Career Advice for Brothers: 2018 vs. Today's AI Shift

Back in 2018, I shared career guidance with my two younger brothers who were at pivotal moments in their professional journeys. One brother was grappling with decisions about his college major, while the other had already enrolled but was contemplating a switch in his academic path. My recommendatio

Back in 2018, I shared career guidance with my two younger brothers who were at pivotal moments in their professional journeys.

One brother was grappling with decisions about his college major, while the other had already enrolled but was contemplating a switch in his academic path. My recommendation to both was straightforward: pursue careers in software development and accounting.

Following my counsel, one brother went on to become a skilled software engineer, and the other qualified as a certified public accountant.

At that point in time, this truly was sound advice. Building software demanded genuine expertise, rigorous training, and there existed robust demand since the majority of companies lacked the internal capability to develop it without bringing on board professionals proficient in coding. Accounting, meanwhile, featured a formidable protective barrier: extensive years of education, in-depth regulatory comprehension, and mandatory professional qualifications. These professions boasted elevated entry thresholds and reliable employment stability.

However, if I were advising them in the present day, my recommendations would differ significantly.

This shift does not stem from these industries declining or becoming obsolete—they remain vibrant and relevant. Rather, the protective barriers around them have transformed dramatically, and failing to recognize this evolution could leave individuals unprepared for the changes ahead.

What Has Changed in the Landscape

The CEO of Anthropic recently made a striking observation that caught widespread attention: the majority of the software developed internally at their organization is now generated by artificial intelligence rather than traditional software engineers.

This statement is not intended as criticism toward engineering professionals. Anthropic continues to operate as one of the most technically demanding companies globally in terms of engineering resources. Yet, it underscores a critical shift in where the true sources of leverage and efficiency now reside.

Software projects that previously required a company to invest $50,000 and several months of a developer's dedicated effort can now be completed in mere days. The hurdles to creating software—such as applications, utilities, and automated systems—are rapidly diminishing. Consequently, the competitive advantage once derived solely from coding proficiency is steadily eroding.

A parallel transformation is underway in the accounting sector. Advanced AI tools are now performing complex tasks like data analysis, transaction categorization, account reconciliation, and financial reporting with a speed and accuracy that would have demanded substantial hours from a qualified accountant in the past. The specialized technical abilities that once formed impenetrable barriers are becoming far more accessible—or, in many instances, entirely bypassable through automation.

The Protective Barrier Has Evolved, Not Vanished

It is essential to emphasize that this narrative is not about artificial intelligence supplanting human workers entirely.

In my collaborations with professionals spanning various sectors, the individuals who are excelling today are not those who have discarded their specialized knowledge. Instead, they are the ones who have augmented their deep domain expertise with a strong command of AI technologies.

Consider a financial expert who possesses profound insight into balance sheets, income statements, and cash flow analyses, and who also excels at leveraging AI querying to uncover hidden patterns, detect irregularities, or simulate various business scenarios. Such a professional can accomplish the output equivalent of an entire team of three.

Similarly, a software developer capable of designing robust system architectures and employing AI to rapidly generate, test, debug, and refine code can deliver projects at a pace that surpasses what a full development team achieved just half a decade ago.

Domain-specific knowledge retains its vital importance—and in certain contexts, it has grown even more critical—since humans are still needed to validate AI-generated results and identify inaccuracies. However, the overarching competency that amplifies all of this is the ability to seamlessly integrate and collaborate with AI systems.

The Three Tiers of AI Proficiency I Advocate

In my coaching sessions with clients, I employ a structured model known as the AI Fluency Levels to guide their progress.

The first tier, AI Assisted, involves utilizing tools like ChatGPT for isolated, ad-hoc activities such as crafting prompts, producing content, and reviewing outputs. This is the stage where the vast majority of users currently operate.

The second tier, AI Workflows, advances to integrating multiple tools and establishing repeatable, automated processes. Rather than manually transferring data between applications, you design streamlined systems that handle these operations independently.

The third and most advanced tier, Building Agents, entails creating and deploying autonomous AI agents capable of managing entire operational workflows with minimal human oversight. This level unlocks the most substantial gains in productivity and efficiency.

Unfortunately, most individuals plateau at the first tier. The transition from level one to level two is precisely where individuals begin to establish a meaningful competitive edge.

The Updated Guidance I Would Offer My Brothers Today

If I were to have that conversation with my brothers now, I would reiterate the core principles from 2018: master the foundational principles of your chosen field thoroughly, obtain the necessary certifications, and cultivate authentic expertise.

Yet, I would append a crucial additional directive.

Develop proficiency in collaborating with AI—not merely as a casual user, but as a strategic partner. This means constructing solutions alongside it, discerning its strengths and limitations, and orchestrating workflows where AI manages the routine, programmable tasks, freeing you to concentrate on high-value decisions that demand human intuition and judgment.

This was the pivotal competency I overlooked in my 2018 advice, yet it stands as the most indispensable skill in today's professional environment.

The professionals I observe struggling are rarely those lacking field knowledge. More often, they are experts in their domains who persist with manual methods, even as their peers layer AI capabilities atop identical expertise to achieve dramatically superior output velocity and scale.

The protective barriers in careers have relocated. The key question for everyone is whether you will adapt and advance alongside them.