All thoughts

Chasing Exponential Growth

May 2025

Today more than ever, we live in a world that is highly competitive and evolving at an unprecedented pace. When I was younger, technologies like cloud computing and big data re-shaped the industry, today AI is doing the same. It is a no-brainer to realize that such revolutionary technologies will destabilize the industry and inevitably force a shift in the market.

Yet, the tech sector is still growing and the demand for skilled tech professionals remains competitive¹². However this does not mean that the required skill sets remain the same, quite the opposite: they evolve at the same pace. This not a new phenomenon, for example the profile of the average full-stack software engineer in 2010 had significantly narrower skill set compared to the average one in 2025. The quality bar keeps getting raised, and companies are looking more and more for skilled specialists who also have the ability to integrate new technologies into their workflow³⁴.

It is now more important than ever to acknowledge that the once-predictable path of linear skill accumulation no longer suffices to thrive. Instead, we must cultivate an exponential growth mindset, where learning compounds on itself, rapidly accelerating our capabilities.

The Illusion of Linear Growth

For many years, a software engineering career often followed a predictable trajectory: a typical journey might begin with a junior role at a mid-to-large enterprise, where the first three to five years would be spent slowly accumulating experience through often not so challenging tasks. Eventually, this linear progression would lead to a promotion to a senior position, perhaps opening doors to more interesting and challenging work, greater responsibility, or even the chance to specialize deeply within a niche domain. This was the traditional blueprint: a slow and steady climb up a well-defined ladder, where constant, slow growth was the implicit expectation.

This linear progression has become not just inefficient, but increasingly potentially obsolete. The underlying assumption that simply putting in "hours" or accumulating "years" of experience automatically equates to increasing value or sustained relevance is a dangerous illusion. We must be able to look beyond the illusion of growth through promotions and fancy titles. The truth is: how those hours are spent makes all the fundamental difference. The market no longer simply rewards longevity; it fiercely competes for dynamic adaptability and a proactive pursuit of adaptable and cutting-edge capabilities.

This external pressure is compounded by an internal reality. While wisdom and crystallized intelligence grow with age, we know that certain aspects of our fluid intelligence — our capacity for abstract reasoning, novel problem-solving, and processing entirely new information — tend to be strongest in our younger years. This isn't to say learning ceases with age, but rather that the efficient assimilation of novel complex information can require more effort over time. This further supports the strategic advantage of embracing deliberate quality practice early on, maximizing those initial years of peak cognitive fluidity.

The question is no longer if you're learning, but how fast and how effectively you're compounding your capabilities. Therefore it becomes essential to seek the settings that fit as catalysts for growth.

The Catalysts for Exponential Growth

Having recognized the diminishing returns of linear progression, let's explore the key fundamentals that will make any engineer not just better, but a perpetually adaptable one.

Deliberate Practice

The first, and perhaps most important, catalyst is deliberate practice. This isn't simply spending hours repeating familiar tasks, instead, as researcher Anders Ericsson pioneered⁵, true expertise stems from a structured and intentional form of practice aimed at improving specific weaknesses, often just beyond one's current capabilities. For a software engineer, for example, this could mean identifying patterns, algorithms or system designs that pose a challenge and diving into them, or tackling a project with an unfamiliar tech stack. To be truly effective, Deliberate Practice needs feedback loops. Actively seek feedback from more experienced peers or experts to evaluate the quality of the work done. It isn't just about catching errors, it's an invaluable opportunity to learn better patterns, identify anti-patterns and alternative approaches. This continuous cycle of stretching, performing, and critically evaluating the results allows our learning to compound, transforming incremental effort into leaps of understanding.

Lean, rapid iterations

When learning or practicing a new concept or technology, focus on building the smallest viable working prototype that demonstrates the core idea, rather than a more complex production-ready system. Breaking down novel concepts into smaller, more manageable components allows you to quickly try a few different approaches, then observe which works best, which fails, and why. Learning through rapid experiments, you compress the time it takes to gain practical experience.

Cross-Domain Exposure

In an increasingly interconnected tech landscape, deep specialization alone can lead to silos and limited problem-solving capabilities. Cross-Domain Exposure and the cultivation of T-shaped skills are crucial for exponential growth. A T-shaped individual possesses in-depth expertise in one or two core areas (vertical) but also a broad understanding of related disciplines (horizontal). This starts with understanding the "why", which allows you to move beyond how something works to understanding the reason behind its design, its impact on the business, and its role within the larger system. This fosters architectural thinking, problem-solving from first principles, bridging silos, and the ability to find clever solutions to new requirements that go beyond technical boundaries.

Mentorship

No one learns exponentially in a vacuum. Mentorship, Peer Learning, and an active culture of Knowledge Sharing are essential and powerful accelerators. Mentors provide guidance based on years of experience, help you avoid common pitfalls, and provide targeted advice that can dramatically accelerate your learning curve. Their insights provide shortcuts saving you countless hours of trial and error. Peer learning and collaborative problem-solving create immediate feedback loops and exposure to different approaches. Environments that actively encourage knowledge sharing create a collective intelligence that benefits and elevates everyone. Leveraging the wisdom and experience of others, and contributing your own, creates a force multiplier for individual growth.

Ownership

Ownership and autonomy broaden your skill set by necessity. Owning a feature or a system from design to deployment, and even through its operation in production, forces you to learn about every facet of the development lifecycle — architecture, testing, deployment, monitoring, debugging and all the other non-functional requirements to satisfy. You are forced to learn quickly and cross-domain, becoming a full-stack problem solver who's solution-oriented rather than a compartmentalized task executor.

Startups: The Ideal Greenhouse for Growth

We have established that individual drive is paramount when it comes to the catalysts for growth. However, the organizational structure, culture, and operational realities of companies can either act as a powerful accelerator or a subtle inhibitor to rapid skill development. It is important to understand that there is a stark contrast between the lean, dynamic world of startups and the established, often more structured, landscape of large corporations.

Startups are at their core smalls companies born to take on specific hard technical problems. By nature of their necessities to achieve their goals, they embody the catalysts for exponential growth. In a lean startup there is no room for "coasting": every decision, every feature, and every line of code, has an immediate tangible impact on the company's survival. Engineers are constantly pushed to solve novel problems with limited resources and tight deadlines. This process embodies continuous deliberate practice. Rapid iteration is not just a preference but another survival mechanism, encouraging a mindset where experimentation is valued over perfectionism, and "failing fast" becomes the mantra. With small teams and limited specialized roles, startup engineers are required to wear many hats. This broad exposure forces them to cultivate T-shaped skills: individuals need to understand the entire product lifecycle and bridge the gap between the technical and business domains, gaining a holistic perspective. The close-knit nature of teams in startups fosters organic and highly effective learning. Engineers of different experience levels and non-technical people actively collaborate in solving end-to-end problems, leading to constant, informal mentorship and peer learning. Finally, engineers are given problems or broad objectives and are empowered with the autonomy and ownership to build effective solutions. This accountability for success and failure compels engineers to learn deeply and broadly, and serves as a powerful motivator for end-to-end problem-solving. This intense environment comes with its trade-offs: potentially higher risk, less structured processes (and occasional chaos), and much higher stress. However, for those seeking to grow their skill sets, startups offer unmatched opportunities to compress many years of experience into only a few — that's true exponential growth.

In contrast, large enterprises, with their size and intricate layers, can present a more complex landscape and barriers for individuals aspiring to grow. Enterprises thrive on silos: deep specialization, where engineers are often confined to specific components of a system or a single technology stack for extended periods. This can lead to expertise in a narrow area but limit cross-domain exposure, making it harder to gain a holistic understanding of the system and the business impacts. Extensive and processes (e.g. approval chains and release cycles) create overhead and, eventually, result in slower and indirect feedback cycles, with several layers between the engineer and the end-user. This inherently slows down the entire learning process. Pair this with the less emphasis on holistic problem ownership, i.e. problems are broken down to small, well-defined tasks, and it is evident how individual growth becomes diluted and in minute increments. Furthermore, enterprises may offer formal training programs, but organic mentorship and peer learning can sometimes be less prevalent because of larger, distributed teams, and a reliance on knowledge sharing through documented processes rather than spontaneous collaboration. Finally, the imperative to maintain existing, often complex and outdated, legacy systems and the natural aversion to risk of large enterprises limits opportunities for deliberate practice on cutting-edge technologies and any radical experimentation.

The limitations of large corporations are evident, however it doesn't mean that great growth is totally impossible. Proactive engineers shall consciously seek out and create conditions that embody the catalyst for exponential growth shared by startups. Seek out cross-functional projects that require collaboration across different teams or technologies to broaden your exposure to new domains. Look for opportunities to champion new technologies or to introduce new methodologies: push for experimentation. Actively seek out feedback instead of relying on formal reviews. Seek out and build relationships with whom embodies the kind of growth you aspire to. Chase ownership and responsibility beyond your role. And of course, nothing stops you from practicing through personal projects outside of work.

Conclusion

The era of linear career growth in tech is behind us. In a landscape defined by relentless innovation and fierce competition, merely "keeping up" means falling behind. Embracing exponential skill growth: a deliberate, accelerated journey fueled by purposeful deliberate practice, rapid iteration, cross-domain exposure, collaborative learning, and genuine ownership. The power to cultivate this mindset ultimately rests with each individual: it's a choice to prioritize learning velocity over static titles, to seek challenge over comfort, to continuously challenge your capabilities. In a world that won't wait, the greatest asset isn't what you know today, but how fast you can learn what comes tomorrow.

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Food for thought