirement, a trusted partner provides:

  • Experienced professionals who bring proven IT governance and security practices.
  • Built-in oversight to reduce the risk of downtime or insider mistakes.
  • Real-time collaboration thanks to shared time zones and cultural alignment.
  • Clear accountability with service-level agreements that freelancers or contractors often lack.

As Rodolfo Cruz, Project Management Officer and Partner at Scio, explains:

“Nearshore development partnerships offer a powerful combination of trust and accountability. Unlike freelancers or one-off contractors, nearshore teams work under formal standards that guarantee quality, accessibility, and long-term peace of mind for businesses.”

Trust also applies inside your organization. Strong IT policies make sure no single person holds too much power, while regular audits and ongoing training keep teams aligned with the latest security protocols. With these safeguards in place—and a nearshore partner committed to accountability—your IT stops being a weak point and becomes a foundation for growth.

Avoiding the “Jurassic Park” problem 

In other words, to prevent rogue IT technicians from creating chaos in the workplace, it is essential to have extensive management policies and procedures in place. The lesson is that businesses must understand the potential risks associated with any technological system they implement, as well as the appropriate steps needed to achieve a safe operation. Individuals and companies alike need to be cognizant of evolving threats to create effective security initiatives. With its exciting plot, Jurassic Park serves as a parable for the need for sound practices in IT; we must remember not all advances come without inherent risk.

So, if you are looking for solutions regarding IT, Nearshore development partnerships can be the perfect solution for mid-sized businesses seeking to streamline their IT management. Companies that are willing to partner with companies in other countries gain access to a more comprehensive network of software engineers and talent with specialized skills. When searching for an effective IT solution, it pays to consider the advantages that come with selecting nearshore development partners. Taking these proactive steps to prevent a potential rogue IT person will minimize future conflicts, protect company assets and ensure everyone is looking in the same direction. As we can see from Jurassic Park, IT security is vital for maintaining a safe and efficient workplace environment, and without proper protocols in place, unauthorized users can access confidential data often leads to a catastrophic result that you can avoid with the proper people on your side.

IT security concept with glowing lock over computer keyboard
Mid-sized companies in Dallas and Austin rely on trusted IT partners.

The Key Takeaways

  • IT is the backbone of modern business. It drives growth and efficiency, but without proper management it can also become a serious vulnerability.
  • Insider threats are real. Just like the Jurassic Park analogy, a single IT technician with too much power can cripple operations and expose sensitive data.
  • Trust must guide every IT process. Having the right people—and the right partners—handling digital infrastructure is critical for long-term stability.
  • Nearshore partnerships provide accountability. For companies in Dallas, Austin, and across the U.S., nearshore teams in Mexico offer the mix of trust, expertise, and real-time collaboration needed to keep operations running securely and efficiently.

Think of us as your extended team, right next door.
Since 2003, we’ve been working with U.S. tech leaders to prevent the kind of “Jurassic Park” IT disasters that keep people up at night. Nearshore means real-time collaboration, cultural fit, and a partner you can count on when it matters most.

If you’re in Dallas, Austin, or anywhere in the U.S., and you want IT to stop being a worry, let’s connect. We’ll listen first, understand your challenges, and then share how Scio can help.

Let’s start the conversation, your trusted nearshore team is closer than you think.

FAQs About Preventing Rogue IT Risks

  • An IT staff member who abuses privileged access, either by negligence or intent, to disrupt operations or leak sensitive data.

  • By partnering with nearshore providers in Mexico that ensure oversight, accountability, and security best practices.

  • Because they operate under formal accountability frameworks, with clear performance metrics and stronger cultural alignment.

  • Regular audits, limited admin privileges, up-to-date patches, and clear reporting lines.

  • Never underestimate insider risks. Trust, oversight, and preparation are essential to avoid catastrophic IT failures.

Beyond Salary & Rate Cards: The Real Total Cost of Software Engineering 

Beyond Salary & Rate Cards: The Real Total Cost of Software Engineering 

Nearshore, Nearshore Software Development, Outsourced Engineering Team, Product Development, Software Development

Written by: Luis Aburto 
Scio TCE Calculator showing real total cost of software engineering beyond salary and rate cards.

A CFO & CTO guide to comparing in-house, offshore, and nearshore

If you’ve ever compared a $120k salary to a $55/hour vendor rate and felt like the decision was obvious, this post is for you. Salary and rate cards are the sticker price. What Finance actually pays – and what Engineering actually lives with – includes ramp time, coordination, security, inefficiencies in collaboration, and a handful of small costs that quietly add up. My aim here isn’t to scare you; it’s to make the math honest so you can choose the right mix with fewer surprises.

I built a Total Cost of Engagement (TCE) Calculator to make these trade-offs concrete. Plug in your assumptions to compare the actual costs of in-house hiring with offshore and nearshore outsourcing side by side. You’ll find the download link at the bottom of the page.

Why total cost comparison beats sticker price

The fastest way to derail an engineering budget is to compare costs on the wrong basis. A salary alone ignores benefits, PTO, tools, recruiting, and management time. A vendor’s rate card hides ramp time, internal oversight, security, travel, and more. Once I normalize these, the option with the apparent lower cost is often just the least complete.

Breakdown of Total Cost of Engagement (TCE) including benefits, bonuses, and hidden costs of software development.
Scio’s TCE framework showing the real cost of software engineering beyond salary — including payroll taxes, benefits, PTO, bonuses, tools, and recruiting.

What I mean by Total Cost of Engagement (TCE)

Total Cost of Engagement (TCE) is an annualized, apples-to-apples number that captures everything you pay to turn ideas into shipped software. The sections below outline the cost elements that belong in a true comparison.

In-house hiring: what sits on top of gross salary

Let’s make this concrete. A Senior Developer doesn’t just cost their base. On top you’ll typically see:

  • Employer payroll taxes & insurance (Social Security/Medicare, unemployment, workers’ comp).
  • Benefits & retirement (health, dental/vision, 401(k) match).
  • PTO cost (holidays, vacation, sick days).
  • Performance/annual bonus (annualized) and stock options/RSUs (annualized).
  • IT equipment & tools (laptop, monitors, peripherals) and software licenses (Office 365, IDEs, Slack/Jira/GitHub, security scanners).
  • Cloud/test environments for realistic integration.
  • Training & development, beyond onboarding.
  • HR & recruiting costs, amortized over expected tenure.
  • Management overhead, because leads and managers spend time coaching and reviewing.
  • Facilities or remote stipend (office, coworking, home setup).
  • Attrition & backfill buffer, if you model churn explicitly.
  • Ad-hoc tooling costs for project-specific devices, services, or environments.
  • In many U.S. contexts, the fully loaded number lands ~35 – 60% above base salary, depending on benefits and your toolset. The TCE Calculator can show this as a waterfall from base → fully loaded so Finance and Engineering can see exactly what drives the delta.
  • CFO takeaway: this is where forecast variance hides – especially bonuses, benefits, recruiting, and training.
  • CTO takeaway: lead times and retention matter as much as cost; continuity reduces rework.

Outsourcing: what sits on top of the rate card

Most proposals show a clean rate. Delivery reality adds layers:

  • Knowledge transfer costs. Expect a few weeks of overlap or slower velocity while context is built. Over time, the KT overhead % depends on the effort required for knowledge transfer and any pilot work. Greater real-time overlap (time-zone alignment) speeds shadowing and code walkthroughs and reduces this overhead.
  • Productivity losses costs. A velocity buffer and rework allowance during early sprints and major scope changes. The delta % here depends on the extra capacity you carry to absorb slower velocity and re-work due to collaboration friction and cultural differences.
  • Team management costs. Product owner, project manager, and architect/tech lead time plus Scrum ceremonies – the coordination tax you pay to keep everyone aligned. The overhead % here depends on time invested by these roles, communication latency across time zones, and the number of asynchronous hand-offs.
  • Tooling & environments. Extra seats, VPN/SSO, CI/CD, scanners, and non-prod data – plus ad-hoc tooling costs that are project-specific.
  • Security & compliance. SOC 2/ISO controls, background checks, DPAs, and data residency constraints.
  • Legal & IP / Administration. Assignment of inventions, privacy addenda, contracting cadence, and local counsel where relevant.
  • Travel & on-site. Kickoff and periodic planning often repay themselves in fewer misunderstandings.
  • FX & payment. If the vendor is not a U.S. company, account for currency spreads, wire/processing fees, and invoice terms.
  • Attrition & backfill. A modest overlap budget keeps continuity when someone turns over. Consider the average voluntary attrition rates in your industry and the typical time it takes to recruit and onboard replacements.
  • Inflation/escalation clauses. Annual adjustments should be explicit, capped where possible, and tied to a known index or collar.

When you account for these, outsourced TCE commonly adds ~20 – 40% on top of the vendor’s published rate over a year. The point isn’t to inflate costs; it’s to avoid being surprised later.

Comparison of offshore vs nearshore software development costs, including time-zone overlap, cultural alignment, and travel expenses.
Offshore vs. Nearshore cost comparison highlighting key TCE drivers such as time-zone alignment, cultural fit, FX invoicing, and travel overhead.

Offshore vs. nearshore: the same categories, different weights

Although both models are common, they differ in TCE drivers – not only the rate card, but also the overhead created by time zones and the collaboration friction they introduce:

  • Time-zone & language overlap. Nearshore teams work the same or adjacent hours, which reduces coordination friction and shortens ramp-up.
  • Travel. A quarterly on-site from Dallas to Guadalajara is simpler and cheaper than a long-haul to APAC.
  • Cultural differences. Communication norms, decision-making, and feedback styles can influence productivity and quality; align working agreements early and use real-time overlap to reduce rework.
  • FX & invoicing. Nearshore engagements are more likely to invoice in USD with smaller FX spreads; offshore corridors may carry higher friction.
  • Attrition & backfill. Patterns vary by market; your buffer should match reality, not generic averages.

The TCE Calculator can generate side-by-side stacks that show how the same project’s TCE shifts between offshore and nearshore with identical assumptions.

  • When nearshore wins: fast feedback loops (agile ceremonies), all-day collaboration in real time, incident response during your business day, and predictable, lighter travel.
  • When offshore still fits: large, well-bounded workstreams where overnight cycles are acceptable and travel is infrequent.

A simple decision guide

Map your situation on two axes: urgency/throughput and compliance/variance tolerance.

  • In-house core + nearshore delivery (Scio). Strong overlap and fast iteration, with travel you can actually budget.
  • Nearshore core + offshore scale. Elastic capacity for well-bounded streams.
  • All in-house. When IP proximity and domain depth outweigh flexibility.

My point of view (Scio): I’ll recommend the mix that fits your throughput, risk, and budget certainty – even when that means not engaging Scio for every role. The calculator helps ground that conversation in numbers, not vibes.

Download the TCE Calculator to run your own numbers, or contact us and I’ll walk through the trade-offs with you.

Luis Aburto_ CEO_Scio

Luis Aburto

CEO