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Hugo Fonseca

DevOps & SRE at BetVictor. Part-time consultant specializing in AWS, GitLab, and Go. Passionate about AI and LLMs.

Beyond the Hype: An Engineer's Take on the LLM Debate

I. Introduction: The LLM Conundrum in Engineering

Large Language Models (LLMs) have exploded into the tech consciousness, dominating discussions, news cycles, and boardroom agendas. It’s hard to ignore the buzz. Yet, within the engineering community—a group typically grounded in logic and empirical evidence—a fascinating dichotomy has emerged. On one side, there’s palpable excitement about the revolutionary potential of LLMs; on the other, significant skepticism, and sometimes, outright dismissal.

Having spent considerable time exploring this domain, including diving into specialized courses and hands-on experimentation, my conviction in the transformative future of LLMs has steadily grown. This post isn’t about blind advocacy, however. Instead, it aims to delve into the heart of this engineering debate, examining the arguments from both the skeptics and the optimists to foster a more nuanced understanding.

Juggling Act: How to Succeed as a Part-Time Tech Consultant

The Allure of the Side Hustle

In the fast-paced world of technology, the idea of part-time consulting is incredibly appealing. It’s a chance to tackle new challenges, expand your skillset, and boost your income—all while maintaining the security of a full-time job. But as many of us discover, it’s a demanding balancing act. How do you give your best to your primary role, your clients, and still have time for yourself?